The Uncounted: Politics of Data in Global Health 9781108483360, 9781108649544

Table of contents :
Cover
Half-title page
Series page
Title page
Copyright page
Contents
List
of Figures
List of
Tables
List of
Abbreviations and Terms
Chapter 1 Contested Indicators
Chapter 2 The Uncounted: Key Populations
Chapter 3 “Something More than Data”
Chapter 4 Cost-Effectiveness and Human Rights
Chapter
5 Modeling the End of AIDS
Chapter 6 Sustainability, Transition, and Crisis
Chapter 7 Listening to Women
Chapter 8 “So Many Hurdles Just to Leave the House”
Chapter 9 The Panopticon and the Potemkin
Chapter 10 Data from the Ground Up
Reflection Questions
Acknowledgments
References
Court Cases
Index

Citation preview

cambridge studies in law and society

The Uncounted Politics of Data in Global Health S a r a L . M . Dav i s

THE UNCOUNTED In the global race to reach the end of AIDS, why is the world slipping off track? The answer has to do with stigma, money, and data. Global funding for the AIDS response is declining. Tough choices must be made: some people will win and some will lose. Global aid agencies and governments use health data to make these choices. While aid agencies prioritize a shrinking list of countries, many governments deny that sex workers, men who have sex with men, drug users, and transgender people exist. Since no data are gathered about their needs, life-saving services are not funded, and the lack of data reinforces the denial. The Uncounted cracks open this and other data paradoxes through interviews with global health leaders and activists, ethnographic research, analyses of gaps in mathematical models, and the author's experience as an activist and senior official. It shows what is counted, what is not, and why empowering communities to gather their own data could be key to ending AIDS. Sara L. M. Davis is based at the Graduate Institute and the Geneva Centre for Education and Research in Humanitarian Action, in Geneva. She earned her PhD at the University of Pennsylvania and held postdoctoral fellowships at Yale University and UCLA. She was a researcher at Human Rights Watch and founding executive director of Asia Catalyst. She was the first senior human rights advisor at the Global Fund to Fight AIDS, TB and Malaria, and later an independent consultant. Her first book was Song and Silence: Ethnic Revival on China's Southwest Borders (2005). In 2017 her research won the International Geneva Award.

CAMBRIDGE STUDIES IN LAW AND SOCIETY

Founded in 1997, Cambridge Studies in Law and Society is a hub for leading scholarship in socio-legal studies. Located at the intersection of law, the humanities, and the social sciences, it publishes empirically innovative and theoretically sophisticated work on law’s manifestations in everyday life: from discourses to practices, and from institutions to cultures. The series editors have long standing expertise in the interdisciplinary study of law, and welcome contributions that place legal phenomena in national, comparative, or international perspective. Series authors come from a range of disciplines, including anthropology, history, law, literature, political science, and sociology. Series Editors Mark Fathi Massoud, University of California, Santa Cruz Jens Meierhenrich, London School of Economics and Political Science Rachel E. Stern, University of California, Berkeley A list of books in the series can be found at the back of this book.

THE UNCOUNTED Politics of Data in Global Health Sara L. M. Davis Graduate Institute of International and Development Studies, Geneva

University Printing House, Cambridge CB2 8BS, United Kingdom One Liberty Plaza, 20th Floor, New York, NY 10006, USA 477 Williamstown Road, Port Melbourne, VIC 3207, Australia 314–321, 3rd Floor, Plot 3, Splendor Forum, Jasola District Centre, New Delhi – 110025, India 79 Anson Road, #06–04/06, Singapore 079906 Cambridge University Press is part of the University of Cambridge. It furthers the University’s mission by disseminating knowledge in the pursuit of education, learning, and research at the highest international levels of excellence. www.cambridge.org Information on this title: www.cambridge.org/9781108483360 DOI: 10.1017/9781108649544 © Sara L. M. Davis 2020 This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2020 Printed in the United Kingdom by TJ International Ltd, Padstow Cornwall A catalogue record for this publication is available from the British Library. ISBN 978-1-108-48336-0 Hardback Cambridge University Press has no responsibility for the persistence or accuracy of URLs for external or third-party internet websites referred to in this publication and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.

CONTENTS

List of Figures List of Tables List of Abbreviations and Terms 1 Contested Indicators

page vi vii viii 1

2 The Uncounted: Key Populations

45

3 “Something More than Data”

65

4 Cost-Effectiveness and Human Rights

94

5 Modeling the End of AIDS

115

6 Sustainability, Transition, and Crisis

140

7 Listening to Women

173

8 “So Many Hurdles Just to Leave the House”

198

9 The Panopticon and the Potemkin

215

10 Data from the Ground Up

234

Reflection Questions

246

Acknowledgments References Index

248 251 296

v

FIGURES

1.1 1.2 1.3 1.4 1.5 3.1 3.2 3.3 4.1 5.1 6.1 6.2 6.3 6.4 6.5 7.1 8.1 8.2 10.1

vi

90-90-90 targets Estimated resources needed for the Fast-Track approach World map based on HIV prevalence Estimated HIV prevalence in Eastern Cape, South Africa, 2014 Sample indicator, coverage of HIV testing among men who have sex with men Grand Anse Beach, Grenada PEPFAR HIV prevention expenditures in the Caribbean, 2010–17 Global Fund HIV disbursements in the Caribbean, 2010–17 Screenshot: GOALS Express, Nigeria UNAIDS model of the Fast-Track approach Civil society and community representatives at the Global Fund Board table Global decline in HIV-related deaths, 2017 Alarming rise in new infections in EECA, 2017 Diagram of Global Fund eligibility assessment Global Fund presentation on rationale for GNIpc Patricia Asero speaking at a PEPFAR meeting, Nairobi, Kenya CVC size-estimation study partner site visit in Jarabacoa, Dominican Republic CVC/UAB timeline for size-estimation study Civil society “elephant in the room,” UNAIDS Programme Coordinating Board, 2015

page 8 13 15 17 27 66 82 86 103 121 141 144 145 159 167 178 199 200 238

TABLES

1.1 Selected Global Fund KPIs for HIV service coverage, 2014–16 and 2017–22 4.1 Excerpt from Eswatini 2017 HIV investment case, GOALS estimates in millions, USD 6.1 World Bank Country income classifications by income level, 2019–20 7.1 Changes in PEPFAR allocations for countries with high HIV prevalence, 2014 and 2018 8.1 Estimated key population sizes for Eastern Caribbean, 2018 9.1 China’s reported drug users, drug detention, and community treatment, 2013–18

page 34 108 158 182 214 222

vii

ABBREVIATIONS AND TERMS

90-90-90

AIDS aPNS ART CCM CD4 test CDC CHAA COP CVC EECA Fast-Track approach

FES FSW viii

A set of targets in the Fast-Track approach. By 2020, UN member states agreed to ensure that 90 percent of all people living with HIV are tested and know their HIV status, 90 percent of all people with diagnosed HIV infection receive sustained antiretroviral therapy, and 90 percent of all people receiving antiretroviral therapy achieve viral suppression, in which the virus is no longer detectable in their bloodstream. Acquired immune deficiency syndrome, the medical condition caused by HIV Assisted partner notification services Antiretroviral treatment Country Coordinating Mechanism A test that measures how many white blood cells are in the body Centers for Disease Control and Prevention Caribbean HIV/AIDS Alliance Country Operational Plans Caribbean Vulnerable Communities Eastern Europe and Central Asia A strategy launched by UNAIDS and approved by the General Assembly that aims to reach the end of HIV as a public health threat by 2030. The approach encourages countries to focus on the locations and populations most affected by HIV and to concentrate resources in order to achieve the greatest impact. Females exchanging sex Female sex workers

LIST OF ABBREVIATIONS AND TERMS

GBV GDP Global Fund GNP+ GNIpc HIV HSS IBBS Intersex

IPV IRB KELIN KPI LGBTQIA MENA MOH MSM NASCOP NGO OECD OECS OST PEPFAR PLHIV PrEP RSSH SDGs Sex worker

Gender-based violence Gross domestic product Global Fund to Fight AIDS, Tuberculosis and Malaria Global Network of People Living with HIV/ AIDS Gross national income per capita Human immunodeficiency virus (the virus that causes AIDS) Health-system strengthening Integrated bio-behavioral survey A person born with sexual anatomy that does not fit the typical binary definitions of male or female Intimate partner violence Institutional review board Kenya Legal and Ethical Issues Network on HIV and AIDS Key performance indicator Lesbian, gay, bisexual, transgender, queer or questioning, intersex, and asexual or allied Middle East and North Africa Ministry of Health Men who have sex with men Kenya National AIDS and STI Control Programme Nongovernmental organization Organization of Economic Cooperation and Development Organization of Eastern Caribbean States Opioid substitution therapy US President’s Emergency Plan for AIDS Relief Person living with HIV Pre-exposure prophylaxis Resilient and sustainable systems for health Sustainable Development Goals Adult who receives money or goods in exchange for consensual sexual services or erotic performances ix

LIST OF ABBREVIATIONS AND TERMS

Transgender

UNAIDS UNDP UNODC USAID WHO

x

A person whose sense of their personal identity or gender does not correspond to the gender assigned to them at birth Joint UN Programme on HIV and AIDS UN Development Programme UN Office of Drug Control US Agency for International Development World Health Organization

C H A P T E R

1

C O N T E S T E D IN D I C A T O R S

Health service conditions in Venezuela are deplorable. . . . Hospitalization areas without running water, fully contaminated surgery rooms, not enough anesthesia to treat the wounded. Several thousand people with HIV are now without antiretroviral treatment. (Red Venezolana de Gente Positiva [RVG+] 2016, 1)

In June 2016 a network of people living with HIV in the Bolivarian Republic of Venezuela wrote to the Global Fund to Fight AIDS, TB and Malaria in Geneva, Switzerland, to appeal for urgent help. Like other global and national HIV agencies, the Global Fund was established in the early 2000s, in a rapid response to international grassroots mobilization: people living with HIV and those affected by TB and malaria, who came together to march and tirelessly advocate for their right to health. Many were dying because they could not afford life-saving treatment. Early on, this movement won powerful allies, such as United Nations Secretary-General Kofi Annan. He told a summit of African leaders: “AIDS has become not only the primary cause of death on this continent, but our biggest development challenge. . . . Somehow we have to bring about a quantum leap in the scale of resources available” (Secretary-General 2001). The Global Fund launched the following year as an international “war chest,” pooling funds from wealthy countries and private foundations, redistributing them to national health programs in need. The Fund was small, flexible, and innovative; it held to principles of transparency, partnership, performance-based funding, and country ownership. Civil society and government champions made the rounds of 1

CONTESTED INDICATORS

bilateral donors – in Washington, London, Berlin, Paris, Strasbourg, Tokyo – and urged them to renew or increase their support. By 2016, when the letter from Venezuela arrived at the glass tower near the Geneva airport where the Fund then had its headquarters, the multilateral agency was disbursing nearly $4 billion a year to more than 130 countries. The letter, titled “VENEZUELA NEEDS YOUR URGENT HELP” in all caps, depicted a stark catastrophe. The Venezuelan activists wrote that their national currency had depreciated by 900 percent, inflation was 700 percent, and they faced long supermarket lines for such basics as rice or milk: “Literally, we are not only suffering hunger, we are also dying, because our health system is totally collapsed” (RVG+ 2016, 2). Their lives had been measured in decades, but now were counted in years or months. They urged the Fund’s leaders to send antiretroviral treatment – or at least, “Come to Venezuela immediately, come visit us to assess with your own eyes and confirm that we are not exaggerating, and that our suffering is real” (ibid.). The Global Fund often receives appeals, but not usually from countries like Venezuela. The oil-rich country was a model of public health in Latin America: it had largely eliminated malaria (Griffing, Villegas, and Udhayakumar 2014). Venezuela had never been eligible for Global Fund assistance. The answer the Global Fund sent, seven months later, was a definite no: “We regret to inform you that the current policy framework does not allow the Global Fund to provide funding to Venezuela,” wrote Board chair Norbert Hauser and executive director Mark Dybul. They explained: “The Board is guided by its approved Eligibility Policy, which annually determines the countries eligible for Global Fund funding. Eligibility is determined by a country’s income level, measured by an appropriate economic indicator of the World Bank, and official disease burden data” (Hauser and Dybul 2017). Faced with a raw, desperate appeal, the Fund had fallen back on a policy built on indicators – what Sally Engle Merry (2011) calls the “tools of global governance.” Activists posted the Global Fund’s letter online, and a wave of public outrage followed. International AIDS activists feel a strong sense of ownership of the Fund; some serve on its governance board. An online petition, “Help people with HIV in Venezuela,” circulated on social media. Within days more than a thousand people had signed. Some activists said that the Global Fund had forgotten its mission. The Global Network of People Living with HIV (GNP+) called on the 2

CONTESTED INDICATORS

Fund to “live up to its mandate . . . and save lives” (GNP+ 2017). The head of the AIDS Healthcare Foundation wrote a scathing open letter, accusing the Fund’s managers of “deep ignorance or indifference to the world events beyond the insular bubble of Geneva” (Business Wire 2017). Were they indifferent? Several Global Fund managers were privately stung by these accusations. The Fund had limited resources and multiple crises to respond to, and could not fund everything. They were following a strategy aligned with global goals. While the crisis in Venezuela sparked fury from an empowered, vocal civil society, Global Fund staff were working long hours on larger, older crises in Africa, which drew less media interest. A few international activists were unimpressed by this defense. They speculated that bilateral donors on the Global Fund Board might be working behind the scenes to block aid to Venezuela, an authoritarian socialist state. One activist told me that among the reasons why the Fund had found the country ineligible, “The main one that is usually not explicit, just implicit, is the political consideration by donors [to the Fund] that they don’t like a country with a government like Venezuela receiving international aid.” But the Global Fund Secretariat in Geneva insisted that it was following policies approved by its Board – a Board whose voting members happened to include some of the very civil society organizations now denouncing the agency in the press. The debate wore on like this for two years. The Venezuela controversy points to a larger problem – one with no easy solution. The global HIV response has received more funding than almost any other disease in the world. It is not enough. Tough choices must be made: in the race to end AIDS, some people will win and some will lose. Globally and locally, HIV traces the vectors of inequality; the valleys and hills of a landscape scarred by centuries of colonialism, discrimination, and domination. But where the funding goes, in the end – who lives or dies – comes down to data. A massive effort to scale up HIV treatment access to meet ambitious global goals, goals that were developed using mathematical models, is running into problems created by messy, on-the-ground realities, and increasing the pressure on donor agencies. As discussed below, the world committed in 2016 to “ending AIDS” by 2030. Funds are limited, and agencies like the Global Fund must demonstrate clear, measurable progress to the public in order to replenish their funds. Data has become 3

CONTESTED INDICATORS

key to measuring and communicating this success, as part of the global rise of “audit culture” (Strathern 2000). Thus donors and governments try to set objectives and indicators, and monitor progress with quantitative data. But the indicators used to make decisions are relatively blunt instruments, in comparison with the complex environments in which HIV thrives; and the data is plagued with holes. As we will see, both what agencies measure and how they measure it are problems actively contested and debated – in many ways, the global HIV response is at the early stages of a steep learning curve in this regard. At every level, there are people and realities that are left unprioritized and uncounted. The Venezuela controversy highlighted some of these quantitative cracks in the global health aid architecture. As it happened, it also ratcheted up pressure on the Global Fund just at the moment when the institution was about to revise some of its indicators. I had the opportunity to observe and contribute to this process, as a consultant advising civil society activists on the agency’s Board. This book draws on interviews with leaders in the global HIV response; analysis of global health tools, budgets, and policies; and ethnographic field research, to explore the ways that data and indicators in global health are selected and constructed, and what they sometimes fail to capture. A good example of this is the oftendebated in Global Fund Eligibility Policy. As the Fund’s leadership wrote in their reply to Venezuelan activists, the Board had approved an Eligibility Policy to focus resources and intensive efforts in order “to achieve maximum impact in the countries and regions with the highest burden of disease and the least economic capacity to respond” – especially, in Sub-Saharan Africa (Hauser and Dybul 2017; The Global Fund 2016). The policy aligned with existing overseas development aid criteria used by many bilateral donors that contribute to the Global Fund and sit on its Board. First, the Global Fund assesses countries’ “economic capacity to respond” to health needs using Gross National Income per capita (GNIpc). But as GNIpc is one number calculated once a year, it does not capture many economic factors or reflect any fast-moving crises. The World Bank uses this indicator to classify countries as low-income, middle-income, or high-income (discussed in more detail in chapter six). When Venezuelan activists wrote to the Global Fund to appeal for aid in 2016, Venezuela’s GNIpc was $13,080, and the World Bank classified it as “high-income.” While activists lobbied and the Board 4

CONTESTED INDICATORS

debated what to do, hyperinflation and plunging oil prices worsened the crisis, and the country’s income plummeted. The next year Venezuela was an “upper-middle-income country.” A country may appear middle-income on paper, as Venezuela still did in the midst of its collapse, but that national income is not likely to be equally shared among a country’s yacht clubs and its shantytowns, or to reflect poor health. Because GNIpc does not capture the complexities of health, the Eligibility Policy also uses other indicators to sort through the long list of countries classified as “middle-income.” One of these is “disease burden”: the percentage of people currently living with HIV in the general population, or the percentage living with HIV among “key populations.” Key populations are groups whose high-risk behaviors and social marginalization put them at higher risk of HIV: as elaborated below, they include men who have sex with men, people who inject drugs, people in prisons and other closed settings, sex workers, and transgender people (WHO 2016, xii). Upper-middleincome countries with a high enough level of HIV burden could still be eligible for the Global Fund. However, Venezuela lacked health data for purely political reasons. First, all health data was censored. Venezuela’s president adamantly denied there was any crisis for people living with HIV – or indeed, that anything was wrong with the health system at all – and refused any overseas assistance. He forbade publication of official information that might contradict this sunny picture of good health. It was difficult to hide the catastrophe. Venezuelan physicians and civil society activists gathered their own data, and despite frequent electricity blackouts and the risk of government retaliation, they found ways to send the information to international allies. A report from Human Rights Watch (2016a) drew on this to reveal staggering hospital shortages: aspirin, antibiotics, and first aid supplies. Journalists smuggled out videos and interviews showing “cascading medical crises” in hospitals (Faiola 2016). But when the Ministry of Health published suppressed government reports that showed an alarming rise in infant and maternal mortality, the president fired the health minister (BBC 2017). The Global Fund relies on official health data, reported by national authorities to the UN, to determine eligibility. It did not use information from advocacy groups like Human Rights Watch. The Joint UN Programme on HIV and AIDS (UNAIDS) was established in 1996 to coordinate and support the global HIV response across UN agencies 5

CONTESTED INDICATORS

and member states. UNAIDS gathers data on HIV from countries on a regular basis, verifies wherever it can, and shares this official data with the Fund for decision-making purposes. But because of official censorship, the most recent data UNAIDS had on HIV in Venezuela was years out of date. Experts at UNAIDS told me that they believed Venezuela probably had high rates of HIV transmission among men who have sex with men, like neighboring countries in the region. If they could have proven this, Venezuela would have been eligible. However, homosexuality and nonconforming gender identities are highly stigmatized in Venezuela, so official national data on men who have sex with men simply did not exist. When countries had no data on HIV among key populations, the Fund’s policy was to treat this lack of data as a zero. International activists lobbying for aid to Venezuela found peerreviewed studies showing soaring HIV prevalence among the indigenous Warao people and shared these with the Global Fund. But the Fund policy was to determine eligibility based on HIV prevalence among the five “key populations” officially recognized by the World Health Organization (WHO) and UNAIDS; indigenous people were not a recognized “key population” (International Council of AIDS Service Organizations [ICASO] and Accion Ciudadana Contra el SIDA [ACCSI] 2018, 24). Venezuelan people living with HIV were caught in a policy vortex created by numbers and the absence of numbers. All the official data they needed to be eligible for medical aid was out of date, censored, missing, or about the wrong people. The Venezuelan activists and their international allies were not so easily discouraged. From 2016 to 2018, they published reports, wrote letters, protested, and briefed delegations on the Global Fund Board (as a consultant, I contributed to one report and supported the Developing Country Nongovernmental Organization [NGO] Delegation to the Global Fund Board in researching and drafting their position). In May 2017, the Global Fund Secretariat drafted a decision for the Board to consider on funding for Venezuela. With the Eligibility Policy and key disease strategies in alignment, and the government continuing to deny that it needed aid, it was no surprise that this proposed decision was voted down. Even if an exception to the policy were to be made for Venezuela, some argued, there was not much excess money sitting around unallocated: it had all been promised to other countries. However, acknowledging that the current policy framework would not 6

AMBITIOUS GLOBAL GOALS

support the flexibility it needed to respond to crises in ineligible countries, the Board also directed a working group to tackle the problem (Global Fund 2017). Finally, in May 2018, nearly two years after the letter arrived in Geneva, the Board approved a policy on “Non-Eligible Countries in Crisis,” which resulted in a commitment to send US$5 million in antiretroviral treatment to Venezuela (The Global Fund 2018). The Board vote was unanimous, with a standing ovation. This small victory for activism over indicators was another example of what makes the global HIV response unique: numbers are powerful, but advocacy is encoded in its DNA. * After over a decade of growth, the global HIV response is at a turning point, with billions of dollars and millions of lives at stake. Ambitious global goals, combined with increasingly limited resources, have created a drive for data to make decisions and measure progress. While there has been real progress, the world is not on track to reach the targets set for 2030. To understand the politics shaping the pressure for data discussed throughout this book, this chapter will give an overview to these political and economic forces, and show how indicators used to measure progress are contested and debated. A broader literature, discussed later in this chapter, has critiqued the power of indicators used in global governance. This book builds on that work, and also argues that some critics may have missed the fluidity and rapid evolution of these tools, as well as the role played by civil society and community representatives in contesting data and indicators at both grassroots levels and the highest levels of global governance. That unique role, and the experience of trying to navigate politics of quantification in the HIV response, may offer lessons for broader consideration in other areas of global health. AMBITIOUS GLOBAL GOALS: THE END OF HIV

In approving the Sustainable Development Goals (SDGs) in 2016, the UN General Assembly committed to “end the AIDS epidemic” by 2030 (General Assembly resolution 70/1, 16). They also resolved, “As we embark on this great collective journey, we pledge that no one shall be left behind” (ibid., 2). Committing to “ending AIDS” was ambitious, and more ambitious than the previous Millennium Development Goal 7

CONTESTED INDICATORS

EMPHASIZING VIRAL SUPPRESSION AMONG PEOPLE LIVING WITH HIV

90%

90%

90%

of people living with HIV know their status

of people living with HIV who know their status are on treatment

of people on treatment are virally suppressed

Figure 1.1 90-90-90 targets. Credit: UNAIDS

(MDG) had been, but mathematical models had shown persuasively that it was feasible. With the endorsement of the UN General Assembly, UNAIDS was tasked with developing a strategy that could achieve the goal. They presented the resulting “Fast-Track approach” to cosponsoring UN agencies and member states, and this was also approved by the General Assembly the following year (UNAIDS 2016; General Assembly resolution 70/266). The Fast-Track approach has been the strategy followed by global HIV agencies and donors since 2016. It is an approach that encourages national HIV programs to focus on the locations and populations most affected by HIV, in order to achieve the greatest possible impact. They set out a long list of and targets, including targets for eliminating gender inequality violence, targets for ending HIV-related discrimination, and more (UNAIDS 2016, 2–4). The central set of testing and treatment targets UNAIDS set for the year 2020 are known as “90-90-90,” and most funding and programming homed in on that goal (see Figure 1.1). The 90-90-90 targets built on the “HIV treatment cascade”: a series of successive stages highlighting what proportion of individuals are engaged in each stage (Gardner et al. 2011). By 2020, these targets were: • 90 percent of all people living with HIV are tested and know their HIV status 8

AMBITIOUS GLOBAL GOALS

• 90 percent of all people with diagnosed HIV infection receive sustained antiretroviral therapy, and • 90 percent of all people receiving antiretroviral therapy have viral suppression (UNAIDS 2017). The logic behind the “end of AIDS” slogan and the 90-90-90 targets can sometimes create confusion, so it may be helpful to briefly explain it before going further. While HIV is rarely discussed in media at the moment, it remains widespread among key populations everywhere and in the general population in some high-prevalence countries. An estimated 37.9 million people are living with HIV globally in 2019. Fewer than half, or approximately 23.3 million, are on antiretroviral treatment (UNAIDS 2019a, 6). Each year, more people newly contract the virus. The end of AIDS was not a campaign to eradicate the virus. Epidemiologists talk about disease control when transmission is reduced; elimination when transmission is halted in a specific geographic area, such as a country; and eradication when the disease is permanently reduced to zero cases. Without a cure, eradication of HIV is only a distant dream, and no country – not even wealthy countries with robust health systems – has yet achieved HIV elimination. In fact, WHO does not currently have a process to validate that a country has achieved HIV elimination, as it does for other epidemics (WHO 2018).1 If HIV elimination were within reach anywhere, a validation process would surely exist. However, control of HIV (i.e., sharply reducing transmission) is an achievable goal. People diagnosed with HIV infection who sustain antiretroviral therapy for long enough can live long and healthy lives and can reduce their viral load (the amount of HIV in the bloodstream) to the point where the virus is undetectable. People with undetectable viral load cannot transmit HIV to others: as the slogan goes, “U=U,” undetectable = untrasmittable. As discussed further in Chapter 5, infectious disease models created by researchers in the 2010s predicted that a rapid, unprecedented global scale-up of antiretroviral treatment, scale-up to the 90-90-90 targets, could trigger a phase change that would sharply reduce HIV transmission in countries where prevalence was high in the general population, such as India or Uganda. 1

The WHO does validate that countries have eliminated mother-to-child transmission of HIV and syphilis.

9

CONTESTED INDICATORS

The critical step was, of course, the first 90 of the 90-90-90 targets: estimating an accurate baseline number of people living with HIV in each country, and then persuading 90 percent of them to take the HIV test and know their status. Unless this target was reached, the rest of the treatment cascade would fall far short of the end of HIV. Ninety percent of a handful of people is failure. This was the logic behind the Fast-Track approach. The race to reach the 90-90-90 targets was on, and the prestige would be greatest for those who reached the targets first. UNAIDS sets Global AIDS Monitoring indicators, based on the global targets, which governments report on annually with data gathered from health facilities (UNAIDS 2019).2 UNAIDS reviews and posts the resulting data online. In July 2017, UNAIDS reported that seven countries had achieved 90-90-90: Botswana, Cambodia, Denmark, Iceland, Singapore, Sweden, and the United Kingdom (UNAIDS 2017, 10). In sharing this news, UNAIDS executive director Michel Sidibé wrote, “When I launched the 90–90–90 targets three years ago, many people thought they were impossible to reach. Today, the story is very different. . . . I remain optimistic” (UNAIDS 2017, 6). By 2019, the story was less optimistic. Sidibé had resigned from UNAIDS under a cloud, and updated data had reduced the list of countries to six. Botswana and the UK had reached 90-90-90 and remained there; Cambodia, Iceland, Singapore, and Sweden were off the list after UNAIDS’ review of their updated data; while Eswatini, Namibia, and the Netherlands were newly listed as having reached 9090-90 (UNAIDS 2019a, 82). By the time this book is published, it will probably be clear that most of the world has not reached the 90-90-90 targets. However, in 2016, with the deadline of 2020 not far away, countries with high rates of HIV were under pressure to reach the targets. It is not new for public health to rely heavily on quantitative data, and the current historical moment is one in which many actors are exponentially increasing the quantity and granularity of datagathering for private purposes (Adams 2016; O’Neill 2019; Zuboff 2016). But the 90-90-90 targets created an even more urgent drive for data on HIV for countries, and for donors financing national HIV programs. 2

Previously, UNAIDS used a similar system called the Global AIDS Response Progress Reports, or GARPR.

10

DECLINING GLOBAL FUNDS

DECLINING GLOBAL FUNDS

With the General Assembly approval of the Fast-Track approach, UNAIDS began to work with modelers again, this time to estimate the cost of the strategy. The numbers quickly became concerning. Here, in order to understand the pressures that donors put on aid recipients, it may be useful to also consider the pressures donors face themselves. The global HIV response has created a system of transnational financial flows among institutions, and as a result, most donors have their own donors to appease, resulting in some fluctuation in funding. UNAIDS had designed the Fast-Track approach at a peak of global HIV funding in 2013–14. In 2016 UNAIDS estimated that rapid scaleup of the interventions needed to implement the Fast-Track approach would cost US$7.4 billion each year in low-income countries, $8.2 billion in lower-middle-income countries, and $10.5 billion in upper-middle income countries: a total of $26.1 billion a year (Stover et al. 2016; UNAIDS 2016a). (Since their main audience was bilateral donors, they did not estimate the cost in high-income countries.) This estimated cost would leave a projected shortfall of about $6 billion per year (UNAIDS 2016a, 8). Where would the world find $30 billion between 2015 and 2020? UNAIDS suggested that lower-middle income countries could increase their share of domestic financing and become more selfsufficient (UNAIDS 2016a, 11). Matt Kavanagh, at the international advocacy organization HealthGap, called this “magical thinking” by UNAIDS (2016). It assumed, he said, that in the next five years, lowincome countries could increase domestic funding by 450 percent, while lower-middle income countries would increase domestic funding by 530 percent. Meanwhile, he pointed out, donor countries were only being asked to increase their contribution by 31 percent. The US, UK, and European countries, among others, had been bankrolling the global HIV response for decades. Their support had risen in the early 2000s, dipped after the 2008 global economic downturn, and had begun to rebound in 2013–14. By “ending AIDS” through one last massive push, they could also end, or at least reduce, that funding obligation. The funds saved once HIV was under control could be applied to other urgent problems, including some closer to home. The idea of “one big push” to end AIDS was appealing. However, just as the bill to make this last push was being discussed in UNAIDS and donor countries, a tectonic political shift hit the two 11

CONTESTED INDICATORS

leading donors. In June 2016, UK citizens voted to leave the European Union. Five months later, the United States elected Donald Trump president. At this moment of volatility, the public debate over external aid reached fever pitch in the European Union, the United Kingdom, and the United States. Growing xenophobia and preoccupation with internal politics was increasing the reluctance of US and British citizens to fund the needs of refugees, respond to climate change, end HIV, and other external goals. Development assistance for health flatlined and began to slip downward again. From 2010 to 2018, HIV funding from donors other than the United States declined by more than $1 billion (Kates et. al. 2019). In 2018 alone, development assistance for health dropped 3.3 percent globally (IHME 2019, 14; OECD 2019). The future trends were grim, with growing uncertainty about the future of the British economy; in his first years as president, President Trump proposed sweeping cuts to the Global Fund. These cuts were resisted by Congress, but the threat remained real (Friends of the Global Fight 2019). As the largest bilateral HIV program, the largest donor to the Global Fund, and the largest donor to UNAIDS and WHO, the US role in the global HIV response was decisive. Anxiety over its future role has been exacerbated in part by the steady decline in European bilateral aid for HIV. The UK and France are the second-largest donors. Smaller bilateral funders, such as Japan, Germany, the Netherlands, the Scandinavian countries, and multilateral financing mechanisms such as the Robert Carr Fund for Civil Society Networks have all played their role. But none of these would fill the gap if the US or UK ended or sharply reduced their support. International organizations have pushed for and successfully persuaded implementing countries to increase their share of domestic co-financing, but not enough to compensate for decreasing external aid (see Figure 1.2). Thus, for the United States and United Kingdom, retaining the strong support of Congress and Parliament was critical to the reauthorization of budgets. Their bilateral HIV programs and the Global Fund all needed to clearly communicate, both to the public and to legislators, that the HIV response was an unambiguously sound investment, that it was saving lives, and also that it would not last forever: one last big push could bring the end of AIDS. The Fast-Track approach implied that one day there could be an end to donor AIDS fatigue. But to get there, donors would need to husband their shrinking resources and make every dollar or pound count. 12

RESOURCE AVAILABILITY IN DANGER OF FALLING SHORT OF GLOBAL COMMITMENTS 30

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Figure 1.2 Estimated resources needed for the Fast-Track approach. Credit: UNAIDS

CONTESTED INDICATORS

TARGETING LOCATIONS AND POPULATIONS

The combination of ambitious global goals, shrinking resources, and the Fast-Track focus on impact created a change in the conversation about HIV in 2013–18. Leaders in the HIV sector began talk more frequently about the need to be “strategic” and to “maximize impact.” Countries and organizations were told to pare down unnecessary expenditures, use evidence-based interventions, and demonstrate rapid progress toward 90-90-90. The language and thinking of cost-effectiveness began to dominate, especially in high-prevalence countries. This focus had a logical rationale grounded in business strategy. As UNAIDS Strategic Information director Peter Ghys said in our interview in July 2019: Currently there’s about 7.7 million people living with HIV in South Africa, so it makes a lot of sense that you have to at least address that. Otherwise, how will you address the world, which has five times more people living with HIV? If you just focus on countries that have small numbers of people living with HIV, you will have some effect – but if you have that effect in small numbers, you don’t really affect the global epidemic.

The US President’s Emergency Plan for AIDS Relief (PEPFAR) perhaps best exemplifies this strategic approach to prioritization. As noted above, PEPFAR is the largest bilateral funder for HIV and the largest donor to the Global Fund. It is based in the US Department of State, where it coordinates the work of seven US government agencies and departments. Its 2017 budget of $6.75 billion included $1.35 billion to the Global Fund, and over $5.2 billion for bilateral HIV programs (PEPFAR 2016). As Congress prepares to approve PEPFAR’s budget each year, the global HIV response goes through repeated bouts of anxiety, with insiders swapping rumors in private and tweeting out encouragement in public as they wait for news. The amount is not usually in suspense, unfortunately: while other global HIV funders have reduced their contributions, PEPFAR’s budget has stayed flat for a decade. At times in the past, PEPFAR has worked in up to fifty countries: today, it focuses those funds on just thirteen highprevalence countries. Figure 1.3 shows a map with country size depicted relative to the estimated number of people living with HIV in each. It depicts the rationale behind the agency’s focus on Sub-Saharan Africa, while increasingly divesting from, or “transitioning out of,” many lowprevalence middle-income countries in Eastern Europe, Central Asia, Asia and the Pacific, and Latin America and the Caribbean. 14

Figure 1.3 World map based on HIV prevalence Credit: U.S. President’s Emergency Plan for AIDS Relief (PEPFAR)

CONTESTED INDICATORS

I interviewed Ambassador Deborah Birx, the US Global AIDS Coordinator who heads PEPFAR, by phone in July 2019, and asked her about this focus. She said: “Honestly, we don’t have unlimited resources. Obviously we’ve had the same budget since 2009, but the epidemic has grown significantly since 2009 – because we’ve kept people alive, and that’s terrific. But the needs, and the different equitable needs, have really dramatically changed.” A senior US official working with PEPFAR, who requested anonymity because they were not authorized to speak on behalf of the agency, agreed: “You can’t dispute that with declining resources, we must focus on impact. The fact is that we know there are hundreds of thousands of people not accessing treatment because we don’t have enough money.” To implement the Fast-Track approach, attention was focusing now on just reaching 90-90-90 in a subset of countries in Sub-Saharan Africa. These countries would simultaneously cut costs, focus efforts, and find all those estimated to be living with HIV, scaling up treatment rapidly. Targeting services where they were needed most, in this way, would in fact deliver greater impact than would addressing HIV uniformly across the general population. For example, countries could focus on locations: using epidemiological data to produce heat maps that showed where the epidemic was concentrated, national health planners could better position clinics and hospitals in HIV “hotspots,” where they were needed (see Figure 1.4). As Figure 1.4 shows, clinics and hospitals have sometimes not been sited in locations where they are needed most. However, HIV is not solely transmitted based on location: behaviors increase the risk. HIV transmission was highest in some countries among adolescent girls and young women, and in all countries, it was high among key populations. Thus, the UNAIDS-Lancet Commission argued, HIV programs needed to not just be sited in the right places; they also needed to be “tailored to the needs and contexts of specific populations” (Piot et al. 2015). What did that mean in practice? Here the role of UN organizations was needed. While the Global Fund, bilateral HIV programs, and private foundations such as the Bill and Melinda Gates Foundation invest in interventions and programs, UN agencies do not, generally, act as major donors. The role of WHO and some other health programs at UN agencies is to review the best available scientific evidence, consult with experts, develop normative guidelines, and advise countries on how to apply them in practice. WHO and UNAIDS set out to 16

Figure 1.4 Estimated HIV prevalence in Eastern Cape, South Africa, 2014. Credit: Health Policy Project

CONTESTED INDICATORS

do this for programs for key populations. They reviewed scientific evidence and consulted with global civil society representatives to produce Consolidated Guidelines on HIV Prevention, Diagnosis, Treatment and Care for Key Populations (2016), which set out the definitive groups to focus on and the services they needed to combat HIV. Key populations, they concluded, were “defined groups who, due to specific higher-risk behaviours, are at increased risk of HIV irrespective of the epidemic type or local context. Also, they often have legal and social issues related to their behaviours that increase their vulnerability to HIV” (WHO 2016, xii). As noted above, WHO identified five groups as key populations: • Men who have sex with men, a term that includes men who identify as gay, as well as men who also have sexual relationships with women; this population faces high risk of HIV, as well as criminalization and stigma in many countries (Beyrer et al. 2012). • People who use drugs: Rates of HIV infection are similarly high among people who use drugs, particularly those who share needles. One in eight people who inject drugs are believed to be living with HIV (UNAIDS 2019b, 9–11). People who use drugs also face higher risks of hepatitis B and C and tuberculosis, and higher rates of violence; most countries criminalize drug use and possession (ibid.). • Sex workers: Sex workers also face high risk of HIV. Male and female sex workers in all their diversity face stigma, discrimination, and police abuse, as well as the threat of violence from clients and others (Baral 2015; Sluggett 2012; Sukthankar 2011). While condoms are essential in HIV prevention, many courts use condoms as evidence in criminal charges of prostitution, undermining public health efforts (Overs and Loff 2013; Shen and Csete 2017; Shields 2012). • Transgender people: Transgender people, whose assigned sex at birth differs from their gender identity or expression, face extremely high rates of HIV: an estimated 19 percent of transgender women are living with HIV (UNAIDS 2014, 3). Reviews of studies have found that stigma and discrimination were also determinants of poor health for transgender people, and that they are in urgent need of prevention, treatment, and care services (Baral et al. 2013; Reisner et al. 2016). • People in prisons and other closed settings: Among the tens of millions of people in detention or incarceration, HIV prevalence is estimated to be “twice to ten times higher than in the general population,” and 18

TARGETING LOCATIONS AND POPULATIONS

it is fueled by widespread sexual violence, drug use, stigma and discrimination, and lack of access to condoms or clean needles (WHO 2016, 5). Due to criminalization, many of the other key populations are also incarcerated at some point in their lives, exacerbating their risk. To address the needs of these five key populations, WHO recommended countries adopt a specific package of health interventions. These included HIV prevention; harm reduction services, such as needle-syringe programs and drug dependence treatment including opioid substitution therapy (OST), for people who use drugs; HIV testing and counseling; HIV treatment and care; prevention and management of co-infections and co-morbidities; and sexual and reproductive health services (WHO 2016, 3). In addition, in a breakthrough, WHO also recommended that countries reform laws, by decriminalizing “behaviors such as drug use/injecting, sex work, same-sex activity and non-conforming gender identity and toward elimination of the unjust application of civil law and regulations against people who use/inject drugs, sex workers, men who have sex with men and transgender people” (WHO 2016, 5). Decriminalization is distinct from legalization. With legalization, a country develops laws and policies to regulate a certain behavior. In decriminalization, the country simply eliminates any legal penalties. As discussed in Chapter 2, people who use drugs, sex workers, and sexual and gender minorities have long called for decriminalization, because it removes the state, especially police, from intrusive management of their lives – management that often results in abuses. With publication of these guidelines, from the global level down to the local level, the focus of donors and implementers under the FastTrack approach was now clearly aligned. The SDGs had called for no one to be left behind, and if this approach were followed as planned, no one should be. High-prevalence, developing countries were the focus of donor efforts and of technical support by UN agencies. These countries were encouraged to review their epidemiological data, map hotspots, and develop “investment cases,” setting out the strategy they would use to achieve maximum impact with limited funds. They would develop these investment cases, where needed, with support from technical assistance providers using cost-effectiveness software to recommend the optimal mix of interventions to achieve these goals. 19

CONTESTED INDICATORS

As for the other countries that were middle-income or upperincome and had epidemics largely concentrated among key populations, the thinking was that these countries could now afford to manage their own HIV programs. They would presumably develop the “political will,” as was often said in Geneva, and do what was needed to fulfill the global plans that they had also endorsed in the General Assembly. Venezuela was not on this mental map of global health, as it is literally not on the PEPFAR map, above.3 But this is natural, because the nature of setting global goals and a global strategy is to make difficult choices: it means setting priorities, which means choosing to deprioritize some things. To develop a strategy means not only deciding what to do, but also what not to do; to find the balance between the things that count and the things that will be left uncounted. At the same time, the Fast-Track approach was not just a strategy, but a communications tool. The “end of AIDS” was a story about the future that would be compelling and persuade undecided people to care. Bauman calls storytelling a “species of situated human communication” whose meaning is shaped by external politics and social factors (1977, 8). Certain kinds of public communications, he says, can be compared to Plato’s “noble lie,” an inspiring myth about the Republic that Socrates imagined could persuade diverse citizens to think of one another as brothers, despite the reality of inequality (Bloom 1968, 93). The Sustainable Development Goals perform this function in a period of human history where inequality is widespread, setting aspirational targets that tell a story about global unity meant to inspire our best selves. To call the “end of AIDS” a noble lie is not to say that it was immoral or dishonest. As a later chapter will show, the objectives were arrived at honestly, and were aimed at inspiring people to care about people living with HIV. But they were not well grounded in the messy realities of inequality. From the outset of the Fast-Track approach, civil society and community activists pointed out these ignoble truths, raising concerns about the neglect of key populations in middle-income countries in Eastern Europe and Central Asia, Latin America and the Caribbean, the Middle East and North Africa, and Asia and the Pacific. 3

Although India and China both have large numbers of people living with HIV, neither is depicted with proportionate size and shading on the map.

20

ADVOCACY AND THE MIDDLE-INCOME COUNTRIES

CIVIL SOCIETY ADVOCACY AND THE MIDDLE-INCOME COUNTRIES

As noted earlier, in the 1980s and 1990s, people living with HIV mobilized internationally to demand treatment and services, and as they were successful and the global response grew, some rose to senior positions in the newly established institutions. ACT-Up, a grassroots network of AIDS activists, was the first of these groups to emerge in the United States, France, and in other countries. Their advocacy explicitly rejected the stigma and AIDS denialism in the public sphere, especially with the now-iconic sign with a pink triangle that read “SILENCE = DEATH.” Activists occupied public spaces, demanding faster action and more funding and research. They also mastered technicalities of medical research and approval, claiming seats in scientific bodies (Chan 2015; Epstein 1988). People living with HIV built up outspoken national networks, including in Sub-Saharan Africa. In the 2000s key populations also began to mobilize transnational networks of gay men and other men who have sex with men, transgender people, sex workers, and people who use drugs. Global advocates representing these constituencies fought for and successfully won seats in the governance of some national coordination mechanisms and global HIV institutions. UNAIDS codified this principle as a normative standard, “the Greater Involvement of People living with HIV” (GIPA): the right of people living with HIV “to self-determination and participation in decision-making processes that affect their lives” (UNAIDS 2007, 1). The principle was incorporated into the International Guidelines on HIV and Human Rights (UN Office of the High Commissioner for Human Rights and UNAIDS 2006, para. 5). The Global Fund also urged countries, with mixed success, to include roles for these constituencies in national multistakeholder committees managing Global Fund finances. Here, it is important to note the distinction that some global HIV governance agencies make between communities and civil societies: community representatives are those who are directly affected by HIV, either because they are living with HIV or are key populations at risk of HIV. Civil society representatives speak for civil society organizations, which can include NGOs, hospitals, or academic institutions, but they are not necessarily representatives of communities. 21

CONTESTED INDICATORS

As the global HIV response has rapidly scaled up, civil society and community representatives have become both insiders and outsiders: consulting on national HIV strategic plans, proposing and approving funding plans, monitoring progress, implementing national and regional programs, and sometimes all of the above. As Biehl noted at an earlier stage of the epidemic, scale-up has produced “unlikely coalitions that both expose the inadequacies of reigning public health paradigms and act to reform, if to a limited extent, global values and mechanisms (of drug pricing and of types of medical and philanthropic interventions, for example)” (2007, 1083). The scale-up of the global HIV response can also reconfigure local prestige and power relationships in problematic ways, creating conflicts of interest and misuses of power that have been explored in academic literature (Kapilashrami and O’Brien 2012; Nguyen 2010; Qureshi 2018). However, the role activists play in global health governance has been less studied. Advocates like those quoted throughout this book now occupy seats in the highest levels of governance. Seated alongside health ministers, ambassadors, and other senior managers, they also contribute to debates about priorities, implementation and accountability. Their public support for global HIV finance programs gives those programs legitimacy, and if they withdrew that support, donors would probably question continuing support. When new bilateral donor commitments are made to finance the global HIV response, these announcements are preceded by more than a year of strategizing and advocacy by international networks such as the Global Fund Advocates Network (GFAN). Many activists have raised increasingly urgent concerns about the impact of donor withdrawal from middle-income countries. When HIV donors transitioned out of middle-income countries in order to focus more of their funding in high-prevalence countries in Africa, the governments of middle-income countries rarely stepped in to fill the gap. In fact, at the same high-level meeting where UN member states voted support for the Fast-Track approach, some blocked key populations-led groups from participating (Holpuch 2016). As Rico Gustav, executive director of the Global Network of People Living with HIV and a delegate on the Global Fund Board, has said, “Everyone talks about leaving no one behind, but key populations were never there in the first 22

ADVOCACY AND THE MIDDLE-INCOME COUNTRIES

place” (Davis and Villafranca 2019). Speaking at the UN, Gustav called on states to “place the needs of the poorest and most marginalized members of society at the start and center, and put the last mile first” (GNP+ 2019). Meanwhile, some have also noted that scale-up in Africa, while resulting in significant progress in declining death rates, has triggered other concerns about failure by some states to procure goods, hire staff, and launch new programs to spend their larger allocations. In 2017 more than $1 billion of Global Fund financing was unspent due to poor cash absorption (Green 2017). The cost of transition from middle-income countries is becoming clear. In 2019 UNAIDS reported that while rates of HIV were declining globally, more than half of new infections were among key populations and their partners (UNAIDS 2019a, 11). As Mike Podmore, executive director of UK civil society network STOPAIDS and a Global Fund Board Member, put it in our interview in May 2019: “Some donors are willing to sacrifice progress in middle-income countries on the basis of focusing on high-burden, low-income countries, because of the feeling that upper-middle-income countries should be stepping up and doing it themselves. The challenge for us is that it’s not morally acceptable just to leave key populations and other people living with HIV to their fate.” All sides of this debate over how best to allocate limited resources have made compelling, rights-based arguments. As Peter Sands, the executive director of the Global Fund, reflected when we spoke by phone in July 2019: “You’ve got to be very thoughtful, because of course, you’re not just thinking about the static cost of any one life saved; you’re thinking about the broader implications for the epidemiology in this situation.” Sands had only recently joined the Global Fund. I asked him how these difficult decisions in global health contrasted with the kinds of decisions he had had to make in his previous role, as chief executive of Standard Chartered bank. He said, “It’s easier in the business world, when you’re thinking about the return on investment of doing X or Y, than it is in the global health world; because the return on investment [in global health] is essentially lives.” Using “lives saved” to measure the results of the Fund’s investments came back to the fundamental premise of the Fast-Track approach: focus investments where they can have the maximum impact by increasing enrollment on treatment. The rationale behind the Fast 23

CONTESTED INDICATORS

Track approach never explicitly told donors to withdraw money from middle-income countries to invest in countries with high HIV prevalence, but as the funding shrank, many did so in order to achieve the scenarios predicted by the Fast-Track approach and to try to reach epidemic control as predicted by the mathematical models. As the debate over middle-income countries highlights, the FastTrack approach, while it seemed clear and logical, left some critical questions about prioritization and politics unresolved from the outset. The 90-90-90 targets were intended to focus efforts and resources on scaling up treatment, especially in high-burden countries. But while this goal was laudable and logical, it did not address the risk that stigmatized and criminalized key populations in other countries would be left behind. 90-90-90 was a clear and easy-to-remember set of targets, and the Eligibility Policy was written to make determining eligibility for HIV financing clear and straightforward, but both these examples also highlights the ways in which indicators and targets can be slippery and contested, especially when resources become tight. The next section touches on a broader literature about this problem of indicators used in global governance, before examining a few illustrative examples of contested indicators at the Global Fund, and showing how these have changed over time. THE POLITICS OF INDICATORS

A growing literature on the use of indicators by anthropologists and human rights scholars has highlighted concerns about the use of indicators in global governance. Critics have shown how indicators can take on the status of law in their operations, reinforcing unequal postcolonial power relationships between global governance agencies and developing countries (Davis and Kruse 2007; Escobar 1995; Merry 2011; Merry et al. 2015; Satterthwaite & Rosga 2008). Indicators are abstractions that reduce complexity of phenomena to make them visible and commensurable across diverse contexts (Bartl et al. 2019; Merry and Wood 2015; Winkler et. al. 2014). To do this, indicators aggregate data in ways that are often distortive and create oversimplified rank-ordering of complex phenomena (Davis et al. 2012, 73–75). The growing demand for indicators and data represents a rapid expansion of mechanisms of transparency and measurement (Riles 2013). Adams (2005) argued that global health indicators like 24

THE POLITICS OF INDICATORS

these imposed external norms that were ill-suited to local specificities and discouraged local programs from pragmatically tailoring their approaches. While I share these concerns, it is also important to remember how new indicators are in global governance, and to note that as a result, they are fluid, shifting in response to political and economic pressures. One example of this is global measurement of gender-based violence. For many years, this problem has been denied and ignored, minimized, and deprioritized. Women’s rights advocates were unable to get an indicator on this issue into the Millennium Development Goals, in part because critics said it was too hard to measure (Anderson 2013; Ellsberg 2006). When UN member states approved the SDGs in 2016, they did at long last include indicator SDG 5.2: “Eliminate all forms of violence against all women and girls in the public and private spheres, including trafficking and sexual and other types of exploitation” (UN General Assembly 2015). This was a triumph for survivors and others who had fought to make this stigmatized and minimized violence visible. But the problems of reporting on this indicator and of understanding the data reported are complex. First, as will be discussed in more detail in Chapter 7, few survivors report sexual and other forms of gender-based violence, due in part to the risks of exposure and their lack of trust in reporting mechanisms. Thus, as we will see, reported numbers on violence against women generally represent only the tip of the iceberg (Merry 2016). Second, the focus on violence against women can render other forms of gender-based violence invisible: there is no SDG for violence against men, for example, though men have been targeted with sexual violence in conflicts as diverse as those in Uganda and Syria (Dolan 2014; Chynoweth 2017). There is also no indicator capturing violence against transgender or nonbinary people, who are also frequently victims. The invisibility of male and trans survivors discursively constructs females as a priority in the indicator, but in ways that can reinforce denialism, invisibility, and lack of services for victims of other genders. Then there is the problem of how to understand a change in the data reported on violence against women (Davis, Schopper, and Epps 2018; Merry 2016). Does an increase in reported incidences of violence mean that there are more actual incidences of violence, or does it indicate that progress is being made because greater numbers of women feel safe to report? On the other hand, how should a decrease in reported cases be understood: does it mean that efforts to reduce violence are working, or that they are failing, because fewer women feel safe to report? 25

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This is not to say that violence against women should not be tracked with a global indicator, but this example is given in order to emphasize the importance of context in shaping the meaning of a sign, like an indicator, and to note that every time an indicator shines a light on an issue, it casts a shadow on other areas that are not prioritized, raising new questions. For example, at the height of the #MeToo movement of 2017, as the hashtag convened an international debate about sexual harassment and sexual violence on social media, attention to the problem of bullying and sexual harassment in international organizations increased, highlighted by some visible scandals, including one at UNAIDS (2018d). In March 2018, the United Nations tweeted a link to a report showing that “special measures to end sexual exploitation & abuse show progress,” with a drop in the number of allegations from 165 to 148 (UN 2018). The responses to this on Twitter included one from a women’s rights campaigner: “Unfortunately, all this shows is a drop in reporting, not a drop in incidents – they know this and this is a PR stunt” (Spencer 2018). As this example of indicators on sexual and gender-based violence shows, indicators and data used to promote accountability can simultaneously reveal some hidden truths, hide other truths, and raise a flag for a space in which there are intensified contests over power. To further illustrate the emergent nature of indicators, this time in HIV finance, the following section shows how a few indicators used by the Global Fund changed between two strategy periods and the different work they did. It is important to underscore here that as the above example showed, the Global Fund is far from unique in contending with the problem of what to measure in monitoring its work. The Fund convenes many diverse forces and actors, making it in some respects a mirror reflecting the broader debates in the HIV sector. The section below looks at a few of the KPIs set by the Board, but not at indicators used by Secretariat managers to monitor progress internally or the indicators used to monitor performance of grants. Chapter 9 will briefly explore my attempts to design a KPI on human rights for the Global Fund when I worked there, and the challenges this created in monitoring compliance. To set priorities and monitor progress, the Global Fund selects indicators for priority areas. As Figure 1.5 illustrates, indicators name the priority area to be monitored: for example, “number of people living 26

THE GLOBAL FUND CORPORATE KPIS

1200

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Figure 1.5 Sample indicator, coverage of HIV testing among men who have sex with men

with HIV who have tested and know their status.” For each indicator, they set a target that they aim to achieve. The target is the specific goal within that indicator (e.g., 90 percent of people living with HIV). Data are the statistics and numbers used to report periodically on whether or not an agency’s work is on track to reach the target. For a coverage indicator, as touched on above, it is necessary to have a baseline estimate of the number of people to be reached. The work of setting indicators and targets and gathering data all presume a clear consensus exists on what should be monitored, what can be achieved, and how to measure progress. In many ways, though, this consensus is still a work in progress, as we can see in the following section, which explores a few examples of this in the Global Fund Corporate Key Performance Indicators (KPIs). THE GLOBAL FUND CORPORATE KEY PERFORMANCE INDICATORS

Beginning in 2014, to monitor its performance, the Global Fund put in place a set of corporate KPIs tied to the 2012–16 corporate strategy (The Global Fund 2011). A second set of KPIs were approved for the next 2017–22 strategy (The Global Fund 2016a, 2016b). However, 27

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setting targets and measuring progress required negotiation among diverse actors on the Global Fund Board, as well as advocacy with countries implementing funding. To understand why, it may be helpful to briefly summarize the unique operating model of the Global Fund. The Global Fund is a partnership made up of numerous agencies, committed to the principle of “country ownership.” Thus the Fund cannot dictate to countries what they should do with their funding. A Country Coordinating Mechanisms (CCM), which ideally should be made up of government, civil society, medical experts, and representatives of people living with or affected by HIV, TB, and malaria, manage the funding in the country. The CCM develops funding requests, select implementing organizations, and monitor progress. Technical partners, such as UN agencies, provide technical support that aims to steer funding requests toward compliance with standards and guidelines developed in Geneva. Funds are disbursed in tranches, with each tranche released only when programs report meeting targets. The Global Fund Secretariat manages this work from its headquarters in Geneva, and all its approximately 800 staff now work in the Global Health Campus, near WHO: there are no country offices. The funding requests from CCMs are reviewed by the Global Fund Secretariat and by an independent panel of experts. Requests may be sent back to the country, with recommended changes. Once the funding request is approved, the CCMs select principal recipients, often the Ministry of Health, to manage the funding. The principal recipients select sub-recipients and sub-sub-recipients to manage specific interventions. As the Fund does not have national offices, it engages Local Fund Agents, usually local accounting firms, to monitor activities and expenditures. The indicators countries are encouraged to use in their funding are set by the Board, which is so large that a colleague once compared it to a parliament. Its twenty voting members each represent larger delegations, divided equally among donors and implementers. In the donor group, the makeup of each constituency is determined by size of contribution to the Global Fund. The United States, United Kingdom, France, Germany, and Japan, as the five largest donors, each represent one seat and one vote. Smaller bilateral donors are grouped in shared seats. Two other constituencies represent the private sector and private foundations; the private foundations delegation is dominated by the Gates Foundation, which makes the largest contribution of any private 28

THE GLOBAL FUND CORPORATE KPIS

foundation. In 2018 the Board approved a new nonvoting seat for public donors that have each pledged at least $10 million – currently, South Korea and Qatar. The ten implementers who make up the implementers’ group includes seven representatives from developing countries (one from each of five World Health Organization geographic regions, two representatives from Africa). It also includes three representatives of delegations of civil society and affected communities. The Fund is one of the few international agencies to include civil society and community representatives in governance, and the only one that gives them three votes. There are eight ex-officio nonvoting members, including UN agencies that provide technical advice on the three diseases. Thus, while indicators set by the Global Fund are important, the process of agreeing on those indicators involves diplomatic negotiation among all these diverse actors, importantly including its bilateral donors, which each have their own foreign policy and health agendas. When I interviewed Peter Sands, he was in the midst of the Global Fund’s sixth replenishment campaign. Each Global Fund donor, he said, was asking him for different kinds of data in order to make the case for funding: “We have donors that are interested in particular parts of the world; we have donors that are interested in what we’re doing with a gender focus. There are donors interested in the progress about key populations. . . . There’ll be people who ask questions on what we’re doing about specific types of intervention.” The debates on the Board over what to measure and how to measure it have often slowed the development of the Global Fund’s KPIs. For the first strategy, from 2012 to 2016, because the Global Fund Secretariat was preoccupied with a major internal restructuring, work on the KPIs only began in early 2013, a year after the strategy had begun. The Board did not approve the KPIs until the end of that year (The Global Fund 2013). The targets and methodologies for each KPI sparked further debate, because all were new, and they were approved the next year (The Global Fund 2014). Thus the first report on performance from the Secretariat to the Board could only come one year after that, in November 2015. At that point, the strategy period was almost over. While the Secretariat reported on a few of the KPIs in 2017, they never delivered an end-of-strategy overview of performance. Instead, the Secretariat 29

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appears to have quietly discarded the first set of KPIs, and smoothly segued into a new, improved set of KPIs for the 2017–22 strategy (The Global Fund 2017a). Development of this second set of KPIs went more smoothly at first. However, as discussed below, debates over the targets slowed approval again. The next section explores three types of Global Fund KPIs in order to illustrate the shifting nature of the goalposts, as well as the different kinds of roles indicators can play: as signs in external communication, as levers to direct funding to a certain area, or in some cases, both at the same time. 1. Lives saved – As Sands said, “lives saved” is the main return on investment, making it an important indicator for the Global Fund. In 2019 a month before the sixth replenishment (or donor pledging) conference was due to take place in France, the landing page of the Global Fund website announced that its partnership had saved thirtytwo million lives (The Global Fund 2019). Similarly, at the fifth replenishment conference in Canada in 2016, Prime Minister Justin Trudeau spoke in front of a screen projecting the words “8 million lives will be saved/8 million des vies seront sauvées,” and held a public conversation with Loyce Maturu, a young Zimbabweam TB survivor who is living with HIV and who relies on programs financed by the Global Fund for her treatment (Canada 2016). “Lives saved” is primarily a sign, an external communications tool for donors like the Global Fund. (Similarly, in 2018, PEPFAR also reported that it had saved more than seventeen million lives [PEPFAR 2018].) It is a compelling phrase, especially when explicitly linked with the physical bodies of Global Fund beneficiaries, like Maturu. Maturu contracted HIV at birth, not through sexual activity or drug use; images of her used in campaigns by the Global Fund Advocates Network show her engaged in virtuous activities such as studying for a degree, educating peers about HIV, playing with neighborhood children, and cooking dinner (GFAN 2016). Maturu is an outspoken activist, but she is not shown protesting. And though the Global Fund has also saved the lives of key populations through its prevention work, Prime Minister Trudeau might have been more ambivalent about sharing the stage with a male sex worker grateful to the Fund for giving him free condoms. One important part of the work this indicator does is emotive, encouraging public faith in the investment. 30

THE GLOBAL FUND CORPORATE KPIS

Reporting returns on investment in “lives saved” also usefully suggests some quantifiable, fiscalized value. However, this is not the case, “lives saved” is not in practice an indicator used to manage programs, because it is too vague. In fact, the Global Fund’s method of calculating “lives saved” has been the subject of academic debate. Friebel and colleagues (2019) have argued that its fails to pinpoint the Global Fund’s specific contribution. The Fund responded by emphasizing that the metric had been arrived at through consultation with experts and UN agencies (The Global Fund 2018b). Both the Global Fund and PEPFAR continue to use “lives saved” largely for external communications. Alongside the living example of virtuous and nonthreatening spokespeople whose lives depend on treatment, the number is a powerful synecdoche that abstracts the Fund’s complex work and turns it into a powerful storytelling device grounded in the “white savior industrial complex,” in which “Africa serves as a backdrop for white fantasies of conquest and heroism” (Cole 2012). But “lives saved” also vaguely evokes neoliberal values of fiscal probity. Donors and members of the public inspired by the idea of their taxes helping rescue a virtuous African might also be reassured by the vague aura of cost-effectiveness. 2. Service coverage – While the “lives saved” indicator is primarily a sign for communications to the public, the Global Fund service coverage KPIs are used to assess progress toward its core goals: whether services funded are being used in sufficient numbers. However, these have been a series of shifting goalposts, and reaching service coverage targets has been sometimes difficult. In the first set of KPIs for the 2012–16 strategy, the Global Fund set a target of an overall number of those tested across all countries. The Fund met this target within the strategy period, which was good news. However, because the indicator only assessed the global number of people tested, it could not assess what percentage of those estimated to be living with HIV were being tested in any given country, and thus whether or not high-prevalence countries were progressing toward 90-90-90. After the Fast-Track approach was approved by the General Assembly, the Fund revised its service coverage KPIs to align with the Fast-Track targets: for example, the HIV testing indicator became a coverage indicator, with a target of 90 percent.

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However, when this and other KPI targets were brought to the Board for a vote, they were not approved. Implementing country and civil society delegations on the Board raised concerns that the ambitious coverage targets were unrealistic: they were derived from estimates and in some cases estimates produced by mathematical models (Garmaise 2017 summarizes the letter implementers wrote about these concerns; as a consultant, I contributed to drafting the letter, but not to Garmaise’s article). Failure to reach the ambitious coverage targets could mean that programs might later be assessed by the Global Fund as failing. To address these concerns, the Board set up a working group of experts appointed by both donors and implementers to review the evidence and modeling behind the proposed KPI targets (ibid.). Based on their recommendations, the Board did eventually approve a revised HIV testing coverage target focused more narrowly on just a subset of thirty-three priority countries (Global Fund 2017b). As Table 1.1 shows, progress in this group of countries has been slow but steady. However, the downside of this approach was that it left dozens of countries out of an important corporate KPI. Another HIV service coverage indicator focused on treatment access (the second 90 of 90-90-90). This indicator showed slow but steady progress. For a third HIV service coverage indicator on treatment adherence, progress was uneven. Reporting stalled then dropped below the starting baseline, as UN agencies revised their methodology for calculating results. In the 2017–22 KPIs, this indicator was focused again more narrowly just on thirty-three priority countries and progress became steadier. Civil society groups and others on the Board urged the Global Fund to set a KPI measuring service coverage for key populations. This proved challenging to do, this time due to lack of data. For countries to be able to report coverage of these interventions, they needed a baseline estimate of the size of the populations to be reached: “key population size estimates” of the number of sex workers, men who have sex with men, transgender people, and people who inject drugs for each country. UNAIDS and WHO recommend that countries conduct these estimates for use in planning and evaluating services (UNAIDS/WHO Working Group on Global HIV/AIDS and STI Surveillance 2010, 4–6). The political and methodological challenges this raises are explored in later chapters.

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THE GLOBAL FUND CORPORATE KPIS

Suffice it to say that many countries lacked these size estimates at that time – and still do today. Of 140 countries assessed by UNAIDS and Global Fund researchers, 41 countries had not reported any key population size estimates since 2010; many of these estimates were assessed as inadequate (Sabin et al. 2016). For some populations, the gaps are worse than others. For example, transgender women face extremely high risk of HIV, but according to UNAIDS’ online database, most countries have reported no size estimates for transgender women (UNAIDS 2019c). There is “almost no data available on HIV prevalence and risk among transgender people” in Africa, in particular (Jobson et al. 2012, 160). Getting this data was a critical first step. The first set of KPIs from 2012 to 2016 focused on leveraging the Global Fund’s power to get a targeted fifty-five countries to produce key population size estimates. Progress was steady on this indicator, driven in part by a motivated Global Fund manager, Jinkou “Button” Zhao, who worked with UNAIDS to draw up a list of fifty-five countries and visited often, pushing the size estimation studies along. By 2016, all fifty-five countries had size estimates. This meant that in the next set of KPIs, the Board could progress to what they had wanted in the first place, setting a coverage indicator and asking countries to report on percentage of key populations to access services. However, of the fifty-five countries that now had new size estimates, few had ever reported data on service coverage. The key populations indicator was revised again by the Global Fund to just measure how many countries could even report coverage. But in the meantime, a new problem had developed: some of the fifty-five countries were now upper-middle-income, and were no longer eligible for the Global Fund. These service coverage indicator examples demonstrate just a few of the challenges involved in setting and measuring the Global Fund’s progress on core areas of its business. Unlike “lives saved,” these indicators are levers that the Fund, UN agencies, and others use to nudge countries to prioritize key areas of the Fund’s strategy. However, as Table 1.1 shows, the shifting goalposts and changing methodologies makes it difficult to assess progress. Asked if the indicators like these are useful in her role as a Global Fund Board Member heading the US delegation, 33

TABLE 1.1 Selected Global Fund KPIs for HIV service coverage, 2014–16 and 2017–22

[1] [2] [3] [4] [5] [6]

Source: The Global Fund 2013, GF/B30/7, pages 8–9. Source: The Global Fund 2016b, GF/B35/07a – Revision1, pages 16 and 21. Indicator to be tracked on a specified set of countries selected in collaboration with technical partners. A “portfolio segment” of countries were selected from the 55 with key population size estimates by the end of 2016. The Global Fund 2014, GF/B32/24.a, pages 4–8. The Global Fund 2015, GF/B33/04B, pages 6–8.

[7] The Global Fund 2016c, GF/B35/22, pages 12–14. [8] The Global Fund 2017a, GF/B38/24, page 13. [9] “Some historical estimates are slightly different from the previously reported data due to technical partner revision of entire time series using most up-to-date data” (ibid.). [10] The Global Fund 2017b, GF/B36/ER08A, page 9. [11] The thirty-three countries are Angola, Bangladesh, Botswana, Cambodia, Cameroon, Chad, Cote d’Ivoire, DR Congo, Ethiopia, Ghana, India, Indonesia, Kenya, Lesotho, Malawi, Mozambique, Myanmar, Namibia, Nigeria, Pakistan, Philippines, Rwanda, South Africa, South Sudan, Sudan, Swaziland, Thailand, Uganda, Ukraine, UR Tanzania, Viet Nam, Zambia, Zimbabwe. [12] The twenty-six countries are Angola, Botswana, Cameroon, Chad, Côte d’Ivoire, DR Congo, Ethiopia, Ghana, India, Kenya, Lesotho, Malawi, Mozambique, Namibia, Nigeria, South Africa, Swaziland, Tanzania, Uganda, Zambia, Zimbabwe, Guinea, Indonesia, Mali, Rwanda, South Sudan. [14] The Global Fund 2018c, GF/B40/14, pages 40–45.

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Ambassador Birx, the head of PEPFAR, said that PEPFAR finds “that averaging, percentages and non-disaggregated data lead to your assumption that you are doing well everywhere, and we know that is not true. There are sites that are really struggling; there are sites that are doing extraordinarily well. We call this the tyranny of averages: you lose the good and you can’t find the not-so-good.” Sands responded that managing specific sites was not the purpose of the KPIs. The Fund uses other indicators for this, he said: “The KPIs aren’t designed to give country-level information. . . . They’re meant to be high-level global indicators of progress: Broadly speaking, is [the Fund] making progress against the key parts of the overall global strategy?” 3. Health Systems Strengthening – If “lives saved” is a sign and “service coverage” indicators are levers, then the Health Systems Strengthening KPI does both kinds of work: telling stories that are compelling to key stakeholders whose support is needed by the Global Fund and leveraging funding to a priority area. However, of the KPIs discussed here, it has been one of the most challenging to measure. Many Board constituencies and donors have publicly urged the Global Fund to focus more on strengthening health systems. As global health agencies begin to address the problem of Universal Health Coverage (UHC), some scholars have argued that global health financing should shift away decisively from specific diseases and toward investing more broadly in strengthening health systems (Benton 2015; Kenworthy 2017). Sands has argued that the Fund’s investments already do contribute to strengthening health systems (Davis and Villafranca 2019). Including a KPI on health systems strengthening was both a way to satisfy critics by showing that the Fund also saw health systems strengthening as important, and a way to encourage grant recipients to finance this work. But while many institutions and experts clearly agree about the importance of health systems strengthening, they do not agree how it should be done or measured (Storeng 2019). Warren and colleagues, including Global Fund staff (2013), found in their review that significant Global Fund funds were being allocated to health systems strengthening interventions, but also found a lack of consensus about the mix was making it difficult to assess progress. Fan and colleagues (2017) reviewed Fund investments in health systems strengthening and found that even those emphasizing stronger 36

PROGRESS, GOALPOSTS, OR A TYRANNY OF AVERAGES?

workforces in their budgets were not correlated with higher density of health workforces. The difficulties in agreeing what to measure are reflected in the relevant KPIs. For the first set of KPIs in 2012–16, the Board approved a Health Systems Strengthening KPI that was based on a Service Availability and Readiness Assessment (SARA) index, with the assessment conducted by WHO. The SARA index uses visits, interviews, and other data to measure a range of areas, including trained staff, medicines, commodities, and more. The target for the first Health Systems Strengthening KPI was an improvement of 5 percent or more in the SARA score of 60 percent of countries surveyed (The Global Fund 2014, 9). However, the reports were not forthcoming from WHO. By April 2016, with the end of the strategy period in sight, there was just one SARA assessment, for Uganda. Uganda showed only a minor improvement to its SARA score; other countries, whose reports were not finalized, had sub-par scores (The Global Fund 2016c, 19). For the next strategy period, the relevant team at the Secretariat took the reins in their own hands. They developed a KPI now renamed “Resilient and Sustainable Systems for Health,” grounded in a new approach driven in-house. This work included creating a dashboard, defining a package of interventions, conducting baseline studies, and using data reported directly to the Global Fund (The Global Fund 2016b, 22; Boulanger 2019). By 2019, while there had been measurable progress, one key indicator, on procurement systems, still lacked a defined methodology (The Global Fund Office of the Inspector General 2019, 13). STEADY PROGRESS, SHIFTING GOALPOSTS, OR A TYRANNY OF AVERAGES?

It might not be a surprise that donor priorities for funding in a context of limited resources are contested and debated, as described in the beginning of this chapter in reference to which countries should be prioritized. It may be more surprising, though, that some areas at the heart of the Fund’s investments are also difficult to measure at a global level. This is due to competing priorities and frameworks, evolving methodologies, gaps in data, and the complex work the indicators do as both communicative signs for specific audiences, and as levers of power and funds. 37

CONTESTED INDICATORS

Two independent audits of the KPIs by the Global Fund’s Office of the Inspector General (an independent function that reports to the Board) show some progress between the first set of indicators for the 2012–16 strategy, and the second set used for 2017–22. They concluded that even though there were numerous weaknesses, many had been or were being addressed, and suggested some improvements to their design and use (Global Fund OIG 2016 and 2019). But for some Board Members, the KPIs still require revision, according to Rico Gustav: If you look at the KPIs, some of the flow doesn’t make sense, to be honest. That’s because [they are] a result of a compromise [among] different donors, to actually put some of those KPIs in so that they can report back to their countries. There must be a better way to accommodate different needs, and create something that actually makes sense.

Sands saw the KPIs as a work in progress: You can always argue about whether we’ve got precisely the right set [of KPIs]. As we go into the next strategy exercise, we’ll look at them again and say, do we need different KPIs to reflect the nature of the strategic challenges? It’s always a little bit of a trade-off between the things you care about, and the things you can actually measure.

KPIs, in other words, will continue to evolve and change. WHY INDICATORS?

If indicators are so fluid, then why use them at all? Because indicators used in global HIV finance offer openings for engagement to promote accountability. Critics argue that part of the problematic work done by indicators has to do with a false sense of transparency: the information behind them may be comprehensible to a small group of experts, while remaining incomprehensible to the public (Bradley 2015). Davis, Kingsbury, and Merry note that “the production of indicators is itself a political process, shaped by the power to categorize, count, analyze, and promote a system of knowledge that has effects beyond the producers” (2015, 2). This political process systematically excludes forms of knowledge that are not quantitative, a problem returned to as well in later chapters. 38

WHY INDICATORS?

Because of these and related concerns, some have begun to argue for various forms of resistance to indicators and quantitative data used in governance (Dalton and Thatcher 2014, 8). Drawing on the “slow food” movement, Adams, Burke, and Whitmarsh (2014) called for an alternative to quantitative methods in health governance: they urged “slow research,” or rich, locally grounded ethnography that could inform more nuanced approaches to health. The unstated implication of these arguments is that there is a unitary and objective reality that numbers oversimplify, but that other kinds of signs, such as qualitative research written with words, might capture better. Some of this book draws on ethnographic research, and I agree that the methodology should be used more often in global health governance, because it introduces nuance and analysis and grounded specificities that quantitative methods can miss. However, it is important to note with humility that ethnography is also a form of signification that has grown out of colonial histories of unequal power that shape subject-object relations (Lewis 1973). All communicative signs are abstractions, whether numerical or verbal. One methodology alone cannot capture the prismatic and complex contexts in which HIV flourishes, or work as a sophisticated decision-making or accountability tool. All forms of knowledge are partial and emergent. This may be reason for cautious optimism: signs like indicators are partial and emergent, but they can be engaged, critiqued, and changed. As Butler notes, a risk of constructivism is that it can be reduced to determinism, erasing agency (1993, xviii). But increasing the agency and engagement of marginalized voices has been one of the greatest achievements of the global HIV response. Country ownership is too often taken to mean government ownership; but because of commitments to transparency and community participation in governance, the HIV sector has sometimes opened up space for other, critical voices. Anthropologists and human rights scholars can support their critical engagement, by introducing questions grounded in alternative forms of epistemology beyond positivist measurement. To do so may require having difficult conversations as we reach across the divides of our disciplines and question what we think we know. While some critics argue for slow research, Sands feels that data production needs to speed up. At Standard Chartered bank, he recalled receiving reports daily: “flash data,” which was understood 39

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to be only 80–90 percent accurate, but which could give him a view on one day of the global performance of key businesses the day before. In global health, he said, he must rely on annual UN reports that may lag months behind the rapid pace of new infections, slowing his ability to respond to emergencies. “It’s very difficult to move much faster than the cycle time of the information you get,” he said. “You’re kind of flying blind.” Just moving to quarterly updates, he said, would make an enormous difference; it would “start making people think a bit differently about program design and . . . the cycle time in which you reprioritize and plan things. I think we need that sense of urgency.” ABOUT THIS BOOK

This book is written for two audiences: scholars and practitioners. As an engaged anthropologist myself, I hope it will enable crossdisciplinary conversations, and so it is written in an attempt to walk a thin line between academically credible research and pragmatic concerns of interest to civil society activists and global health officials. Some of the book is informed by my professional experience: first as a folklorist, then a researcher at Human Rights Watch; then founder of Asia Catalyst, an NGO working with community-led health rights groups in China and Southeast Asia; then as senior advisor on human rights at the Global Fund; and lastly as an independent consultant based in Geneva, Switzerland, working on strategy and policy in global health governance. It is written as a series of encounters with quantitative tools and policies used to make decisions in global HIV finance: population size estimates, biometrics, cost-effectiveness software, investment cases, infectious disease models, randomized controlled trials, indicators, and compliance mechanisms; examining each through the critical lens of anthropology and human rights. Woven throughout these dives into the technocratic tools of global health governance are a series of vignettes from an ethnographic study in the Caribbean. This aims to introduce real people whose lives are affected by data-driven global health decisions and show how they worked together to gather data on key populations that empowered them to make their own decisions. The methodologies used are briefly summarized below. 40

METHODOLOGIES

METHODOLOGIES

During 2016–19, I worked with an NGO, Caribbean Vulnerable Communities, to conduct five ethnographic field research trips to the Eastern Caribbean of periods ranging from one to six weeks. My research was a study of a key population size estimation study in six countries, particularly in Grenada, and it aimed to document the challenges faced by the researchers, their engagement with civil society, the choices they made, and the social factors shaping scientific results (Latour and Woolgar 1986). During these visits, I participated in meetings as an observer and conducted semistructured interviews over three years with the same core group of a dozen participants. They included academic researchers, civil society managers and staff, indigenous field workers, government health officials, and consultants from Grenada, Saint Lucia, Dominica, and the Dominican Republic. I also spoke by phone with ten experts at US and international organizations with expertise in HIV in the region. Meanwhile, in Geneva, I also conducted semi-structured interviews with thirtyfour technical experts, managers, and staff of international organizations and civil society organizations in the context of their professional work. With each person interviewed, I discussed the purpose of the book and potential risks, which included the possibility of their disclosing negative perceptions that could cause reputational harm to the interview or others, leading to their experiencing difficulties in working with larger agencies or with their own governments. I obtained verbal informed consent. Each person quoted in the book was invited to review their quotes, to withdraw them, or to propose revisions. Most did not make changes to what they had said, or made only small grammatical changes that did not affect the substance. In a few cases, individuals requested anonymity or to use their first names or initials, either because they were not authorized to speak for their institutions or because they were concerned about being identified as members of stigmatized key populations groups. A handful of people asked to speak on background. In the course of my work as a global health consultant, my thinking about data in global health governance was shaped by my participation in civil society meetings, Global Fund Board meetings, and as an observer at two UNAIDS Programme 41

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Coordinating Board meetings. I did not write explicitly about these meetings, as my participation in most of these were protected by confidentiality agreements with my clients. In Chapters 2 and 6, which drew extensively on materials originally produced for clients or colleagues, I obtained permission based on their review of the chapters. This included my work for the three civil society delegations on the Global Fund Board on the Eligibility Policy, discussed in a later chapter, and on a report I coauthored with the Kenya Legal and Ethical Issues Network on HIV and AIDS (KELIN) and the Kenya Key Populations Consortium, discussed in the next chapter. I also read widely in academic and grey literature, as well as global health policies, published board meeting reports, and data published by UNAIDS, WHO, UN Office of Drug Control (UNODC), UN Development Programme (UNDP), PEPFAR, and the Global Fund on their websites. This research was approved by the Institutional Review Board at St. George’s University, Grenada. It was largely funded from my personal savings earned while teaching and working as a consultant. CVC contributed per diems and provided shared housing on three of my field trips. A prize from the Swiss Network for International Studies in 2017 covered the cost of another trip. Beyond this I received no other financial support. As I came across findings that I thought they could use, I briefed civil society activists and UN technical advisors. Sometimes this meant the conditions I was writing about changed. Where I am aware of these changes, they are noted. There are limitations to these approaches. One important limitation is the focus on HIV, without addressing similar issues in tuberculosis or malaria, or doing justice to the complex problems raised by the needs of some groups not discussed in the book, such as prisoners, indigenous peoples, or persons with disabilities, for example. In addition, while the status of a professional offers some insights, it also sometimes makes it difficult to criticize colleagues and former clients. My discussion of the role of civil society engagement in global health governance reflects this, as it does not delve into the real weaknesses and abuses in some organizations, a topic addressed in some other studies. I have tried to be fair but will fall short of praising

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METHODOLOGIES

global health institutions as much as their champions would like, or being as tough as their critics would be. * The chapters that follow telescope in and out between the “country” and “global levels,” which is often the working practice of global health. As Tsing (2004) points out, there is no such thing as a view from nowhere. In Geneva, headquarters to several global health agencies, officials often speak of the “global level” as an imaginary shared space where they work, and the “country level” as a common set of developing countries. They draft policies at “global level” and pilot them at “country level,” taking away “lessons learned” to revise or discard the policies. The first warning sign for a policy that will have a short life in global health is when officials began to warn one another in Geneva that “it will be confusing to countries,” as if they were not in a country, or were not confused. While not strictly a field site, Geneva emerged as a venue for unexpected overlaps and arms-length reflection. Independent scholars writing on the fringes of the academy sometimes develop a resemblance to Ahab. I chased data and its critics across oceans and airports, through libraries, cafeterias, WhatsApp groups, and UN corridors. Indicators and data turned into slippery prey, chased across oceans: sometimes looking like a mathematical leviathan, other times a flickering school of tropical fish that slipped away when grasped. This translucent and evanescent quality of data under scrutiny, the slipperiness of indicators, contrasted with the rhetorical solidity they assumed on a slide deck used by someone to make a fact-based case. Data that looks like a Great Wall from afar can sometimes crumble like sand when scrutinized up close. Looking at it as an anthropologist and human rights practitioner, it often appeared that key parts of the context had been left out to construct a solid fact. But some indicators and data truly are better than others, and as they were all created by humans, they all can be deconstructed and remade in other forms. Ferguson (1995) showed that development aid can be an “anti-politics machine” that attempts to turn political problems into technical ones, while quietly expanding state bureaucracy. The tools discussed in this book are perhaps some of the small engines driving antipolitics machines, which can be disassembled and examined. 43

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As one example of this, the next chapter explores one of the most basic pieces of data needed to ensure “no one is left behind” in the race to HIV control: the key population size estimate. In the Venezuela case, as discussed in the beginning of the chapter, this was a crucial missing data point for eligibility, because due to homophobia and stigmatization of men who have sex with men, the data had not been gathered. This widespread problem is explored in the next chapter.

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C H A P T E R

2

T H E U N C OU NTE D: K E Y POPULA T I O N S

The offices of HIV community-based organizations are usually on the edge of town and can be hard to find.1 In Hong Kong, I roamed through the cavernous former airport terminal for an hour before walking behind a used car showroom to find a small sign: “Activity Center.” Behind it, the offices were full of HIV support groups and workshops. In Kingston, Jamaica, an unmarked HIV clinic was housed on a quiet residential street. In Yangon, Myanmar, dozens of sex workers, trans people, and gay men thronged a room lined with rugs, loudly debating the soap opera blaring on a tiny television set; the front door was unmarked. Why are these outreach workers still hiding, thirty years into the history of AIDS? These tiny offices are on the front lines of the global HIV response. The world needs these networks of outreach workers to go questing out into the streets – finding their peers, explaining how HIV is transmitted, sharing condoms and clean needles, and persuading peers to come in for an HIV test – and persuade those who test positive to start treatment: the crucial first step to reaching the 90-90-90 targets. Their offices ought to be easy to find. But the absence of signs is itself a sign of the suffocating stigma that thirty years on still surrounds HIV. For key populations and other people living with HIV, visibility is 1

This chapter is derived in part from an article published in the International Journal of Human Rights, August 16, 2017, copyright Taylor & Francis, available online: https://www .tandfonline.com/doi/full/10.1080/13642987.2017.1348707; and in part from “Everyone Said No”: Biometrics, HIV and Human Rights, a Kenya Case Study. Nairobi, Kenya: KELIN and the Key Populations Consortium, 2018. https://www.kelinkenya.org/everyonesaidno/.

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THE UNCOUNTED: KEY POPULATIONS

dangerous. Public exposure can lead to loss of jobs and homes; it can trigger extortion, arrest, attacks, even death. Organizations navigate their visibility carefully, and the missing signs and use of coded language are signs of absence. In many countries, having an office, even just meeting for dinner, brings risks. Sanjar Kurmanov, the director of Labrys, an LGBTIQA group in Kyrgyzstan, vividly described to me how Molotov cocktails drove the group out of their building while neighbors watched and did nothing (Davis 2016). A few weeks later, a small restaurant dinner in honor of International Day Against Homophobia and Transphobia was interrupted when a mob, calling themselves “The Forty Heroes,” swarmed over the walls. In Kurmanov’s telling, police showed sympathy with the mob, treating the victims as if they were the criminals. Still, Kurmanov said Labrys had found a new office and would reopen shortly, because demands for their services were only growing. All over the world, there are countless stories like these, in which community HIV organizations are hounded out of their offices, pick up the pieces, and start again somewhere new. These are the populations states pledged, in approving the SDGs, not to leave behind. But in the real world in which these commitments are funded and implemented, a politician who champions the rights of key populations risks becoming a target as well. Increasingly, donors are pressing countries to generate better data, demands reinforced from the country level by community activists. This chapter explores related tensions and difficulties in generating key population size estimates. It explores the data paradox, in which government denialism and criminalization reinforce invisibility, and shows that criminal laws may make it harder to estimate the actual size of key populations, creating mistaken impressions of success. Some countries have tried to fill the gap in data on key populations with biometrics (scans of irises or fingerprints). In Kenya, community resistance halted a government study that aimed to use biometrics to identify and count key populations, because of their concerns about criminalization. Lastly, the chapter explores how some key populations increasingly insist that they be treated as partners in data-gathering. DENIAL, CRIMINALIZATION, AND THE DATA PARADOX

If key populations are often in hiding, it is because in recent years, many government officials have engaged in open scapegoating of them, in 46

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a political context of growing populism. In 2018, Brazilian president-tobe Jair Bolsonaro called himself a “proud homophobe” (Phillips 2018). In 2016, in the wake of a contentious presidential election, Indonesian political cabinet ministers competed to outdo one another with public condemnations of homosexuality, “a feeding frenzy of anti-LGBT rhetoric,” during a year in which one out of four men who have sex with men were living with HIV (Kine 2017). Other leaders opt for flat denialism: “In Iran, we don’t have homosexuals,” Iranian President Mahmoud Ahmadinejad said to a US audience, even as Iran accepted international funding for HIV (Borger 2007). In Uganda, the acting minister for health asserted, “People know that homosexuality is not Ugandan or an African issue. It’s [a] few individuals here in Kampala who are practicing and trying to promote it” (IRIN 2014). In fact, most laws criminalizing same-sex sexual behavior were imposed by European colonizers and are promoted by some USbased pastors (Semugoma et al. 2012, 312). These and similar laws in other countries play a role in legitimizing homophobia, stigma, discrimination, and exclusion. As of 2019, seventy states criminalize same-sex sexual activity and a growing number prohibit “LGBT propaganda” (Mendos 2019). Six impose the death penalty, though international human rights law asserts it should be imposed only for the most serious crimes (General Assembly resolution 2200A [XXI]a, article 6). Transgender people are criminalized and prosecuted in fiftyseven countries (Transgender Europe 2019). Sex work is criminalized in 208 countries and dependencies (Global Network of Sex Work Projects [NSWP] 2019). Drug use and possession of drugs for personal use are criminalized in most countries (UNAIDS 2019b). As qualitative research has shown, key populations tend to avoid HIV studies and clinics in countries where these laws exist, because they fear being publicly exposed or reported to police (see, for example, Amon and Kasambala 2009; Booth et al. 2013; Csete and Cohen 2010; Elliott et al. 2005; Global Commission on HIV and the Law 2012 and 2018; Jurgens et al. 2010; Shannon et al. 2014; Schwartz et al. 2015). Avoiding health services and health surveys, remaining uncounted, are forms of self-preservation, as well as everyday forms of resistance to oppression (Scott 1985). This results in what Baral and Greenall (2013) call the “data paradox” for key populations: “Decision-makers deny that most affected populations exist . . . so no research gets done on these populations; the 47

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lack of data feeds the denial; and so on.” This is a vicious cycle of invisibility, in which absence of evidence is taken as evidence of absence, and the bodies whose existence is denied are driven into invisibility, illness, even death. While ACT-Up said in the 1980s that “silence equals death,” today it can be lack of data that kills. An ecological study I conducted with colleagues explored this paradox by showing how criminalization can be associated with implausibly low size estimates of key populations (Davis et al. 2017). It also showed how one result of low size estimates can be to mask a national failure to reach those populations. Our study drew on the database of country-reported data on HIV and key populations published online by UNAIDS for 2007–14, monitoring of laws by the International Gay, Lesbian, Bisexual and Transgender Association (ILGA), and UN statistics to estimate the proportion of the adult male population represented by the country-reported size estimates for men who have sex with men (Mendos 2019). Our resulting analysis, using chisquare tests, found that criminalization of same-sex sexuality was associated with implausibly low size estimates for men who have sex with men (less than 1 percent of the male population) reported by countries to UNAIDS. Size estimates were even more implausibly small in the countries that impose the death penalty for same-sex sexuality. These findings were not surprising, and were clearly consistent with the human rights research referenced above. But implausibly low population size estimates like these have a second damaging effect. As we conducted that analysis, it initially appeared as if a larger proportion of countries that criminalize same-sex sexuality had reported very high rates of HIV testing coverage among men who have sex with men. This flatly contradicted human rights research, not to mention common sense. It was also inconsistent with associations for the other indicators. We probed further, focusing on twelve countries reporting between 90 percent and 100 percent HIV testing coverage among men who have sex with men. These twelve countries were skewing the overall results with implausibly high testing coverage. Most, but not all, were middle-income countries with concentrated epidemics. Three countries had reported an astonishing 100 percent testing coverage among men who have sex with men: Hungary, Saint Lucia, and the Marshall Islands (Davis et al. 2017, 5). 48

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Why were countries that criminalized same-sex sexuality reporting such high testing coverage? Looking for answers, we reviewed the narrative reports countries had submitted to UNAIDS, and reached out to organizations representing men who have sex with men in those countries, or to regional organizations. The activists who wrote back were outraged to learn of the high testing reports. In Hungary, which had reported a frankly incredible 100 percent coverage of HIV testing among men who have sex with men, I contacted Tamás Dombos, a Board Member of Háttér, a Hungarian LGBTQI organization. Dombos replied, “I think the data provided is utter BS. Hungary is among the countries with the lowest levels of testing.” And indeed, reading the short report Hungary had submitted to UNAIDS revealed that the 100 percent reported HIV testing coverage was based on a three-month survey of 388 “homosexuals” (Hungary 2010, 4). Dombos said, “As far as I know the 388 survey was [based on] recruitment . . . at HIV testing centers, so it is a very distorted sample, and completely inappropriate to measure testing coverage.” He shared a survey published by Háttér in the same year, which found that 43 percent of the men surveyed had never been tested for HIV (ILGA Europe and Háttár 2010, 7). Similarly, activists in the Middle East, when asked about Algeria’s 2014 report of 96.6 percent HIV testing of men who have sex with men, also expressed skepticism. One noted that programs for men who have sex with men had been hit hard due to transitioning out of donors. And again, when we looked at the narrative report submitted to UNAIDS, it emerged that Algeria had only conducted one survey of fifty-nine men who have sex with men, fifty-seven of whom had been tested and received their results: result, 96.6 percent coverage (République Algérienne 2015, 38). In fact, eight of the twelve countries we looked into had no reported size estimate at all for men who have sex with men that they could use as a denominator for service coverage. In the Marshall Islands, the narrative report submitted to UNAIDS noted that there was no size estimate for either sex workers or men who have sex with men; the country had started a size estimate for sex workers, but had canceled this after “the study brought unwanted attention on the sex workers, with some subsequently being deported and others disappearing to avoid prosecution” (Republic of the Marshall Islands 2014, 32). 49

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As this bleak picture emerged, I wrote to John Waters, research director at Caribbean Vulnerable Communities (CVC), to ask about the reported high rates of HIV testing coverage for men who have sex with men in Antigua, Saint Kitts and Nevis, St. Lucia, and Suriname. Had these four Caribbean countries done anything special to reach men who have sex with men that might explain the high reported rates of HIV testing? He replied with an exasperated email which summed up the problem for all the countries I was now thinking of as “false 90s”: No, this is not plausible, and no, there have been no extraordinary efforts carried out in these specific countries to reach [men who have sex with men]. The mystery is really rather simple. It has to do with the denominator. Unfortunately the population size estimates are often way off . . . as you have seen, when the denominator is off, it results in some absurd conclusions.

Thus, when criminalization results in low key population size estimates, countries that are failing to reach men who have sex with men may mistakenly report they are being successful. Criminalization can contribute to, we concluded, “official denial of the existence or size of key populations; to failure to adequately address their needs; and implausibly high HIV service coverage reports” (Davis et al. 2017, 1). The unrealistically high targets promoted by the UN may contribute to this phenomenon as well, as Wendland noted in her study of maternal mortality reports in Malawi (2016). As part of the FastTrack approach, the 90-90-90 targets were intended to incentivize increased testing and treatment, but they may mask other similar situations where the baselines on which coverage is reported create a false picture of success. This can create a Potemkin effect in which high service coverage reports are based on a distorted, low baseline, creating the appearance of success while masking grimmer realities. According to legend, Potemkin was a fake village built by a local official to impress Empress Catherine II on her site visit to war-torn Crimea. We briefed UNAIDS on this research, and in several cases UNAIDS or national health authorities removed or revised the data. But some countries, when informed of these errors, continue to report success erroneously, and these reports are more ethically questionable. As described in the previous chapter, donors to the global HIV response are aware of the widespread gaps and the need for better data on key populations, and to address this gap, the Global Fund set a corporate KPI in 2012–16 for the number of countries with key population size estimates, working with UNAIDS to encourage countries 50

BIOMETRICS IN KENYA: “EVERYONE SAID NO”

to complete them. Both PEPFAR and the Global Fund convene national HIV planning meetings in which key populations are invited to participate. The push-and-pull between donors and governments has created openings for domestic activists to also raise concerns and demand better data, but sometimes with methodologies that create new contests over power, autonomy, and trust. BIOMETRICS IN KENYA: “EVERYONE SAID NO”

Kenya’s contested IBBS is one example of this. When Kenya reported a new size estimate for men who have sex with men to PEPFAR in 2015, both PEPFAR and several national key populations groups rejected the number as implausibly low. Peter Njane, of ISHTAR-MSM, a Kenyan NGO, said, “We had disputes over how the data was collected. We questioned where they got their information. Donors were there, we’re shown the final product, the money has been used, and the community didn’t accept it” (Esom et al. 2016, 18). In response, Kenya’s national health authorities came up with a plan to conduct new size estimation studies. However, they proposed to do so using biometrics; an approach that Lowray’s ethnography of Kenya noted “creates a more juridical-like relationship” between clinicians and their clients, a “logic of verification [that] simultaneously imparts and reinforces relations of distrust” (Lowray 2017, 132). * “Hey Meg am dashing out to an activist meeting”

During the period in which I was writing on this book, my phone vibrated with incoming emails and texts from Allan Maleche daily (usually addressing me by my nickname, which is Meg). As I reached for the phone each time, part of my brain was already trying to guess might be troubling Allan, a rising rights advocate in global health: some new corruption scandal in Kenya? Global Fund Board debates? Or was he just being searched by security at the airport, yet again, as part of one of those “random security checks,” which often “randomly” happened to select a tall, African male? Allan had started in human rights and health as a law student and part-time data clerk working on a research grant for prevention of mother-to-child transmission of HIV (PMTCT). As he remembered it, while entering the data, he began to wonder what benefits the 51

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women might be getting from the study. A lawyer working on HIV and the law recruited Allan to a small firm, where he got absorbed in a sideline pro bono project, KELIN. Allan soon took over KELIN, building it into a prominent NGO working on national health and human rights law, and the organization was soon recognized globally. I was the Global Fund’s senior human rights advisor from 2013 to 2015, and I first met him when he joined a meeting there on tuberculosis and human rights in 2014. On his first visit to Geneva, he had performed impressive feats of consensusbuilding with UN and government officials. Later the following year, the Developing Country NGO Delegation to the Global Fund Board recruited him as a delegate. Allan has the lawyer’s gift for well-constructed argument; a knack for working a room; and whatever the special thing is that drives him to cheerfully, persistently champion the rights of marginalized communities. He moved up quickly on the Global Fund Board: from delegate to Alternate Board Member of his delegation; then chair of the Implementers Group. From 2017 to 2019 he was a Board Member heading the Developing Country NGO delegation, appointed to one of the Fund’s three influential standing committees. In 2018, Allan also won the Elizabeth Taylor Human Rights Award, a prize given on the main stage of the International AIDS Conference, before a crowd of tens of thousands, and beamed live online. Moments before this ceremony, the leader of a coalition of African women living with HIV that had raised allegations of sexual harassment and bullying at UNAIDS approached Allan backstage and asked him to raise their concerns. Allan hesitated for only a moment; then took the stage and said, “There are many days when the challenges we face in Kenya and globally can seem endless. Human rights are never really secure – they must be fought for every day.” He said he believed the women’s allegations, and called on the UN to set a higher standard on human rights and gender equality (KELIN 2018). When I asked Allan how he had managed this rapid rise in global health, he said he tells himself, “In every situation, try to be the person who’s proposing a way forward, or a way to get out of the quagmire of where we are stuck. . . . You then become acceptable to every warring side.” On this particular morning, he was texting while driving from one national HIV meeting and the next, and the way forward was unclear: “Why does the community have to bear the burden to prove biometrics are not good?” 52

HIV AND KEY POPULATIONS IN KENYA

In order to respond to the drive for data, some countries are turning to new technological tools to track and count key populations. Biometrics are increasingly widespread in tracking delivery of services. But in Kenya, using it with key populations triggered a controversy over who does the counting and how it is done. HIV AND KEY POPULATIONS IN KENYA

Kenya’s HIV prevalence is estimated at 4.7 percent, with approximately 1.6 million people living with HIV and incidence of over 1 percent (UNAIDS 2019c). While the broader geographic region of East and Southern Africa has the highest HIV prevalence in the world, Kenya’s efforts, including increased domestic and international financing, have contributed to “steep declines in HIV infections and deaths from AIDSrelated illness” (UNAIDS 2018, 190). The challenges remain significant, including widespread gender inequality and gender-based violence, and stigma and discrimination (UNAIDS 2018, 190–91). For Kenya’s key populations, the burden is heaviest and data gaps are greatest. The structural barriers that increase their vulnerability include poverty, stigma, homelessness, and criminalization. Key populations in Kenya tend to avoid government agencies and use pseudonyms in order to avoid public disclosure; in addition, sex workers and people who use drugs migrate often in search of housing and employment. Among sex workers, HIV prevalence is 29.3 percent, or nearly one in three sex workers; for MSM and people who inject drugs, it is more than 18 percent (UNAIDS 2019a). These numbers are a weak basis for planning the national response, however, as they date from 2011. Kenya reports no data on HIV among transgender people. In response to negotiations over a previous Global Fund grant to the country, in which the amount and prioritization of direct funding to key populations-led programs became a subject of debate, the national networks and organizations of key populations came together to establish a national Key Populations Consortium. The platform is an ad hoc coalition uniting several national networks and organizations representing men who have sex with men, male and female sex workers, and people who use drugs (some individual transgender people participate, but not a national organization; a transgender leader I spoke with said their network had different concerns from the consortium and preferred to work independently). Jackson Otieno, then of the Gay and Lesbian Coalition of Kenya, a member of the consortium, said, “We had to form the 53

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Consortium to negotiate better for funding. That’s why the pushback [against biometrics] was so spirited. That’s why we have the gains we’ve seen in this country.” In 2015–17, not long after Njane and others raised concerns with PEPFAR that Kenya had implausibly low population size estimates, the Kenyan national health authorities developed a plan, funded by the Global Fund, to conduct an Integrated Bio-Behavioral Survey (IBBS), a form of study that analyzes HIV and risk behaviors among key populations. In this case, the researchers planned to use biometrics, the measurement and analysis of biological data, using physiological attributes such as DNA, face, fingerprints, eye retinas and irises, hand geometry, or veins – and/or behavioral data such as voice or handwriting – for identification purposes (Tzaphlidou and Pavlidou 2011; Seydtaghia 2019). Raw data is gathered, stored, and, in some cases, read through a contactless integrated circuit chip. Newer forms of biometrics can identify individuals through heartbeat, gait, and silhouette. Biometrics are increasingly used in court cases, for identity cards, and in business – for instance, to access iPhones. Since 9/11, many governments, including Kenya’s, have used biometrics at border controls. A growing number of private and nonprofit companies partner with health agencies in use of biometrics. These tools, linked with artificial intelligence (AI), have created excitement about the possibility of “precision public health” that uses tools which “leverage AI to monitor and assess population health, and select and target public health interventions based on AI-enabled analytics” (USAID 2019, 11), especially in developing countries with weak health systems where individuals can be hard to reach. However, because they intrude on human dignity and privacy and “dilute [the self] in a collection of digitized parameters,” a French national ethics committee concluded, biometrics create “legitimate reason to fear for survival of the free space left to an individual” (France National Consultative Ethics Committee for Health and Life Sciences [CCNE] 2007, 6). The fears become more acute and immediate for individuals at risk of arrest, as is the case for key populations in Kenya. THE KELIN AND KEY POPULATIONS CONSORTIUM REPORT

In 2017, Privacy International approached KELIN to develop a report on privacy and biometrics for key populations, and KELIN invited me 54

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to work with them in the process – work that was largely pro bono. We agreed to make the report a joint initiative across Privacy International, KELIN, and the Key Populations Consortium. KELIN produced an analysis of national laws and policies relevant to data and privacy protections, and I analyzed international policies and reviewed academic literature on biometrics and health. The Key Populations Consortium hired a consultant who drafted a position paper. Together, the lawyers, the consultant, and I met with members of the Consortium to gather their input into the draft report, spending a week in Nairobi conducting fifteen meetings with representatives of Consortium member organizations including sex workers, harm reduction organizations, and LGBT groups, in order to understand their experiences of the process and their concerns. In most cases, we met with small groups of between two and five staff of the organizations in their offices, though in other cases we met with individual executive directors. We also met with representatives of WHO’s country office and held off-the-record conversations with two international organizations to understand their perspectives. NASCOP did not respond to a request to meet. I drafted the report, which was reviewed by both KELIN and the Consortium, and published jointly the following year with a public Twitter conversation that three of us participated in (KELIN and Key Populations Consortium 2018). THE STUDY AND THE CONCERNS OF KEY POPULATIONS

In 2014–15, officials at the Kenya National AIDS and STI Control Program (NASCOP) began planning the IBBS study, funded by the Global Fund. NASCOP held meetings during 2015 to develop a research protocol, submitting this to the national ethics review board. The US Center for Disease Control provided technical advice in this process, with other international universities and UN agencies. The research protocol, shared with KELIN and me by key populations activists, planned to use a number of methods to enumerate key populations, outlined plans to protect human subjects, and to obtain informed consent. It was approved by the national ethics review board in February 2015. As related by key populations activists and KELIN, who participated in the process, five months after the research protocol was approved, key populations representatives learned of the plans to use biometrics in 55

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the study for the first time in a meeting with NASCOP. They raised immediate objections, given criminalization of key populations, and called on NASCOP to use other methods. NASCOP, arguing that they had addressed any risks in the ethics review, initially resisted these demands. Key populations representatives asserted that while they had been listed in materials submitted for ethics review, they had not been previously consulted, and that the process was not taking their input seriously. “Why can’t the government use other identifiers?” asked one LGBT advocate. This started an ongoing debate between members of the Consortium, officials at NASCOP, and partner technical agencies. In the end, as described below, the key populations advocates involved the donor agency and UNAIDS in Geneva, and successfully put a stop to the use of biometrics in the study. NASCOP’s main argument for use of biometrics, as explained to me by key populations representatives who had participated in the meetings, was to manage the risk of double-counting and risk that medicines would be sold on the black market. In recent years, NASCOP has made numerous efforts to better coordinate service delivery in a complex landscape of government, clinics, and NGO clinics, but had reportedly found it difficult to manage this task given the mobility of key populations; sex workers and people who use drugs often moved from one location to another. They believed that the use of biometrics, which had previously been utilized in a Nairobi program serving sex workers, would enable better management of programs. Pascal Macharia of Health Options for Young Men on HIV/AIDS/ STIs (HOYMAS), a male sex worker-led organization and member of the Consortium, argued that the flexibility of key populations should be accommodated: “HOYMAS is of the view that a person will only seek a service they need. Some people may collect commodities for others who are afraid of attending the clinic. Stigma and discrimination is still an issue.” Bradley Njukia is Deputy National Coordinator of KESWA, an umbrella group of Kenyan sex worker organizations. He said, “From the sex worker point of view, it’s not really logical. Why don’t you look at people who are not getting treated?” All of the key populations representatives raised concerns that data gathered for the study could be used by the police to target their communities for arrest, given that same-sex sexuality, sex work, and drug use are all criminalized in Kenya. Some Kenyan politicians had made homophobic statements to the 56

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media, especially during the election period. Several activists cited the arrests of key populations activists following an HIV meeting across the border in Tanzania as reason to believe that the Kenyan government could similarly decide to crack down on key populations abruptly. “Look at Tanzania,” said Njane. “Here things are relaxed, but things can erupt like this,” snapping his fingers. Lorna Dias and Jackson Otieno of the Gays and Lesbians Coalition of Kenya raised concerns about the role of the private sector in advancing biometrics for key populations. They noted that a Microsoft-supported project, BioSIM, captures bio-identifiers of Kenyan schoolchildren and uses them to track attendance, justifying reduced funding for some schools where attendance is low (Microsoft Philanthropies MEA 2017). Dias raised concerns about the rights to privacy of the children involved, questioning whether the data could be used, including by Microsoft, in the future. Similar partnerships by World Food Programme with a private data analytics company Palantir generated public criticism (Parker 2019). In the United States, Palantir has partnered with the Central Intelligence Agency, police departments, and Immigration and Customs Enforcement on surveillance and predictive policing programs linked to human rights abuses (Parker 2019). For the companies partnering with development agencies, there is a potential for access to a vast trove of data that can enable rapid progress with developing artificial intelligence (Zuboff 2019). A key concern key populations in Kenya raised was their late involvement in the planning process. Abigael Lukhwaro, Program Coordinator of the Kenya harm reduction program for Médécins du Monde, asserted that putting beneficiaries’ wishes first is a core principle of harm reduction; a top-down approach that sought to impose biometrics could destroy the fragile trust they had established with highly marginalized clients, who were extremely guarded with any identifying data, and who often used pseudonyms to access health services. NASCOP pointed out that some organizations, including one working with sex workers, had adopted biometrics successfully (Mwangi 2007). However, an activist working with MSM told us that his community was unwilling to use those facilities, in part because of their reluctance to use services patronized by women who might turn out to be relatives or neighbors, and in part because of those facilities’ use of biometrics. As Njane put it, NASCOP also argued that communities had not objected to use of biometrics in a 2009 study, but he responded, “Back then we didn’t know our rights. We are empowered now.” 57

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While never explicitly connected to their concerns about the use of biometrics in the IBBS, the contested presidential elections were in the background during my brief time in Nairobi in September 2017, and there were related anxieties connected to biometrics that may have heightened concerns about their use in the IBBS. The 2007–8 elections had been marred by violence (HRW 2016). In 2017, to mitigate risk of fraud, biometric data had been used to identify voters at Kenya’s polls. However, in the contested run-up to the elections, the head of information, communication, and technology at the Independent Electoral and Boundaries Commission had been kidnapped, tortured, and assassinated, and there were allegations that his arms had been cut off in order to obtain his fingerprints to access the voting system (Calamur 2017). When the results of the 2017 election were challenged, it emerged that the servers holding the biometric data could not be checked for fraud because they were located in France, beyond the Kenyan government’s control. Parliament banned the French firm from Kenya for ten years (Mwere 2019). These and related events were unfolding during my week in Nairobi with KELIN and the Key Populations Consortium, and they heightened anxieties in the background of our meetings. As KELIN’s lawyers and I drove around Nairobi, time that was often spent in traffic, the lawyers passed the time by reading aloud and dissecting judicial decisions relating to the elections, debating rule of law, politics, and civic space with me and the driver. While some fears among key populations in Kenya were grounded in direct experience and others were more speculative about the roles of unknown players, they collectively pointed to the anxieties that are created by the intrusive and evolving nature of the new technology and the unstable nature of rule of law. Data stored for one purpose can easily be later used by the state or an enterprise for another purpose not originally consented to. While Kenya’s HIV Act requires the Minister of Health to develop privacy guidelines for collection of HIV information, these guidelines have yet to be put into place. A report by Privacy International notes that most African countries lack data privacy laws, and that [i]n 57 percent of countries in Africa, data processing occurs in a legal void, which means that information collected as part of registration today could be kept for an indefinite amount of time and used for 58

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different purposes in the future, as technology, corporate incentives, or governments change. In such contexts, there are a lack of requirements for how data is managed and stored, which is particularly concerning in the case of biometric data. (Privacy International 2019)

To address key populations’ concerns over the risks linked to biometrics, NASCOP proposed a data protection plan that would identify a neutral entity to store the data, ensuring the study data could not be shared with other agencies without a legal order. Activists agreed this would be helpful. However, they were still concerned that a change in leadership could override the agreement, or that a court could order biometric data be given to the police. And in fact, even in countries where protective legislation exists, data management systems are subject to breaches (Saberin 2018). The debate itself highlighted the changing role of civil society in Kenya, and the contested nature of “country ownership” in relation to global health finance priorities. NASCOP believed it was mandated to conduct the study, given the backing of international donors, technical partners, and the ethics review board, and were eager to produce the data needed to meet a Global Fund KPI on key populations service coverage. Kenyan activists asserted that research could not begin without their agreement and participation, and they successfully leveraged contacts at UNAIDS and the Global Fund to back them up. The key populations networks agreed to maintain a united front within their consortium. They also engaged in extensive outreach. They wrote to contacts in India to learn more about how biometrics had been used for HIV treatment there, and appealed to Ambassador Birx at PEPFAR and to the UNAIDS Kenya country office for support. They also contacted the Community, Rights and Gender team at the Global Fund in Geneva. In follow-up messages after their call with the Global Fund, US government representatives, and representatives of HealthGap, Grace Kamau (representing the Key Populations Consortium), stated that the consortium supported the need for more accurate data on key populations. However, she underscored in a follow-up email on September 19, 2017, “I would like to clarify that our stand on use of biometrics in the IBBS is NO and nothing has been agreed on. The final decision can only be agreed upon by all K.P. consortium membership [in] our upcoming meeting.” 59

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UNAIDS issued an advisory note to the Kenya Ministry of Health (Jacobi and Simao 2016). While the note took no position for or against using biometrics, it raised two concerns: first, the question of whether the use of biometric data is necessary and has specific benefits in the context of an HIV survey; and second, the need to put in place dedicated safeguards. The Global Fund Community, Rights and Gender team did not issue a statement, but held conference calls and involved the Country Coordinating Mechanism as well as the Key Populations Consortium, underscoring the need to negotiate a solution that would satisfy all. The consortium issued further open letters, reiterating their position on biometrics. In the end, their approach was successful. In August 2017, the US Center for Disease Control contacted the Key Populations Consortium “and said they had dropped biometrics” from the planned study, and that they would “make key populations groups our partners.” The Global Fund confirmed that the remaining funding for the study did not need to be returned and could still be used for the same purpose. As Njane said, “The major thing was the community coming together and speaking with one voice.” Dias agreed, “Everyone just said no, and kept saying no.” By remaining united across diverse key populations groups, and leveraging their connections at senior levels of global health agencies, the Kenyan organizations had successfully shaped the methodologies used for a study about their constituencies. Participants in the discussions said that in Kenya, key populations advisors would now help oversee the research. The debate over biometrics in Kenya also sparked discussion and review of policies in Geneva and in Washington, at a moment when donors were under pressure to demonstrate progress, and biometrics were being rolled out more widely to achieve this purpose. As a senior US official working with PEPFAR said in our interview, “There are critical concerns about the intersection between public health and criminalization. There’s a hunger for more data among donors that often goes right to the heart of that intersection.” The heads of the two leading global health financing agencies, however, while careful not to endorse biometrics for key populations in our interviews, did not rule it out for other groups. Peter Sands said that biometrics offered clear benefits in certain cases, “Particularly where you have highly mobile populations, [and] it’s often quite difficult to track down whether or not treatment is consistent, or whether this is somebody who’s come in before.” The risks are 60

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in situations where there are human rights considerations, then introducing biometric or any other form of identity system creates risks around individuals’ human rights position. So I think it’s quite difficult to generalize, because it very much depends on the degree to which identity can be used against people.

Ambassador Birx stated, “We will not fund behavioral surveys that utilize biometrics. We just think that we cannot be assured the longterm confidentiality of key populations. So we will not support biometrics linked to risk.” However, she said, PEPFAR had successfully used biometrics in Haiti as part of monitoring in other programs. Kavanagh and colleagues’ review of ethics and human rights concerns in public health surveillance concluded that “the biometrics approach is not currently likely to be appropriate in many jurisdictions” (2018). However, the drive for data continues. Gavi, the Vaccine Alliance, announced in 2019 that it would use biometrics to track infant vaccinations (NEC Corporation 2019). In Yemen, the World Food Programme announced it would suspend food aid after Houthi rebels refused to participate in an anticorruption data-gathering program that included biometrics (Parker and Slemrod 2019). The use of biometric data-gathering is rapidly on the rise in refugee programs as well (Crisp 2018). In a phone interview, Paul-Gilbert, program manager at the Global Network of Sex Work Projects (NSWP), affirmed: The use of biometrics – which is being pushed more and more – is something we would strongly advocate against if the data can be accessed by the government, and the government criminalizes these populations. For other programs that gather data, the issues would be: Who has access to this data? Who publishes it? Do people check, before they publish, what can be published?

When I asked Allan, in late 2018, what the future held on this issue, he said, “Kenyan civil society will not give up. Biometrics still remains an issue.” WHO STUDIES AND WHO GETS STUDIED?

Donors and UN agencies are pushing countries to do more in order to progress toward the end of AIDS. But in the complex power relationships that shape both transmission of HIV, and access to services, data on key populations has become a flashpoint for wider contests over power, autonomy, and trust. Sex workers have been especially vulnerable to intrusive 61

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data-gathering in the HIV response, and their transnational networks have been vocal in demanding more equitable and rights-respecting approaches to data-gathering. Authorities have at times forcibly gathered data on sex workers, without informed consent or basic privacy protections (NSWP 2014; Agence France Presse 2015; Mgbako 2012; Moszynski 2008). The Global Network of Sex Work Projects has opposed forced testing of this kind, arguing that it violates human dignity and discourages sex workers from HIV services (NSWP 2013). Similarly, as the focus of donors and global health agencies shifted to targeting hotspots, this drive for more precise and granular targeting created risks for criminalized key populations whose locations could be precisely mapped, exposing them to arrest or violence (Amon 2013). The Global Network of Sex Work Projects has warned in particular against geolocation of hotspots as a methodology for data-gathering about their constituency and cites an example in Kenya where publication of a map showing sex worker locations in a peer-reviewed journal article was followed by harassment and arrests of sex workers (2015, 4, 7–8). Similar debates are now emerging about the use of phylogenetic analysis to map transmission of HIV (Chung et al. 2019). As Paulo Longo writes, “Sex workers are used to being ‘subjects’ of research and generally not participating in the process. Their role is usually restricted to giving information and facilitating access to (other) respondents. They generally do not have easy access to the results and these are not commonly applied for their benefit” (Longo 2004, 9). To address these and other risks, NSWP recommends ensuring that sex worker-led organizations “fully understand and have control and input over the process of data collection, analysis, and dissemination of the information” (2015, 14). This goes a step farther than standard practice among epidemiologists conducting key population size estimates in many countries, who often include key populations as low-paid data-gatherers or “enumerators.” Rather, NSWP and other sex worker–led organizations have called for research processes to go a step further and be sex worker–led (Ditmore et al. 2010). Wolffers argues for “participatory community-based approaches . . . based on a dialogue” (Wolffers 2004, 1). Longo, himself a former sex worker, described a study in which he was a Principal Investigator, and in which sex workers “actively participat[ed] in all phases, from the design of the research to the production and distribution of the reports” (Longo 2004, 9). Similarly, several organizations that are led by or work closely with sex workers have published research guidelines 62

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that insist on the right of sex workers to define the terms of engagement (Sonke Gender Justice et al. 2014; Stella 2003; WONETHA 2014). Some indigenous peoples have taken a similar approach to strictly bounding and defining the kind of power arrangements they will consent to forming with researchers. According to Trevor Stratton, who coordinates the International Indigenous Working Group on HIV & AIDS, the Working Group has developed an approach that aims to move past framing indigenous data in terms defined by researchers using their own frames (King 2017). Externally designed research, Stratton said in our conversation in August 2019, tends to produce “Helicopter research: landing on the roof, taking the elevator down to the 5th floor.” Rather, he said, he and his colleagues seek to develop deeper, long-term partnerships with researchers, in order to generate “two-eyed seeing”: multidimensional insights into the “emotional, mental and spiritual health” of a community. This kind of assertive questioning of the data and methodologies troubles the traditional subject-object relationship in public health research, in which a subject (researcher) studies an object (the person studied). However, it is in line with broader HIV activism’s history of creating new forms of subjectivity that include interrogation of scientific authority. While the problem of conducting key population size estimates and other studies about criminalized groups may appear to be technical, in fact, it is primarily a political problem. The solution to gaps in data on hidden key populations is not a technocratic solution: there is no silver bullet to eliminate a rational and sensible absence of trust. Reforming laws to decriminalize key populations, electing leaders who do not make stigmatizing statements, are political solutions. But as NSWP and others have argued, a related solution is to address the power imbalances in data-gathering and place communities in leadership roles. * During the biometrics debate, I was at the 2016 International AIDS Conference in Durban, South Africa, where I learned at a preconference that CVC, the Caribbean organization that had helped shed light on the data paradox, was planning a regional study of HIV among key populations. I reached out to John Waters to learn more. John, a native of the Dominican Republic, coordinates research for CVC. He has a low-key style and a faintly lingering accent from a childhood in Scotland. Behind his friendly grin and loose plaid shirts is a razor-sharp brain powered by big ambitions for key populations. 63

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At midday, conference goers walked outside the meeting hall for a march of thousands in downtown Durban, holding banners with slogans such as “Don’t Brexit the AIDS Response.” Afterward, we sat outside the conference center with coffees in the bright sun. John said that the lack of accurate population size estimates was now acknowledged to be a critical gap by all the key actors in the Caribbean. He was especially concerned about the issue we had corresponded about: how countries with poor size estimates overestimate their success. There had never been key population size estimates in the small island countries of the Eastern Caribbean. Under a Global Fund grant, CVC would lead the work of conducting the first-size estimates for men who have men and sex workers in six countries. John was excited to involve a team of researchers from the University of Alabama at Birmingham’s Sparkman Center for Global Health. However, this project, he said, was going to be first and foremost about re-engaging dormant community-based groups in each country, so that when the data was gathered, they would be positioned to use it to provide services. I asked if I could observe their study and document the engagement of communities. John agreed. I was eager to get on the ground again, to confront the data paradox. As John and CVC’s project got underway, it began to demonstrate both the impacts of data-driven global health decision-making on real people, and a potential alternative approach to iris-scanning, DNA-scanning, and other top-down approaches to data-gathering.

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The drop on the hillside of St. George’s, the capital of Grenada, is steep – one false step and you could tumble past houses, shanties, shops, and cars into the blue bay sparkling below. Without a sidewalk, you navigate gingerly around parked cars and the steep ditches on either side of the road, hoping the next one careening around the bend won’t take out your toes or concuss you with a rearview mirror. In this chapter, we telescope in from a global perspective to a local one – a precipitous shift to a hilly terrain shaped in part by a history of colonialism, invasion, and the aftermath. Grenada is about as far as you can get from a priority country in the global HIV response. Many people in global health are unsure where the country is located, or confuse it with the Spanish city of Granada. Grenada is a small island state, HIV prevalence in the general population is low, and there is no data on HIV among key populations. It is classified as an upper-middle-income country. Thus, while external aid, including aid from the Global Fund and the US government, previously funded much of the region’s HIV response to date, by the time I arrived, donor interest in the Eastern Caribbean was clearly on the wane. The mood in the halls of those agencies was changing. Donors increasingly felt that upper-middle-income countries in Latin America and the Caribbean could afford to foot their own health bills; they just “lacked the political will” to do so. The shift in the view of donors toward middle-income countries had emerged in the context of the pressure to reach ambitious global goals, such as the end of AIDS, with diminishing resources. Under those 65

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Figure 3.1 Grand Anse Beach, Grenada. Credit: Sara L. M. Davis

pressures, as noted already, high-prevalence, low-income countries were a greater priority than middle-income countries like Grenada, where HIV is concentrated among key populations. In the race to reach the end of AIDS in high-prevalence countries, key populations were being left behind – or, as Rico Gustav had put it, “We were never there in the first place.” Criminalization, stigma, and violence contribute to lack of resources, which in turn reinforces the lack of data. Absence of evidence about key populations was taken as evidence of absence of their existence. As donors withdraw, domestic financing is increasing, but programs for key populations have relied almost exclusively on external donors; when those donors leave, the programs often end (Arán-Matero et al. 2011). Meanwhile, the same dynamic was playing out around the world, for activists in middle-income countries in Latin America, in the Middle East and North Africa, in Eastern Europe and Central Asia, and in Asia and the Pacific – all the countries whose national income indicators were climbing. Rising national incomes were triggering panic among thousands of civil society organizations serving key 66

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populations, which all depended on external aid. The heat was on globally to do key population size estimates and to do them fast. At the time of this study, Global Fund staff were warning Caribbean advocates that the Fund’s Eligibility Policy might in future eliminate a provision that kept small island economies eligible. It was not clear, at that moment, just when the Global Fund would transition from the Eastern Caribbean. The CVC study might be the last chance that Grenada and its neighboring countries had to get this data. Caribbean advocates like John Waters urgently needed data on key populations to push for funding for HIV in general, and for key populations in particular: for the Global Fund, and to persuade national health ministries to add a line item or two for HIV prevention and community mobilization to their national budgets. That resources are constrained became clear in Grenada’s Ministry of Health, which occupies a quietly decomposing building in the Ministerial Complex nestled at the top of a long drive in the lush Botanical Gardens. In the building lobby, the portrait of Prime Minister Gairy is more than two decades out of date. An unraveling gray corporate carpet lines the hallway whose chipped walls lead to the senior HIV advisor’s office, where we sat because there just weren’t enough available conference rooms. Dr. Francis Martin brings dynamism and precision to his work. He’s always crisp and polished, an energy that fills the windowless four walls around his desk. He described the dire health needs of the population of Grenada. The health budget was 6 to 7 percent of the country’s gross domestic product (GDP): “We’re not getting a smaller piece of the pie than others in the region, but because our GDP is small, it’s a smaller amount.” For HIV, Dr. Martin faced a perennial frustration with getting people to test and start treatment. Out of a population of 107,825 people, there were 570 people known to be living with HIV, but incidence was on the rise, and the true number “may be significantly higher” (Chaudhry et al. 2018). It has been difficult, in particular, to get men to take the test. An annual testing day at street festivals helped, but every other day of the year, he was consumed with the problem of missing people. John Waters suspected that the spike in HIV among Caribbean men in stable heterosexual couples suggests that many of them were “on the down low” hooking up with other men. For Dr. Martin, “Because we don’t fully understand the sociodemographics, it’s difficult to adequately allocate resources. We’re blinded in terms of what programs, numbers, 67

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quantity and quality of programs to address those. I hope doing this [study] will help us to make good management and policy decisions.” It would also, he said dryly, “help to debunk some of the myths that exist even among the medical fraternity of health care providers, help us to move away from anecdotal and ideological information and rely on hard, scientific facts.” By conducting an ethnographic study of the CVC study, with the support of John, Dr. Martin, and their teams, I hoped to better understand the challenges with finding and counting key populations in practice, and what happened when civil society participation was introduced into the process – how data was “cooked” by researchers (Biruk 2018). I also hoped to understand how decisions taken using indicators and data in Geneva and Washington affected the lives of real people, and how community engagement might affect the process. How would community members feel about the result? Over 2016–19, I visited the Caribbean repeatedly, watching as John worked to foster partnerships between health officials and civil society activists in each country, recruiting and training researchers, gathering the data, and finally pushing for the data to be published and used to fund services for key populations. Without John’s dogged persistence in locating, inspiring, and connecting others around shared goals, this never would have happened. As it was, it became something of an epidemiological epic. John traveled constantly from island to island to haggle with and persuade others, his trips frequently interrupted by elections, bureaucracies, personal politics, plane breakdowns, and hurricanes. I checked in with him often via web conference and text message to hear what was happening across the region, but mostly kept focus throughout on Grenada, flying over on my holidays. I also spent some time as a tourist in Grenada, exploring the island by GPS, and found from time to time that my rented jeep had ventured into a blind spot, or that Google Maps had me fixed firmly in the ocean. Grenada has always been a little bit off the global map. To map is to impose a form of abstraction on a landscape, which may or may not be meaningful for people who live in and know that landscape intimately. By its nature, maps render some things visible and others invisible. In particular, as I learned my way around, I was conscious of walking in the bootprints of previous Americans. Grenada’s 1979 Marxist revolution attempted to address chronic unemployment and deep economic inequality by putting in place social and economic reforms (Marcus and Taber ed. 68

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1983; Collins 2013). The revolution devolved into factional struggles which ended in the execution of Prime Minister Maurice Bishop, a number of government officials close to him, and an unknown number of civilians (Government of Grenada 2009). The United States invaded in October 1983. The Reagan administration’s justification at the time was a letter from the Organization of Eastern Caribbean States (OECS) requesting its assistance, and threats to the safety of US students at St. George’s University, both justifications that have been contradicted in some Grenadian accounts (Coard 2018; Collins 2013; Lewis 2013). Maps, or the lack of them, played a central role in some of the bungled aspects of the US invasion. The troops on the USS. Guam had prepared for Operation Urgent Fury by watching the John Wayne film Sands of Iwo Jima, but with little information on the country (Spector 1983, 6). Their invasion “was launched with little accurate information about conditions on the island. . . . Since standard military maps were not available, several other kinds of maps, including a reprinted tourist map of Grenada with a makeshift military grid overlay, were issued” (Harper 1990, 55). Because the US Marines and Army had different maps, at least some of the targets on which the United States fired were mistaken (Spector 1987, 10). While the invasion was followed by increasing stability, Grenadian society “continues to struggle with locating the proper place of the revolutionary period . . . in its historical memory” (McCalpin 2013, 139). The wounds remain deep, and few Grenadians speak about this painful period. Mapping is often a critical part of “civilizing projects,” but the accompanying errors sometimes have problematic follow-on effects. Scott shows that colonizers used mapping to “attempt to make a society legible, to arrange the population in ways that simplified the classic state functions of taxation, conscription, and prevention of rebellion” – and, presumably, disease control – creating “maps that, when allied with state power, would enable much of the reality they depicted to be remade” (Scott 1999, 2–3). Scott finds these projects of statecraft created “rational orders” so abstracted from local realities that the resulting policies often did more harm than good. The parallels for HIV are obvious: as mentioned in the previous chapter, a project that aims to chart the locations and numbers of hidden populations risks doing different kinds of harm. With the CVC study, the aim of the mapping is to make a population legible to itself, so that its champions can advocate for, and deliver, services to keep that population alive. 69

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These historical, economic, geographic, and political factors combine to make Grenada a valuable vantage point from which to reflect on the delicate work of mapping and rebuilding a network of key populations. Researchers on HIV tend to focus on big countries with high HIV burden; they are grand stages from which to make big points about the global governance drama. Maybe a smaller country can help to make a small point about what sometimes gets forgotten in the race to reach global targets and end AIDS. Put simply: if you can’t reliably count men who have sex with men and sex workers on a small island, can you really count them anywhere? * This section pans out just far enough to locate Grenada geographically, historically and in the context of the regional HIV response, for readers unfamiliar with the country. The rest of this chapter explores what happened in the early phase of the size estimation study, as John and his colleagues raced against the clock to design their study and put essential partnerships in place, before funding ran out. The nation of Grenada, a leading world exporter of nutmeg often referred to as the “Spice Island,” is actually made up of three islands: Grenada, Carriacou, and Petit Martinique. It is the second-southernmost country in the chain of islands that make up the Caribbean, located just southwest of Barbados and north of Trinidad and Tobago. The first inhabitants of Grenada were the Taino or Arawak Indians, then the Kalinago or Carib Indians. The Grenada Kalinago actively fought Spanish colonization, but when their loss was assured, legend has it that one of the last Kalinago communities committed collective suicide by leaping from a peak on the northern end of the island. Spain invaded in the sixteenth century, then France and Britain alternated rule of the country for most of the seventeenth and eighteenth centuries. Britain took control after 1783 and made Grenada a profitable sugar colony, incorporating its plantations into the transatlantic slave trade. As Phillip’s (2010) study of women in Grenadian history shows, resistance continued throughout this period. In the wake of the Haitian revolution, in 1795, Julien Fédon, a free colored planter, led a revolt in Grenada that took most of the island from the British. It was ended the following year, though Fédon himself was never caught. As Phillip shows, resistance was sometimes less visible, exercised by women who ran away from slavery, vandalized colonizers’ crops and equipment, or supported and supplied rebel troops (Phillip 2010, 32–35). 70

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Grenada did not achieve full independence until 1974. In 1979, as left-wing governments were elected across the region, a socialist revolution swept to power in Grenada. Four years later, the revolution fell apart: army troops massacred protesters and executed president Maurice Bishop along with two other cabinet members. The United States invaded, the culmination of a traumatic period rarely discussed in Grenadian public discourse. “There are as many versions of what happened as there are Grenadians,” writes McCalpin (2013, 117). In the aftermath, critics have argued, tax codes were revised to benefit foreign investors, and the gap between rich and poor grew (Zunes 2003). The US invasion of Grenada was the first to use humanitarian and pro-democracy rationales for military action that was followed by economic deregulation and a resulting “upward flow of capital towards the already wealthy” (Forte 2013). While Grenada’s economy grew gradually, two hurricanes in 2004 and 2005 caused infrastructure devastation that weakened the national spice industry, leaving a debt burden of $347 million and little fiscal space for investments in health or other public services (Government of Grenada 2013). Meanwhile, the region was contending with the second-highest HIV prevalence in the world after Sub-Saharan Africa. The HIV epidemic first emerged in Haiti, having probably spread from central Africa. While infections have gradually decreased and the Bahamas is now the only country in the region with a generalized epidemic surpassing 1 percent of the general population, HIV is on the rise among key populations across the region. Thus the donor discourse about lack of political will to fund health in upper-middle-income countries has a basis in fact, but also risks erasing a key part of the history of AIDS. When some of the first waves of HIV cases emerged from the Caribbean in the 1980s, it was the Reagan administration’s lack of political will to respond, and its stigmatizing response to HIV among Haitian migrants, that helped turn small domestic outbreaks into a global pandemic. Like many countries in the region classified by the World Bank as an upper-middle-income country, Grenada remains a fragile and heavily indebted economy dependent on external aid; its small HIV epidemic also undermines its growth potential. I spoke with Dereck Springer, director of the Pan-Caribbean Partnership against HIV and AIDS (PANCAP) and former chair of the Implementers Group on the Global Fund Board, on July 30, 2018. Springer said that while the 71

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absolute number of people living with HIV in the Caribbean is small, “[w]ith HIV, if we don’t ensure that we sustain the gains, it could threaten sustainable human development, especially in the context of hurricanes that cause displacement, impact the health system. . . . We are now bracing ourselves for the next hurricane season.” The effort to sustain the gains on HIV regionally has been hampered by numerous gaps in information. As of 2017, nearly half of the fifteen Caribbean Community member states had not reported HIV prevalence to UNAIDS. Most Caribbean countries lack data on HIV among key populations, though in the cases where it exists, prevalence rates are alarmingly high: in Jamaica, an estimated 32.8 percent of MSM are living with HIV. Regional consultations convened by the Pan-American Health Organization (PAHO, the regional office of WHO) identified stigma, discrimination, and criminalization as barriers to services for key populations, and prioritized strengthening the health system response in part by “increas[ing] the availability and use of strategic information” on key populations (PAHO 2011, 30). Rates of stigma and discrimination in the general population are also high and hamper the participation of men who have sex with men in the health system (Beck et al. 2017). Most countries in the Caribbean criminalize same-sex sexual activity (ILGA 2019, 397–425). As a result, many men who have sex with men were hidden: “This environment has led [men who have sex with men] to self-identify as heterosexuals living a double life, married with children on [the] one hand while secretly engaging in sex with males on the other” (PAHO 2011, 6). As John put it, they were living on the down-low. There were many countries in the Caribbean with no data for key populations or out-of-date data. As two US experts explained to me, the United States had attempted repeatedly to do key population size estimates in the Eastern Caribbean in the past, but the risks due to homophobia and criminalization had made these difficult to implement. Now the Global Fund was urging countries in the region to gather better data on key populations. As discussed in the first chapter, the Fund had approved a Key Performance Indicator (KPI) to track institutional progress on the number of countries able to report size estimates and service coverage data for key populations. Thus two global policies or tools already discussed were appearing in conversations in Grenada: the KPIs, and the Eligibility Policy, which included a provision protecting eligibility for small island countries, 72

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a provision that might get removed in the future in order to enable the Fund to direct more funding to high-burden, lower-income countries. The Global Fund’s multicountry grant to the Caribbean included the size estimation study. The Secretariat of the OECS was the principal recipient contracted by the Regional Coordinating Mechanism to be responsible for the regional grant, and CVC would conduct the population size estimation studies in Eastern Caribbean countries. * As John and his colleagues began preparing to launch the project, he shared their original concept notes with me. CVC’s project aimed to estimate the size of populations “of both female sex workers and [gay, trans and other men who have sex with men],” and to map hotspots, developing subpopulation profiles. They planned to do this study for men who have sex with men and transgender people in five countries of the Eastern Caribbean: Antigua and Barbuda, Grenada, Saint Lucia, St. Vincent and the Grenadines, and St. Kitts and Nevis. They would do the same process for sex workers in Dominica, Grenada, St. Kitts and Nevis, Saint Lucia, and St. Vincent and the Grenadines. CVC also planned a tuberculosis prevalence study in prisons in three countries: Antigua and Barbuda, St. Kitts and Nevis, and St. Vincent and the Grenadines. While tuberculosis is the leading cause of death among people living with HIV internationally, John believed that TB was probably not being diagnosed in some HIV patients with TB coinfection because they were asymptomatic. I began to look into the methods used for size estimation. UNAIDS, playing its normative and technical role, has published guidance for countries on how to do this. The guidance recommends beginning a population size estimate by defining the population and geographic area; conducting formative research using qualitative research methods, in order to learn more about visibility and practices of the population to be studied; and reviewing published data. Research methods for the size estimation include census and enumeration methods (for example, using face-to-face interviews to count populations), the capture-recapture method (in which successive groups of people are counted in a given location), snowball sampling (in which respondents introduce other respondents), and others (UNAIDS/WHO Working Group 2011). Many size estimates use multiple methods and triangulate the results. As one colleague observed, the methods used in size estimation are derived from those used to tag elephants or pandas in the wild, 73

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to estimate size of animal populations at threat of extinction: an unfortunate parallel for hidden key populations. In the formative phase, CVC’s initial plan was to use several methods; as discussed later, these methods were revised to adapt to the context once the study got underway. Initially, they planned to do time-location sampling, aiming to “approximate probability sampling by mapping the universe of venues where these key populations can be found, randomly selecting the day, time, and location for recruitment and systematically selecting participants from the venue” (CVC 2016, 5). They would combine this with respondent-driven sampling, using peer referrals to find “a myriad of hidden subgroups (seeds) that may not congregate at all – such as ‘down-low’ men, or young women engaged in transactional sex – using non-identifying codes to link enrolled participants to those whom they refer.” The study would also use some other methods; initially, they considered doing an online survey, in-depth qualitative interviews of selected key informants, and semi-structured focus group interviews, though as noted above, some of these methods were revised later (CVC 2016, 11). As the process developed, and the challenges in finding key populations became more evident, CVC revised its approach: it abandoned time-location sampling when it was clear that there were few stable meeting locations, and added in “wisdom of the crowds” to average the estimated population size based on informant estimates. CVC even drew, where they could, on data shared by gay dating apps, using a web/ mobile app multiplier method to generate another estimate of male users registered in some countries. At the end, the research team planned to triangulate the resulting estimates and use these to extrapolate national numbers. CVC’s approach had an additional component that set it apart from most other key population size estimates described in the UNAIDS guidance: participatory action research, a form of research that “seeks to understand and improve the world by changing it” (Baum et al. 2006, 854). In this approach, community engagement and empowerment are built into the research design in order to facilitate future use of the research for practice. For John, including participatory action research was essential, because the purpose of the study was not only to generate numbers, but also was “really about strengthening the outreach work . . . and the services that are provided to key populations in the [Eastern Caribbean].” He aimed to do research that “enables us to really drill 74

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down” and characterize local subpopulations who “often times have more things that are different about them than things that are in common,” and to take these nuanced differences into consideration in designing interventions in partnership with community-based groups. In an early interview, he said, “Obviously this is a blanket statement, [but] you’re much more likely to get individuals that are really committed coming from civil society.” Many of the Caribbean civil society activists he knew were volunteering because of personal experiences that had driven their commitment, and because there was no funding to pay for their time. One of John’s collaborators on the study was Julia Hasbún, a Dominican veteran practitioner of participatory action research, and a passionate advocate for key populations. In our interview, Julia underscored the importance of civil society as partners in the research: “They are the ones who go to the vulnerable populations, it’s not the government.” This was why she said she liked working with John: he was a risk-taker on behalf of others, and his motivation, in contrast with some civil society leaders, was “not to grab the money; it’s to take the money and invest it in the best way possible.” To help design the research and analyze the data, John brought in Dr. Henna Budhwani of the University of Alabama at Birmingham as a co-investigator. Henna, a dynamic young sociologist with a streak of premature gray in her long hair, had worked with John before in Jamaica, and was still relatively new to HIV research. But she also shared his and Julia’s sympathy for marginalized communities, based on her own former studies of stigma, abuse, and depression in her community of Muslim American women. Through using participatory action research, John and Julia explicitly encouraged the study participants to define priorities and frame them in local languages, to reveal diverse local specificities and officially denied difficult realities, and to use this participatory approach to challenge global categories and approaches. This was what the Global Fund at its best did best: through its funding and governance, creating the kinds of partnerships and platforms that were a complex and fluid meeting place for projects of top-down governance and grassroots empowerment. But for all that to work relied heavily on a translator like John and some of his colleagues, who had the trust of all sides and who could walk the line between state projects and community ownership of the data. 75

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Their approach challenged traditional donor-recipient power relationships, and in part because of this, and because of weather and infrastructure and bureaucratic hurdles, they almost immediately ran into numerous challenges that caused repeated delays. * Before research could begin, the team needed to conduct formative assessments in three countries and use these to finalize the research protocol, validating it in a regional workshop. The protocol would then be used to apply for ethics review board approval in all six countries, but in many of the countries the ethics review board had not met for some time; most were unfamiliar with the kind of research being proposed here. CVC also needed to establish national steering committees in each country, and to identify partner civil society organizations to work with, as well as allies in all six of the health ministries. In this preparatory phase, they ran into both political and administrative challenges. First, there were political challenges. The team faced ongoing pressure from the health ministries in some countries to manage the funds and own the processes directly, something that John resisted as he was concerned that the ministries might not have the needed relationships with either the communities or the local civil society organizations. Meanwhile, the OECS demanded geospatial mapping data for all the key population venues, with this data to be turned over to national health services. John suspected this pressure was coming from its member states. He was adamant that that was “a non-starter,” as the data could be used to target individuals for arrest, and pushed back. While these complex negotiations were underway, several of the six countries held elections and changed leadership. This put all the agreements CVC had reached with earlier administrations, including previous health ministers and chief medical officers, into question, said John on one phone call: “During the [Global Fund] concept note development, the countries were involved. We thought all the countries were on board and that we had taken decisions with them. [It turns out] that’s not always the case.” He took multiple trips to regional meetings, “going back to square one” in his negotiations with health ministries. He was hopeful throughout: “It’s mainly taking time to approve stuff and get buy-in; they’re not opposed.” Antigua was one frustrating example. CVC had planned to do a tuberculosis prevalence study in prisons there, for which they had won the support of the health minister and chief medical officer. However, 76

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after an election, John’s negotiations had to begin anew with the newly appointed officials. Just then, a journalist came to the country to investigate prison conditions, and published a damning exposé (Handy 2016). The health ministry canceled the prison study. For Henna, the resistance by some of the governments came as a surprise: Initially I didn’t understand this [HIV study] was not something health ministries were welcoming. The assumption in my head was, of course we’re doing size estimates with countries that want this data. With the prison studies, we sent an infectious disease expert to Antigua to get the lay of the land, and now we’re not conducting the study in Antigua.

Added to these political challenges were the logistics – difficult travel, limited funding, slow disbursements from the Global Fund, identification of partner NGOs, and recruitment and set up of research teams and equipment needed in each country. There were also budget pressures. Part of the plan for this study was to procure tablets to do the surveys, because respondents could be handed tablets to answer some of the more sensitive sexual questions, instead of having to speak to someone. Some Global Fund grant money was reprogrammed to other purposes, leaving less for the size estimation study; the research team was required to deliver the same results with less funding. That meant less money for tablets and less money to hire data-gatherers. This slowed work further. The annual hurricane season and long Christmas holidays imposed further delays. The pressure was growing on the team to do the research in shorter time, with less funding, and to deliver rapid results. By early 2017, John was finally ready to begin the formative assessment to lay the foundation for the study, and here I began to get a sense of the methodological challenges that would be added to the political and logistical barriers. Based on interviews and observations, the formative assessment helps determine whether the population is visible, where they congregate, who the gatekeepers are, and how they interact with the public and with officials. Based on this assessment, CVC would finalize the research protocol, hold a workshop to standardize it across all the countries, and then apply for ethics review board approval in each country. I flew to Grenada to tag along. Now CVC began to confront the third and potentially greatest set of challenges: those posed by stigma, discrimination, and the mistrust of a community largely driven underground. 77

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In early January, John landed in Grenada. I had been there for a few weeks already, doing some vacationing and exploring of the field site. I picked him up at the airport in a rented jeep, navigating on the unfamiliar left side of the road. While I wove through Grenada’s unpredictable traffic of careening trucks and drivers stopping for neighborly chats with pedestrians, John broke down the tasks ahead – a workshop on sexual and reproductive health for regional health care workers, meetings with Henna, and interviews with community activists and former peer outreach workers. We swerved around the private minivans that serve as buses, which careened down the street, blaring soca music, stopping precipitously to recruit passengers through open doors. I shared what I’d managed to learn about Grenada in a month as a visitor. I had driven around the island with friend and fellow AIDS activist Karyn Kaplan, getting lost in hilly back roads. Grenada’s main tourist destination is Grand Anse beach, a blindingly beautiful two miles of white sand and turquoise bay near the airport. Off the beach drag, the hilly island stretches north. While the capital’s marina bristles with the masts of sparkling yachts, that pocket of luxury is belied by stark poverty in the center and north of the island. Many people live in wooden shotgun shacks, propped up above mud roads on stilts or cement blocks. We stopped at a sandwich shop in Gouyave (pronounced “Gwov”), a small town famous for its fish market, its narrow streets lined with buildings whose hand-painted signs could have first been hung in the 1950s. Shops were shuttered. Chicken roti, a spicy curry wrapped in flat bread, was what was for lunch, and no one else seemed to be buying. John asked if I’ve been able to locate any red-light area with sex workers, perhaps close to the tourist district, but I had not. The bars along the beach closed at 10:00 p.m., and most of the hotels were expensively, blandly quiet. The occasional cruise ships only docked for the day, leaving at night. While I’d been hit on by the occasional Rasta working the beach, they mostly seemed interested in finding a foreign girlfriend who would also buy small bags of nutmeg or marijuana. Through his civil society contacts, John lined up a few initial interviews with peer outreach workers who previously worked for the Caribbean HIV/AIDS Alliance (CHAA), a regional initiative now shuttered due to lack of funds. In the upstairs conference room of a local community library, we met with a few young people who were watchful, shy, and defiant. 78

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One young man who recently moved to St. George’s from the countryside described his fear at the overwhelming big city. Being gay in Grenada was “like a disease,” he said quietly. “No one wants to be by you, touch you – even members of your own kind reject you.” There were distinct social classes, and as for the high rollers, “You can’t lime with them; they won’t talk to you.” Later, he texted me to ask for help with finding an apartment. A young woman, formerly a CHAA outreach worker, said there were many young women involved in transactional sex who “don’t perceive themselves as sex workers.” These women went to bars “where they think rich men are at, and try to look as fancy as they can.” Homophobic violence was rare in Grenada, she said: “Social scorn is the bigger problem. We like to slut shame a lot.” Grenada’s conservative public culture is inherited in part from its colonial past. The country is deeply religious, majority Roman Catholic (heritage of the French), with a strong and growing Protestant minority (promoted by American evangelists), with tough laws that criminalize sodomy and sex work (inherited from the British). Those seen as violating social mores face social death. To understand this context better, I met with Jeannine SylvesterGill, who heads the Grenada Planned Parenthood Association in a small building on one of the steep side streets in St. George’s. She was petite and dynamic, a clear-eyed advocate for the rights of young women. Jeannine was also master of code-switching. In a majority Grenadian room, like the workshop for health care workers CVC organized that January, she worked the side-eye, cracking astute jokes in local dialect that got the whole room laughing. With visitors like me, she moved into crisp American English. I asked her what she estimated to be the size of key populations in Grenada. Jeannine was reluctant to give an answer. Eventually, “if you really force me to put a number up on the wall, for men who have sex with men I’d say 6 percent, not as much as 10 percent,” of men in Grenada. But for sex workers, given widespread reliance on transactional sex to supplement women’s meagre incomes, she said, “There is such a spectrum; it’s really difficult for me to say that yes, she’s a sex worker.” We met in her basement office, while out on the street, the sun was beaming, cars were honking, and there was a steady buzz of conversation. The corner diner had a long line of local professionals filling Styrofoam containers with goat stew and macaroni pie. But in the Planned Parenthood clinic above Jeannine’s office, the silence was grim: a few 79

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women stared blankly at the floor, the TV, anywhere other than at each other. Groups like Jeannine’s were long familiar with the challenges of finding and serving people who hid in order to survive. If her estimate was accurate, there might be between two and three thousand men in Grenada whose survival depended on their skill at hiding their sex lives: a lot of people hiding in plain sight. A civil society activist working with men who have sex with men told me that many men he knew were leading double lives: I’ve seen it, I can tell you. I live in an area called Mont Tout. At night, you see . . . these guys, hardcore guys on the street that condemn homosexuality. . . . By day they would throw these words at me, [but at night] in the club, guys would brush past you a few times, and you feel that they’re throwing you bait. A lot of bisexual guys would have a girl stand next to them. . . . They’re sending out signals in a group like, “Well, look at all these fine-looking people here tonight.” When we’re alone, [they] explain that “When I said that, I meant you.”

Untangling the layers of play, coded communication, and plausible deniability in this study would not be easy, either for those counting or those counted. Some of it would require overcoming endemic mistrust by men who have sex with men and female sex workers of the health care system. At a CVCorganized workshop, which included twenty health care providers from Eastern Caribbean countries, health care workers wrestled with ways to address stigma related to homosexuality and sex work. But one man raised a question he had about those who come out as gay: “Why would you want to be socially abhorrent and make yourself an outcast?” While there have been numerous efforts to reduce HIV-related stigma in health care settings, it persists globally and across the Caribbean region. A baseline survey of HIV-related stigma in St. Kitts and Nevis found that despite antidiscrimination policies in place and training provided, a significant percentage of health care workers held stigmatizing views of people living with HIV and other vulnerable groups (National AIDS Programme et al. 2013). The stigma in health care created a specific challenge in recruiting research teams for the CVC study. While the health care workers seminar continued, John and Henna sat at a hotel cafe and puzzled over how to recruit and put in place research teams that could win the trust of key populations. They mulled over their options: should they hire enumerators who were health care workers who might turn off the population with their potentially stigmatizing views? Or hire less80

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educated community workers who have the trust of the population but lack training to do reliable research? “How about medical students?” Henna suggested, thinking of St. George’s University, down the island. John shook his head. Meanwhile, the ethics review board approvals were moving slowly in most countries, where they met rarely as a rule, and now were being asked by CVC to approve new research approaches and concepts for a politically sensitive project. One way or another, John and Henna had to pick up the pace. “There are external forces pushing us,” like the Global Fund, said John. “We’re already late, and the Principal Recipient is putting huge pressure on us. We run the risk of losing the grant if we don’t push forward.” However, Henna pointed out, they could not hire researchers or book plane tickets – getting more expensive day by day – without the review board approvals. It was beginning to become clear why there had never been key population size estimates before. For John, the solution to the problem of recruitment, and to all the methodological problems, was to have the buy-in and active participation of community-based key populations-led organizations, and to invest in training them to do the research, building their capacity for the long term. But as we began to meet with civil society organizations, we encountered a fourth challenge: each one raised the harm caused when US funding for the one initiative to reach key populations in Grenada, CHAA, was abruptly terminated. From the formative interview participants, we heard of a once-thriving gay bar now shuttered, of house parties gone underground. Jeannine at Planned Parenthood said work on HIV in the community had been difficult since CHAA and Population Services International had both left. She described the “roller coaster ride” of providing sexual health information to youth, when programs first scaled up and then abruptly ended. Having been burned by this abrupt abandonment, some organizations were hesitant to leap into the CVC study. The shutdown of CHAA exemplified a larger global trend: the trend toward donor transitions out of middle-income countries. This was happening across many donors in the name of maximizing value for money, and on decisions sometimes made on the basis of just one or two numerical indicators. * Funding from the United States, the Global Fund, and the World Bank has, until now, largely financed the Caribbean HIV response (Farmer 81

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2005). However, in recent years, the US bilateral investment has fluctuated sharply thanks to abrupt changes of strategy (see Figure 3.2). These changes, which were small shifts from the perspective of billions of dollars of global HIV financing, had a dramatic impact on the landscape of the HIV response. Several years later, people were still talking about it; it was still a factor affecting the CVC study in Grenada. As the two largest donors to HIV programming, the Global Fund and PEPFAR often try to harmonize, covering complementary programs. In this region, while the Global Fund shouldered the responsibility for funding antiretroviral treatment, PEPFAR focused on key populations. Among other projects, it financed an international organization to strengthen peer outreach to key populations. The International HIV/AIDS Alliance (recently rebranded as Frontline AIDS) is a British international organization founded in 1993, with strong donor support, to encourage the emergence of community groups as part of the global HIV response. In most countries where it works, the Alliance (as it was known then) works through a local civil society organization. Finding none in the Caribbean that fit their criteria, they instead established a regional office in Trinidad which they called the Caribbean HIV/AIDS Alliance (CHAA). The plan was to eventually establish this office as a self-sustaining and independent NGO. PEPFAR invested in CHAA, while it was also planning a gradual transition out of the Caribbean. The agency’s 2013 regional operational plan says, “[A] key activity with . . . 2013 and 2014 funds, will be the development of ‘Sustainability Plans’ in conjunction with governments, civil society and other donors . . . [to] include priorities for the

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region and specific countries; benchmarks for phasing down in some countries while rationalizing continued resource allocations in others” (PEPFAR 2014, 5). Thus, both the donor and the Alliance planned to establish a new institution, or set of local institutions, that would become indigenously led and financed, after a gradual, phased withdrawal. The idea was to “build the capacity of key population and civil society organizations to become more sustainable and actively engage in policy dialogue and resource decision making,” preferably over about a 6-year period ending in 2019 (PEPFAR 2014, 13). These plans changed overnight. In 2014, Bennet Charles was a CHAA program officer in St. Lucia. He recalled: It happened over a weekend. On a Wednesday or a Thursday we were told that we had to have everything packed by the following Monday. There had been no notice of closure to the country staff, it just ended abruptly. . . . There was no opportunity to transition. . . . We spent the weekend boxing up [all the data]. After we shipped it all off to Trinidad, the next day, access to the regional database was shut down.

CHAA insisted that all programmatic data on key populations must be sent back to the headquarters. There was no explanation, said Charles: “There was never a regional meeting, never any sit-down with staff. [Regional organizations] could maybe say why it closed, but the islands never got an answer. Our jobs were over from one day to the next.” HIV testing for key populations on St. Lucia ground stopped. “There was a huge gap. It really was traumatic.” What had happened? PEPFAR had “pivoted” to invest more of its increasingly constrained resources in larger countries with high HIV prevalence: the push to reach the end of AIDS was forcing the agency to prioritize, and it was prioritizing large populations of people living with HIV. In a 2016 presentation titled “Having the Courage of Our Convictions,” PEPFAR technical staff argue that their new approach, PEPFAR 3.0, would respond to the plateau of financing for HIV by “optimiz[ing] efficiencies and maximiz[ing] impact,” the language of cost-effectiveness. Dereck Springer, at the regional coordinating agency PANCAP, recalled, “The formula Ambassador Birx chose was to look at whether you were getting the best bang for the buck in terms of investment. When they looked at the Eastern Caribbean they realized they were placing a significant amount of money, but yields in terms of key populations, numbers being tested, those yields were small.” Moreover, in a region 83

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where the costs of travel and goods are exorbitant and inflation rages, the cost of reaching one or two thousand people was probably higher than it would have been within a single large low-income country. A senior US official working with PEPFAR described in our interview how this worked in Washington: All the country teams were asked to come in with their historical data of where they were working with people living with HIV [PLHIV], regardless of whether it was a generalized epidemic in South Africa, or a concentrated epidemic. They were brought in and ranked. [PEPFAR] took a look at facilities across the countries, took the numbers of people already in treatment, looked at where we could get the biggest number on treatment, and chose our provinces and sites. Basically, [PEPFAR] ranked [countries] 1 to 10. We didn’t have good size estimates or even prevalence estimates for all populations. We were doing it based on the estimated number of PLHIV. So we went 1 to 10 on PLHIV and population density. We were going where the epidemic was.

To be more precise, PEPFAR was going where the epidemic was measured: where there was no data on people living with HIV, the absence of data was treated as a zero. This extremely simple approach to eligibility – more simplistic than the Global Fund’s Eligibility Policy – may have been in part a move aimed at making the resulting impact of PEPFAR investment easier to report to Congress. Congressional representatives who authorized PEPFAR’s budget might be more easily impressed by an absolute number of people on treatment, than by a harder-to-communicate combination of indicators. I shared this rationale with Bennet in a text message. He texted back, “So we actually need more PLHIVs . . . hmm.” A straightforward ranking system based on numbers of PLHIV was never going to favor small island countries with large data gaps. PEPFAR decided to end funding for the Eastern Caribbean, but to continue supporting a regional coordination mechanism. That year, PEPFAR’s investment in HIV prevention in the Caribbean plummeted from over $7 million in 2013 to just over $1 million. The difficulties, the cost, and the low yield of returns had all proven too much; PEPFAR’s earlier, gradual transition plan for the Caribbean was set aside. In 2015, funding for the Caribbean increased again, but with a new strategy that focused on the largest islands in the region with the highest numbers of PLHIV, not in community-led outreach in smaller 84

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countries. Then, in 2017, PEPFAR changed priorities again, concentrating funding even further. Said Springer: Prevalence in the Caribbean, in terms of the general population, it’s not that high compared to countries on the African continent. . . . If PEPFAR was to continue to support the Caribbean, they would have to place most of the funding for Eastern and Southern Caribbean . . . in Jamaica. When you look at the epidemiology, Jamaica had the highest burden in regards to [men who have sex with men], but didn’t have as many persons on treatment.

For the first year of the new two-year Regional Operating Plan, he recalled, PEPFAR would cut the regional budget by 10 percent, and reallocate 67 percent of the regional resources to Jamaica; in year two, 76 percent of the regional funding would go to Jamaica. This would slash resources available for other countries in the region. PEPFAR warned, furthermore, that if Jamaica failed to meet strict new numerical targets for getting key populations on treatment, funding would be cut for Jamaica as well (Antillean Media Group 2017). This created stress on Caribbean implementers, Springer remembered, “On the one hand, we had the Global Fund preparing to transition. On the other hand . . . we had just gotten countries to commit to Treat All, and now committing countries to move to [Pre-Exposure Prophylaxis, or PrEP], and now [we were] saying, ‘Graduation is going to happen quicker than you expected.’” In a briefing for a regional meeting of heads of government, Springer wrote that while funding for Jamaica would increase and Haiti’s would continue: “Funding for the Bahamas will cease as at 30th September 2017. Funding for Barbados will cease as at 30th September 2018 and Guyana, Suriname and Trinidad and Tobago will receive reduced funding” (Springer 2017). In early 2019 Ambassador Birx’s assessment of Jamaica’s performance was poor: “The Caribbean is underperforming, mainly due to ineffective program implementation in Jamaica. Jamaica is the driver of the region’s underperformance” (Birx 2019, 4). Jamaica’s failure to meet targets, especially for treatment adherence overall and for reaching key populations, meant that despite getting the bulk of funds that had been cut from other countries, Jamaica had still “fallen behind,” she said (ibid.). Thus, instead of getting the planned 76 percent of regional funding, Jamaica faced reductions in 2019 (Birx 2019, 6). In a region where external aid funds most of the response to HIV, these abrupt shifts in policy, even when small in terms of absolute 85

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numbers, can radically reshape the landscape. In the Eastern Caribbean, one consequence was that some community-based organizations serving key populations shut their doors. They were left without the data they had helped create, which it turned out did not belong to them, or to any local institution, but belonged to the donors. Their hard-won community networks, built among hidden populations, proved difficult to maintain without funding. The loss of the programmatic data from CHAA, while it would have never substituted for national size estimates or other HIV studies, was still a blow. It meant that local groups were now both operating without funding, and as Peter Sands had put it in another context, they were flying blind, with no data. The hidden populations whose trust these groups had worked hard to gain did not cease to exist, of course, but they slipped away from view, reabsorbed back into double lives and coded messages. Men on the down-low and sex workers in Grenada did not know that priorities had shifted in the global HIV response, and that several more lives were being saved in an African country: all they knew was that one moment there were people offering some minimal services; and the next moment, those people had stopped. Anyone seeking to win their trust again in the future would have to work twice as hard. This made the Global Fund’s support for key population size estimates in the Eastern Caribbean even more important than in the past; other donors had transitioned out, while the Fund held on and even increased funding in the region (see Figure 3.3). However, the clock was clearly ticking: some on the Global Fund Board were arguing that the provision for small islands like Grenada might need to be cut, so that funds could be prioritized for the push to end AIDS in high-prevalence countries. All the more critical, then, for 20,00,00,00,000 15,00,00,00,000 10,00,00,00,000 5,00,00,00,000 –

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Figure 3.3 Global Fund HIV disbursements in the Caribbean, 2010–17

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John and his colleagues to seize the opportunity to get data on key populations while funding still existed to do it. * The driver of our minivan taxi was a polished professional, moving his van smoothly around Grenada’s hairpin bends, air conditioning at full blast. John, in the front seat, tried to strike up a conversation. “We’re here to study sex workers,” he said. “Do you know where we could find them?” The driver muttered, “I don’t know nothing about that.” There was no red-light district in Grenada, that we had been able to find. The area around Grand Anse Beach is quiet and low-key. There were a couple of bars on the beach, but they were fairly staid, the kinds of spots where local professionals go for lunch, and where medical students grab a cocktail and burger to celebrate finishing exams. They closed early. John and I had been scouring the island looking for sex workers, and unusually, not a single taxi driver seemed to have a clue – or was willing to admit to having one. We were on our way to meet GrenCHAP. I had read a little bit about them online, though information was sparse, and most of it had to do with the failed constitutional reform vote just a few months earlier. In late 2016, Grenada held a referendum on reform of the constitution. The proposed seven amendments included one that would have swept away a last remnant of colonialism, replacing the UK Privy Council as Grenada’s final court of appeals with the Caribbean Court of Justice (UNDP 2017; Now Grenada 2016). The referendum vote, initially scheduled for October 27, was postponed a month over controversy around whether one of the provisions on gender equality would open the door to recognition of same-sex marriage (Jamaica Observer 2016). In fact, GrenCHAP and other advocates had lobbied for nondiscrimination based on sexual orientation and gender identity, not for marriage equality, but the nondiscrimination proposal never made it onto the ballot (Maitland 2015). Amid public confusion and homophobic anxiety, the country voted no, and the Privy Council stayed in place as the final court of appeals. In January 2017, this all still rankled. We arrived at GrenCHAP, a small one-room office with a couple of desks near a basketball court. GrenCHAP had no paid staff, only volunteers with other full-time jobs, so the office was opened up just for our meeting. Nigel Mathlin, one of the founders and former executive director, had stepped away from the grind of running an NGO to start a media firm. Kerlin Charles, the incoming executive director, 87

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wore multiple hats, including chairing a national coalition, GrenAIDS, to enable some coordination in the gap left by the recent collapse of Grenada’s National AIDS Committee. A young staffer, who preferred to be called Mr. B in this book, was also on hand as a key volunteer. All three of GrenCHAP’s leaders were in their twenties or thirties. While we waited for Nigel, who was stuck in traffic, we spoke about the laws criminalizing same-sex sexuality and sex work. Kerlin and Mr. B explained that even when the laws were not enforced, they legitimized homophobia and discrimination, and shaped the environment that made people reluctant to be identified. Mr. B said that many Grenadian men who have sex with men “think that homosexuality is against the law, when in fact it’s anal sex. To them, it’s the whole person who is criminalized.” Nigel arrived. In a room darkening as the sun set, with the basketball game echoing in the street, John leaned forward on his metal folding chair to make the pitch. Why do this study? John mentioned my research on punitive laws, arguing that when size estimates for sex workers and men who have sex with men are done by the government without the help of civil society, key populations are usually underestimated: “[The government] make ridiculous claims that 90 percent have been reached. . . . Bad size estimation studies allow the government to say that everything is great – they’re dangerous. . . . We want to do this through the communities.” Nigel listened, but he was openly skeptical. In the past, he remembered, GrenCHAP experienced researchers coming in, doing studies, and leaving with the data, without ever sharing any reports or results. “We’ve had no data for a few years: CHAA closed out and they passed on nothing,” he said. Big donors and the Ministry of Health asked for size estimates to satisfy external donors, but while the community was key to producing the data, the money that data leveraged never reached GrenCHAP: “In terms of financial and technical support, it’s zero. We have individual allies [in the government], but our organization is not acknowledged officially.” So why should GrenCHAP spend their limited time on producing data that would not benefit them? He argued that size estimation studies done on other islands would produce estimates that could just as well apply to Grenada. John acknowledged Nigel’s views, but he responded that population size estimates could deliver something unique in Grenada: profoundly local information, the characterization of subpopulations. He talked about how he had seen this happen in a study he did in the Dominican 88

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Republic: “We’ve been able to identify small subgroups who are highly vulnerable, and design targeted interventions that changed their reality. For example, we had a case with fifteen- to seventeen-year-olds who were being left alone. They were gay and living with HIV, but not getting tested. We were able to get those kids on treatment.” He cited another example from Haiti, where a study done with communities was able to reach down-low men who had not been reached any other way. The GrenCHAP group absorbed this. Mr. B raised the question of how security and anonymity would be preserved for study participants. John answered that in the past, health ministries had demanded that CVC’s data be turned over to them, and “we declined. We want to do something different. We need to focus on organizations on the ground. It’s difficult as we know people have been burned so many times. We won’t come in [here] and do the study just for the sake of doing the study.” He acknowledged that the question of who owns the data is an important one. He said that CVC was committed to protecting security and ensuring community ownership. Kerlin Charles warned how difficult it would be to do this study after several years of little funding for programmatic outreach. When GrenCHAP organized occasional socials, they would get forty people or so, but then, said Kerlin, “everyone disappears,” melting back into their down-low lives. The government was not reaching out to key populations, agreed Mr. B. “We are starting from scratch in terms of the capacity of this organization.” He said that to make this study work, he would need to win over gatekeepers in specific cliques. To do that, GrenCHAP need funding to develop an active social schedule: parties, hikes, boat trips, movie nights. John took this seriously. He fully grasped the importance of gradually building up frayed community networks again, through a series of social activities. He promised that as a partner in the study, GrenCHAP would have access to small amounts of funding for events. The group was moving toward an agreement to partner together on the study. As the meeting wound up, Nigel underscored, “I’m adamant that there should be something useful for the community [as a result of this study]. Not just data.” John agreed. Cautiously, they moved onto next steps: John would share a draft protocol for their review. GrenCHAP would send a participant to a protocol standardization workshop in Saint Kitts later in the month: maybe Mr. B, who seemed the most interested. 89

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We left with hugs in the dusk, beside the now-empty basketball court. We were good to go. But the picture John painted in the taxi afterward was of a fractured community, with no shared meeting ground, dormant networks: “I’m a little bit concerned that we can pull the networks together quickly to do this. It’s much easier to do this kind of exercise when you’ve got NGOs that are strong and active in the field.” Was Grenada unique, in his experience? “Yes and no.” Each island in the region had different dynamics, he said. But in each there are these periodic retreats and advances – “some bars, social venues, tend to kind of disappear in one place and pop up elsewhere.” Grenada would be one of the toughest countries in which to do the research, not because the environment was dangerous, but because in the wake of the abrupt withdrawal of US funding, there had been no outreach to key populations for years. “Everything needs to be started again.” * While expectations mounted on what could come out of the study, the risks that formed the data paradox in Grenada were real: denial led to lack of data, which reinforced denial, because people felt they had to lead double lives. When I interviewed Kerlin Charles a few months after that meeting in GrenCHAP’s office, she said the research offered the opportunity to push back on those in the government who denied the existence of men who have sex with men: “We can use the data to help repeal the buggery law. Next time we have a referendum, we can use the data. It will be great for advocacy work in our country. If the government say we don’t have gay people, we can say: here.” But she noted that with that opportunity came the risk that the government would attack the credibility of the size estimate: “It would threaten the status quo of the country” to be able to prove there are men who have sex with men and local sex workers in Grenada: “I don’t want someone in the government to say this is manufactured data. This process really has to be black and white.” Mr. B agreed, “We will get a pushback from the general population. [We] need to be prepared for that.” Julia Hasbún agreed that the research could be maligned as being an agenda of the global north: “The gringoes are coming,” she joked. Similarly, Kizzy, a longtime activist working with sex workers in Grenada, expressed concern, “People are in denial. They will never believe there are men who have sex with men and sex workers. They will ask, where the money is coming from to finance this?” 90

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Dr. Francis Martin, the senior medical officer in Grenada, was new to working on HIV, but very alive to the risks in his dealings with his colleagues and supervisors in the Ministry of Health. From the outset, John had involved government officials in the meetings and planning, hoping to build alliances between civil society and their government counterparts, to build a real and lasting community of practice. In some contexts, this led to flareups between activists and government officials. But in Grenada, he found an early ally in this doctor, who spoke frankly: Because the national program’s ability to reach those populations in the past has failed miserably, hence the incidence and prevalence trends we’re seeing today. The only hope the Ministry of Health has is to truly support civil society and involve them in the process. We really need to foster the relationship . . . [this is] the only window we have right now.

Dr. Martin said he was looking forward to being able to rely on “hard scientific facts.” He also wanted to see better coordination between the Ministry of Health and civil society in Grenada, because at the moment, as Nigel had also said, there was no partnership in place. “The Ministry of Health is kind of ad-hoc-ly hoping the civil society organizations are doing something.” To change this, he would need to overcome some resistance to change among older officials: “The present generation is not going to give us the change we need” in laws and policies. But like the others in civil society, he also was alive to the risks: “If the information comes out in a way where we have a problem with change management . . . it could drive key populations further underground, if they feel targeted.” This risk had surfaced during the long ethics review process in Grenada, when some of his colleagues had really been forced to digest new concepts. To mitigate the risk, he did a Cabinet Mention to brief Grenada’s leaders about the proposed study, “because of the scale of what was anticipated, and the population involved, especially because there are legal implications around key populations.” He said the Cabinet understood that “we have inherited a colonial system and laws that don’t reflect the current situation. The government was willing to step aside and let things take a natural course.” In that sense, then, perhaps the failed referendum had helped to spark a public conversation that could gradually lead to a more inclusive society. But it was still unclear how the public would respond once 91

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the size estimates were published in black and white, contradicting the popular view that Grenadian men who have sex with men and sex workers did not – in the view of some, should not – exist. * We have moved not very far from the start of this chapter – just a few miles down the road from the tiny community organization offices cached in the hills of St. George’s, past the glittering yachts in the marina, to the somewhat battered halls of the Ministry of Health. More than miles separate these two spaces, though; a history of power and finance has worn deep rifts into this landscape. Grenada and other small island countries in the Eastern Caribbean have lived for centuries in the shadow of larger powers that have abruptly, sometimes violently, shaped national politics and economy; and that have also offered life-saving aid. Over its history, the interventions and demands of those countries have shaped many aspects of public and private life. In recent years, the regional HIV response built in large part with foreign aid has struggled to sustain itself as donors began to transition out, rationing global finance for larger countries with lower costs and more people living with HIV. The sometimes abrupt processes of transition have been especially hard on key populations, who lack other sources of funding. Their trust and networks were fragile and in some cases collapsed when foreign aid withdrew, taking the data with it. The impact of aid eligibility, decided based on indicators at the global level, was made visible in Grenada’s low HIV testing numbers and in the darkened ground-floor offices of GrenCHAP. For the CVC study, gathering data on hidden key populations went hand in hand with local efforts to restart abandoned programs and networks. For those Grenadian activists, data-gathering needed to produce not just data, but something more than data: new social ties, new infrastructure, new hope, empowered and visible community leaders. The act of counting key populations thus became not just a process of counting people, but a means to mobilize them, to convene diverse social forces, and to reveal hidden truths. As later chapters will show, with increasing trust came visibility, and with visibility gradually came more empowered and resilient organizations that could serve and speak for hidden communities. Dr. Martin certainly hoped the data would shine a light on the task before him. “We’ve been blinded in terms of what programs, numbers, quantity, and quality of programs” Grenada needed, he said. He would wait to see the results of the CVC study to know for sure, but admitted 92

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at the outset, “I’m not satisfied that priorities have been where they should be” in the national budget. The CVC study “could not have come at a better time.” Grenada was just beginning to put new systems in place to more efficiently and effectively manage its limited resources for health, he said, including a new national health insurance scheme. He and his colleagues were identifying a basket of services that would be covered by this scheme, creating electronic medical records, and building a district health information system. As part of this slow, hard work of health system strengthening, Dr. Martin and his colleagues were starting to cost out services, and once that was done, they would do a cost-effectiveness analysis, an exercise that would be “absolutely essential.” Personally, he believed that Grenada would need to invest more than it had in the past in programs to reach key populations. But he admitted, with a rueful smile, “There’s always going to be a fight for prioritization.”

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The fight for prioritization in health finance, mentioned by Dr. Martin in Grenada, has only become more fierce in recent years due to the race to reach the end of AIDS with reduced funds. This pressure has been managed through the rising dominance of discourses and tools grounded in cost-effectiveness. These tools and concepts can be a double-edged sword for marginalized communities and interventions: while they can be used to make a case for investment in key populations, they can also be used to reinforce forms of epistemological exclusion based on lack of quantitative data. In addition, cost-effectiveness is sometimes used to exclude other values. In this and the next chapter, we leave behind Grenada in order to dive into what some may consider the belly of the beast – the machinery behind the drive for data. Increasingly, as noted in Chapter 1, the pressure on donors to demonstrate results – in the face of diminishing public enthusiasm for financing the HIV response – has been passed on from the global to the country level. National HIV programs are increasingly required by donors and global health agencies to write investment cases that analyze epidemiological data and set out strategic plans for how countries will invest their finances. These are, developed using cost-effectiveness analysis software. In writing these investment cases, officials may confront a map full of hotspots, with not enough water to put out all the fires: they have an epidemic that affects numerous vulnerable groups and now face wrenching questions of prioritization – questions that will only grow, presenting starker choices, as donors continue to transition out. 94

MAKING A CASE FOR HUMAN RIGHTS BASED ON COST-EFFECTIVENESS

This chapter begins by exploring the rise of cost-effectiveness and investment cases in health financing, then explores how costeffectiveness analysis has been used to construct these cases, and examines some cost-effectiveness software used in HIV finance with a critical lens. We then explore how cost-effectiveness analyses play out for key populations in some national investment cases and examine whether human rights norms offer alternative principles of decisionmaking. MAKING A CASE FOR HUMAN RIGHTS BASED ON COST-EFFECTIVENESS

From 2012 to the present, cost-effectiveness as a discourse and frame for prioritization in global health finance quickly rose to prominence. This means that anyone engaged in developing HIV finance plans, whether at the global or the country level, has increasingly needed cost-effectiveness evidence in order to make the case for financing any intervention; these interventions need to work in the model of the market. I encountered this while working at the Global Fund. As I prepared to leave the institution in 2015, I held a hand-over meeting of the Global Fund Human Rights Reference Group, an external advisory group, to review progress and plans. We had achieved a number of measures that are discussed more fully in other articles (Davis 2014, 2015), including the establishment of minimum human rights standards for all funded programs and the option for countries to request funding for programs to address human rights in national HIV, TB, and malaria programs – such as know-your-rights training for community groups, legal aid services, or law reform projects, to name a few. However, on this occasion, a manager from Finance updated the Reference Group on numbers that confirmed our worst suspicions: that most countries did not ask for funding to do this work (Davis 2014, 2015). As the group brainstormed ways to negotiate with, persuade, or incentivize countries to include human rights interventions in their HIV and TB funding requests, the Finance manager asked, “Do you have any evidence that these human rights programs of yours are costeffective?” The group stared at him blankly as he specified, “You know, evidence that these programs have an impact on health that justifies the expenditures?” 95

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The group of human rights experts exploded: “You don’t use costeffectiveness to justify funding human rights programming! You fund it because it’s the right thing to do!” But I wrote cost effectiveness? in my notebook and then spent months pursuing this particular white whale, reflecting on whether cost-effectiveness tools help implement or undermine international human rights standards. As discussed in the following analysis, the tools seem to do either, depending on the context. In the best cases, concepts such as allocative efficiency support health planners in making rational choices that prioritize populations based on HIV prevalence and risk. But a focus on economic evaluation grounded in data on quantifiable populations can also sometimes undermine equity because, as we have seen, some populations are small, some only appear small because they are hiding, and many are not easy to count. Over a period of about a decade, as global resources for HIV became more volatile and leveled off, and pressure increased to demonstrate that the billions spent on the HIV response had an impact, the leading donors financing global health began to shift toward an approach in which the donor exercised greater agency to view the epidemiological landscape as an investor with a strategy, selecting where donors would prioritize their investments. The investment tool was adapted from the private sector to support this changing power dynamic. The next section explores the rise of investment cases and the role that costeffectiveness tools play in developing them. THE RISE OF THE INVESTMENT CASE

The investment case is a tool first developed in private sector in the early 2000s, before the 2008 economic crash. The early 2000s were a period of feverish increase of mergers and acquisitions; in response, some business analysts began urging investors to create investment cases in order to assess the specific need or problem they aimed to solve, the relevant market opportunity, and what the corporation the investor would acquire offered that uniquely positioned it to solve the given problem. In promoting these new tools, consultants urged businesses to place an “emphasis on tangible and quantifiable results” (Harding and Rovit 2004) – for example, projected earnings within a defined time period. In a major article that was the first to apply this investment approach to HIV resource allocation, Schwartländer and colleagues (2011) made 96

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the case for what they termed a “strategic investment framework” in HIV. To fit each country’s context, they argued, national health planners should mimic investment thinking and be more strategic: use epidemiological data to identify the specific problems in the country’s HIV epidemic and then design the appropriate combination of activities to fit their response, producing quantifiable results. They recommended the investment approach include both biomedical interventions such as treatment and prevention, along with “critical enablers” – programs to mobilize communities and advocate for law and policy change (Schwartländer et al. 2011, 2032). This landmark article, coming in the wake of the global financial crash, decisively influenced UN agencies and donors. Schwartländer is now chef de cabinet at WHO, but at the time he was a senior manager at UNAIDS, and the agency began to actively promote the Strategic Investment Framework. UNAIDS published a strategic investment guidance document that drew on Schwartländer’s article to set out a four-step process through which health planners could “zero in on core activities” to have “maximum impact” on the epidemic: 1. 2. 3. 4.

Know the problem. Design the investment portfolio to solve the problem. Apply the investment portfolio at scale and generate efficiency. Sustain for impact and ending AIDS. (UNAIDS 2012, 6)

UNAIDS worked closely with the Global Fund to roll out the strategic investment approach. The Fund had recently gone through a major restructuring process, changing from an approach in which applicants competed for funding based on the strength of their proposals to an allocation approach where each eligible applicant was guaranteed a sum; the investment approach helped structure this new approach to engagement with aid-recipient countries. The Global Fund began to encourage applicants to base their funding requests on national strategies or, where these did not exist, to draw on technical support provided by the UN or by bilateral technical assistance programs to create investment cases that analyzed “optimal allocation of existing resources, and a prioritized scale-up plan to reach national disease control goals” as part of national funding requests (The Global Fund 2017c, 3). The Fund stressed that while technical assistance might be used to develop these investment cases, they were to be “country-owned” and “country-developed” (The Global Fund 2017c, 3). An explicitly 97

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prescriptive approach would have sparked resistance from some countries insistent on their sovereignty, so investment cases became “a vitally important advocacy tool” for persuading countries to take a more strategic approach to planning resource allocation (UNESCAP 2016, 36). As then Global Fund executive director Mark Dybul put it in a lecture, responding to HIV had become “a numbers game”: “There is no such thing as a global HIV epidemic. There never was. . . . The only way [to respond] is to look at each epidemic, understand each epidemic, and then respond to each epidemic in the way that is most likely to be effective, based on the data which are available” (Dybul 2017, 3). As countries began to develop investment cases, Global Fund Board donor and partner agencies, such as the World Bank, deployed experts to provide technical assistance to countries preparing their funding requests (World Bank 2013). They often did this through country visits in which donors, UN agencies, and international consultants made the case to national health officials for the priorities that global health had collectively identified, such as scaling up treatment access, financing prevention for key populations, and finding efficiencies in health systems, for example – including priorities set in the Global Fund’s corporate KPIs. Thus the use of infectious disease models, the implementation of cost-effectiveness software, and the development of investment cases has rapidly become a technocratic project done behind closed doors, with external technical advisors or consultants leading the discussion. However, the processes underway resembled a rationing of public services, creating what Biehl called “a state of triage and politics of survival” (2007, 1083). COST-EFFECTIVENESS ANALYSIS AS A TOOL IN INVESTMENT CASES

Health economics developed specifically in order to facilitate these kinds of choices. The field first emerged in the mid-twentieth century (Jakovjlevic and Ogura 2016; Mushkin 1958). The underlying premise of health economics is that financial resources for health are limited and health officials bear the responsibility to optimize collective resources and ensure the greatest benefit to the collective population (Carrin 2011; Jack 1999). 98

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In cost-effectiveness analysis, using data about the costs and the health outcomes of each service, a health official (or the consultant advising her or him) uses mathematical models that generate and compare future scenarios using different health interventions. This may include an analysis of allocative efficiency – which populations or interventions the health official might focus on in order to obtain the highest impact for the lowest expense. The impact is usually measured in metrics that represent years of life lost to ill health or mortality. By reviewing these different future scenarios, the health official selects the course of action that delivers maximum health impacts within a fixed budget. As Aldo Yazbeck notes in his introductory guide to costeffectiveness, this approach always requires “some form of rationing”: “Any way you cut it . . . developing a benefits package will produce winners and losers, especially in poor countries with large populations and small budgets for health. Losers in this context are the group of people that inevitably will get less, in terms of benefits or services, than others” (Yazbeck 2002, 7–8). Yazbeck is Lead Health Economist at the World Bank, and his phrasing, echoed in other health economics texts, exemplifies neoliberalism as articulated by Wendy Brown (2014). While “neoliberalism” is a term frequently used to describe multiple different phenomena, Brown argues it “is best understood not simply as economic policy, but as a governing rationality that disseminates market values and metrics to every sphere of life and construes the human self purely as homo oeconomicus” (Brown 2014, 176). The result, she says, is to shift responsibility from states to individuals, who must compete in a world no longer premised on equality but divided between winners and losers: “both persons and states are constructed on the model of the contemporary firm, both persons and states are expected to comport themselves in ways that maximize their capital value in the present and enhance their future value” (Brown 2014, 22). In the model of the market, the human body is an asset and health is an investment justified by producing additional economically productive life years, which lead to higher national income (Musgrove 2004, 2–6). Along these lines, Kenworthy noted in Lesotho that neoliberal rationales underscored national campaigns to combat HIV that focused on the responsibilities of individuals to change their behavior to prevent transmission, without considering the structural factors and political inequalities driving transmission (2017). 99

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By adopting tools from the private sector, such as investment cases, and developing tools that explicitly build investment cases on costeffectiveness analysis, the global HIV response has gradually reshaped itself to align with the model of the market. Thus this chapter argues that the cost-effectiveness analysis tools are one small but important expression of a larger trend identified by Sparke (2018, 2019), Adams (2016), Jenson (2010), Mawdsely (2018), and others toward financialization of development assistance; this is one instance of the way that global health has increasingly “rationed and targeted life-saving investment” (Sparke 2019, 1). In her 2016 chapter on the rise of metrics in global health, Adams makes a related argument about the economic rationale for metrics used in global health, which skews too far toward the role of the private sector based in part on a misunderstanding of the Global Fund’s business model. Adams argues that the shift toward the use of metrics and indicators in global health governance represents “a trend more simply toward the market overall” (2016, 23). She points to the Fund as an example of this, arguing that “making profits on health investments is part of the modus operandi of the institution” (2016, 42). The mistaken statement that the Fund earns profits appears to be based largely on a 2010 Global Fund press release announcing the launch of a co-branded index with S&P Dow Jones Indices. The Global Fund’s communications director, Seth Faison, confirmed in an email on August 23, 2019, that the index never came to fruition. As a Swiss foundation, the Global Fund cannot earn profits. The Board periodically reviews available funding and may approve additional expenditures on a case-by-case basis (The Global Fund 2019a). Any analysis of the Fund’s complicated relationships with the private sector would need to also take into account both its piloting of Wambo, an online procurement tool for commodities used by grant recipients, and the role of its Market Shaping Strategy in lowering prices of health commodities and services (The Global Fund 2015a). However, Adams’s argument is helpful in pointing out how quantification contributes to the culture of economic values that shape decision-making in global health finance agencies. Rather than embracing profit-making enterprises for themselves, I would suggest that all global health donors have moved toward embracing the model of the market: donors are investors, countries and populations must position themselves to compete for investment, and success is communicated publicly in numbers of “lives saved.” 100

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Brown argues that the shift toward the model of the market undermines a political system predicated on equal rights: “A democracy composed of human capital features winners and losers, not equal treatment or equal protection” (Brown 2015, 38). In the context of HIV, it should not be surprising if “losers” often turn out to be those who have always lost before due to historical discrimination, criminalization, and official denialism. As the designers of the tools do not appear to have factored in these unquantified realities, prioritization using cost-effectiveness tools can sometimes perpetuate indirect forms of discrimination. The next section explores some HIV cost-effectiveness tools with a critical lens and shows how these have been used to shape investment cases in three examples, before turning to consider whether human rights norms offer any alternative principles in allocating limited funds for health. AN EXAMINATION OF HIV COST-EFFECTIVENESS TOOLS

As part of their approach to providing technical assistance, UN agencies and donors have developed several software tools for costeffectiveness analysis. Briefly, here is an overview to how they work, followed by some reflection on how HIV cost-effectiveness tools steer users to prioritize among populations. In using the software, health planners, often with support from international consultants with expertise on the software, input national budget parameters, and national strategic targets such as for HIV incidence, for example. The software then uses data on the cost of various interventions, combined with national data on HIV among various subpopulations, and epidemiological data on HIV transmission rates, as well as data on the impact of different interventions, to predict the future rate of HIV infections that would result with different combinations of interventions within the budget parameters. Users can visually compare and contrast these scenarios, in order to clarify the choices they must make. Two examples of this are the GOALS software and Optima, though there are several others. GOALS was developed by Avenir Health with funding from USAID, and is part of the Spectrum suite of health policy software (Avenir Health 2019). National health planners use Spectrum policy models for a variety of health planning purposes, including to forecast 101

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demographic changes, estimate needs for family planning, for tuberculosis programs, and to report data to UNAIDS. GOALS assists those planners in estimating the amounts of funding needed to achieve goals set in national strategies for HIV, tuberculosis, sexually transmitted infections (STIs), and noncommunicable diseases, in order to “understand how funding levels and patterns can lead to reductions in HIV incidence and prevalence” (Stover et al. 2003, 3). In order to model the national HIV epidemic, GOALS segments the adult population by sex and risk groups, predicting rates of HIV infection for each group (Futures Institute 2011, 27). The software then displays the effect that could be had on those infection rates by programmatic interventions, such as condom use, pre-exposure prophlylaxis (PrEP), or male circumcision, to pick a few examples (Futures Institue 2011, 30–33). By altering costs and other parameters, users can use GOALS to produce charts to visualize various scenarios (see Figure 4.1). The screenshot in Figure 4.1 is taken from a simplified online version, GOALS Express, used for demonstration purposes (Avenir Health 2019). As the users select interventions, or change national targets or unit costs, they can see epidemic rates vary for population groups such as men who have sex with men, sex workers, or “low-risk heterosexual” populations. These rates are represented by the changing width of the colored bars that represent each subpopulation. In other words, health planners use the tool to prioritize among populations, based on the cost-effectiveness of interventions that would prevent HIV transmission to that group. Optima, developed with support from the World Bank, also assists users to determine “the optimal allocation of HIV resources and coverage levels across programs in specific HIV settings” in a global context of declining international funding for HIV programs in low- and middle-income countries (Optima Consortium for Decision Science [Optima Consortium] 2017, 3). Optima also divides national populations into subgroups, though their groupings differ slightly from those used in GOALS and include geographic region, population type (risk and age-based), HIV infection status, HIV diagnosis status, CD4 count (a CD4 count measures the white blood cells that show how well the immune system is functioning, and a normal CD4 count is between 500 and 1,500), and cascade status (Optima Consortium for Decision Science [Optima Consortium] 2017, 55–56). The groups can be customized based on available data. 102

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Figure 4.1 Screenshot: GOALS Express, Nigeria Credit: Avenir Health

Using epidemiological, demographic, behavioral, clinical, and financial data, Optima generates visual graphs which depict future trends: for instance, depicting the impact of PEPFAR divestment or of the country reaching the 90-90-90 targets. The software then produces optimal allocations of HIV resources across program areas, such as “Female sex worker programs” or “prevention of mother-to-child transmission.” The Optima software can also generate forecasts for health planners of rates of AIDS-related deaths by subpopulation group, with outcomes for each group changing based on which interventions are prioritized. In one case, a team of consultants generated scenarios to inform a Southeast Asian regional health sector strategy that depicted rates of deaths by subpopulation in Indonesia – such as men who have sex with men, transgender people, and others – based on current spending allocations in 2012, and forecasted how these could alter using optimized allocations during 2015–20 (Grantham et al. 2016). The 103

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political context in which this is produced would probably shape decisions among these two scenarios: as noted earlier, in 2019, following a wave of homophobic statements by Indonesian government leaders that began in 2016, Indonesia’s parliament debated a proposed law criminalizing adult consensual same-sex sexual behavior, and one member of parliament called for the death penalty or life in prison to be imposed on LGBT people (Beresford 2018). Other tools, such as OneHealth, estimate cost but do not assess costeffectiveness; they can be used to forecast the resources needed for a combined set of interventions across multiple health areas, helping plan the health sector budget (Avenir Health 2016). Health economics tools like those described above offer users an evidence-based visualization, which can enable a frank discussion about how best to allocated limited resources. However, the tools create these scenarios by selectively focusing on specific elements of the context to display visually: subpopulations based on risk, medical status, and so on. The tools thus construct scenarios that block out or omit the political, legal, and social context in which HIV flourishes. The scenarios modeled by these tools create a highly simplified picture which erases political problems that would shape decisions and health outcomes. This is the first concern to note about the cost-effectiveness tools. The lack of large amounts of quantitative evidence of the impact of those laws on health of course would make it difficult to incorporate them into the visualizations, but not impossible, as discussed in the next chapter. The second concern has to do with the above-mentioned “winners and losers.” GOALS, Optima, and OneHealth list interventions that are also the names of subpopulations (e.g., FSW for interventions targeting female sex workers, MSM for interventions targeting men who have sex with men). While the competition is framed as one between health interventions, in effect the charts visually pits subpopulations against one another in a competition for limited resources, and encourages the selection of winners and losers. When they prioritize one or another intervention, health planners visually see future rates of infection, or rates of death, veer up and down among each subpopulation in response to their choices. They then have to decide who will receive services and who will not, which subpopulations will live, and which may not survive. Interventions for smaller populations are inherently less likely to be cost-effective. This in itself raises 104

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troubling ethical questions that are not explicitly considered in the tools or in the processes that use them. The third problem here is that the visual choices presented to health planners may feed into the data paradox discussed earlier. For key populations, as we have seen, official size estimates are often implausibly low or missing altogether. Interventions focused on very small populations are unlikely to be assessed as cost-effective, and the same is true for those who are actually not small populations, but who appear small because of government denial and failure to gather accurate size estimates. Because cost-effectiveness software does not explicitly address the ways in which criminalization may distort size estimates, the scenarios the software generates may lead health planners to inadvertently de-prioritize criminalized groups that appear smaller or do not appear at all. Furthermore, and most concerning of all, some populations are completely omitted from the list of subpopulations that health planners select in the tools: in particular, prisoners, male sex workers, and transgender people. It is possible for software users to manually add in subpopulation groups, such as male sex workers, prisoners, and transgender people. However, if the country lacks official data about those populations, there is little justification for adding in the groups. The tools thus structurally disfavor populations for whom there is no data, reinforcing historical discrimination, without explicitly addressing the fact that they are likely to be historically deprioritized Some experts I have spoken with argue that male sex workers, at least, can be reached through interventions that target men who have sex with men. In July 2019 I spoke to Paul-Gilbert, program manager at the Global Network of Sex Work Projects, and asked him whether this approach worked in his experience, or whether male sex workers required unique interventions. He said: Male sex workers definitely need different kinds of programming than men who have sex with men. The frequency of sex can be different, the demands in terms of protection can also be different. And in terms of locations, where you plan your service would vary a lot. . . . I’ve seen really good examples of services . . . usually programs and organizations that are led by men who have sex with men who have had experience in sex work.

However, he said, these are rarely funded, and “when these services are not community-led, they are often stigmatizing, or people wouldn’t 105

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make the choice to come out as sex workers. . . . We don’t have further information on this, because there is no data, because there is criminalization and stigmatization that prevents people from saying what they’re doing.” The cost-effectiveness tools also did not explicitly factor in stigma, discrimination, and criminalization: they lack any human rights consideration. OneHealth asks users to conduct a “bottleneck analysis” to adjust coverage targets, but this is subjective, and some health officials may lack awareness or information about, for example, how criminalization affects sex workers. As an illustration of how this lack of human rights sophistication may play out in health economics, an early version of GOALS asked users to rate the “existence of a supportive policy environment” (Stover et al. 2003, 9). However, the World Bank table this manual provides to rank country policy environments gives Senegal as an example of a country with “strong” policy support for the HIV response (ibid.). Senegal has made important progress in the HIV response but criminalizes “unnatural sexual acts,” and in 2008 the arrest of a group of Senegalese HIV peer outreach workers on the basis of their sexual orientation was criticized by the International AIDS Society (Mendos 2019, 363; International AIDS Society 2008). In practice, the tools can be used to advocate for investment in prevention programs for key populations. In conversations with the designers of some of the software tools, they emphasized that equity is a priority in their conversations with national health officials. However, the main purpose of the tools is to focus on health benefit to the general population, and the fact that the options for reaching those goals are shaped by inequitable contexts is set aside for a qualitative discussion, which relies largely on the goodwill of someone in the room and their willingness to raise questions not built into the software. In a context of ambitious goals and global scarcity created by flatlining development assistance budgets, the tools, backed by donors and UN agencies, are encouraging health planners to choose how to allocate resources to ensure maximum progress toward the end of HIV. This is an important consideration in ensuring the reduction of waste and maximizing of resources for health services. As Dudley and colleagues argue, “Failure to use economic evaluation in the decision-making process can itself be unethical, as it may mean that resources are consumed in ways that are ineffective, thus denying others the 106

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opportunity to benefit from help and support” (Dudley, Silove, and Gale 2012, 53). Under the human right to health, states are obligated to dedicate maximum available resources to progressive fulfillment of the right to health. Cost-effectiveness analysis can help states to fulfill this rights-based obligation. But the tools and process in which they are used need to be further developed with reference to structural factors that shape data on key populations, to integrate high-level commitments on human rights and key populations into decision-making tools. THREE SAMPLE INVESTMENT CASES

How do the tools shape resource allocations for populations that have been historically discriminated against? Future research should include a wider review of investment cases to examine this question further. Review of three case studies explores how cost-effectiveness analysis plays out for key populations in Eswatini (the country formerly known as Swaziland), Sudan, and Belarus, and the results are decidedly mixed. The national investment case Eswatini submitted to the Global Fund commendably commits to addressing the needs of female sex workers and young women, who face a crisis with extremely high rates of HIV in the country (see Table 4.1). It also commits to funding community mobilization. The prevention budget for 2017–18 lists allocations for “priority populations,” including youth, female sex workers and their clients, men who have sex with men, and cash transfers (for adolescent girls and young women). However, male sex workers and people who inject drugs have no size estimate, no prevalence data, and no allocation for either year; though injecting drug use is believed to be on the rise in Eswatini, there is no official data on the issue. Transgender people also certainly exist in Eswatini, but are not even listed in the estimated resource needs created using GOALS or in the funding request submitted to the Global Fund in 2017 (see Table 4.1). In Eswatini, cost-effectiveness analysis helps some key populations but contributes to reinforcing discrimination, data gaps, and invisibility for others. Two other examples show mixed results for key populations. In Sudan, in the context of declining funding levels, a World Banksupported allocative efficiency exercise using Optima recommended significant shifts of resource allocations toward some key populations, but not others. 107

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TABLE 4.1 Excerpt from Eswatini 2017 HIV investment case, GOALS estimates in millions, USD

Prevention Priority populations Youth focused interventions Female sex workers and clients Male sex workers and clients Cash transfers Injecting drug users (IDU) IDU harm reduction IDU testing and counseling IDU community outreach and peer education IDU needle and syringe exchange IDU drug substitution Men who have sex with men Community mobilization

2017

2018

18.04

20.39

0.46 0.18 0.00 1.26

0.46 0.18 0.00 3.29

0.00 0.00 0.00 0.00 0.00 0.31 1.99

0.00 0.00 0.00 0.00 0.00 0.35 2.03

In a consultation with Sudanese government officials, aid agencies, and others, UNAIDS and modelers identified ten populations for inclusion in the model, including “female sex workers, their clients, MSM, children, and–disaggregated by sex–youth, adults, and older people” (World Bank 2015, 4). This prioritization was important for those long-discriminated-against populations. Homosexuality is criminalized, and intense backlash has made it a sensitive topic in Sudan (Ghareeb 2011). Cost-effectiveness analysis was here strengthening a case for prioritization of services for men who have sex with men. However, no drug users were included in the model due to lack of data. El Mahi (2018) calls a surge in substance use “the elephant in the room” in Sudan, but says prevention and treatment programs are “meager.” Transgender people and male sex workers are not mentioned in the case study at all. Perhaps those participating in the analytical process felt that making the case for funding for services for men who have sex with men was as much as could be achieved in Sudan at that point in time, and that recognition of the needs of male sex workers or transgender people would be too difficult – or perhaps there was just no data. In assessing how the analysis influenced budget allocations, the World Bank case study notes that allocations for men who have sex 108

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with men and female sex workers increased from 7 percent of the annual budgets for HIV to 29 percent, but notes that a significant allocation for prevention in the general population was retained, though it was not cost-effective (World Bank 2015, 7–8). In a third example, the cost-effectiveness analysis recommended focusing on a disfavored key population, but its recommendations do not appear to have been taken on board by health planners. Belarus has had increasing HIV incidence, and over 25 percent HIV prevalence among people who inject drugs (UNAIDS 2017a). Across Eastern Europe and Central Asia, insufficient resources are dedicated to harm reduction services compared to the need, and Belarus is not an exception to this trend. A 2016 Optima cost-effectiveness analysis for Belarus, supported by UNAIDS, UNDP, the Global Fund, the World Bank, and others, analyzed data on HIV and financial resources, and found that the HIV epidemic was concentrated among people who inject drugs, men who have sex with men, and female sex workers, recommending that they be “the core focus of HIV programs” (International Bank for Reconstruction and Development [IBRD]/The World Bank 2016, 29). Unfortunately, as the Global Fund has transitioned out of Belarus and the national government has taken over responsibility for financing HIV services, there has been a 20 percent decline in the number of people who inject drugs receiving opioid substitution therapy (UNAIDS 2019b, 47). The cost-effectiveness analysis in this case appears to have been an international intervention aimed, in part, at advocacy by global health agencies: an attempt to influence the country’s health planners to reverse the regional trend and increase funding for harm reduction, as well as other needed services. In a country where international aid is significant, such as Eswatini, the leverage exercised by donors and UN agencies is greater than in a country where aid is transitioning out, such as Belarus. In these three cases, some key populations for whom there is data may benefit from advocacy that relies on cost-effectiveness analysis, but those who are uncounted are left behind. Thus, for larger subpopulations where there is good data, costeffectiveness analysis combined with donor and UN advocacy may result in larger allocations in HIV financing; but smaller groups and less welldocumented or recognized groups are invisible and more likely to be disfavored. In global debates like the one over Venezuela, or over donor transitions, both the champions of prioritizing high-prevalence countries in 109

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Africa, and the champions of prioritizing key populations in middleincome countries, had used the language of human rights to make their arguments. In engaging with these tools, I wondered whether human rights standards had addressed either the use of cost-effectiveness analysis or processes of prioritization in contexts of limited resources. HUMAN RIGHT TO HEALTH AND PRIORITIZATION

Human rights standards have created the foundations for much of the advocacy in the HIV response, but while the right to health is upheld by international treaties, the standards do not address how to prioritize. They merit a brief overview here for those unfamiliar with them. The right to the highest attainable standard of health is widely respected. It is asserted in the Universal Declaration of Human Rights, a foundational UN document (General Assembly resolution 217 A[III]). In 1966 the right to health was articulated in the International Covenant on Economic, Social and Cultural Rights, a multilateral treaty ratified by 169 countries to date. This right has since been elaborated in numerous other human rights standards for different groups.1 Other guidance has interpreted human rights law specifically for HIV, such as The International Guidelines on HIV/AIDS and Human Rights. In addition, regional instruments such as the African Charter on Human and People’s Rights have provisions on the right to health, and a number of countries have included right to health provisions in their constitutions (Heymann et al. 2013). Domestic lawsuits have used these standards to hold states accountable for fulfilling the right to health in South Africa, Kenya, Brazil, Colombia, and India (Cabrera and Ayala 2013; Yamin 2014). General Comment 14, drafted by the UN treaty body responsible for the International Covenant on Economic, Social and Cultural Rights, sets out obligations states have under the right to health under the Covenant. General Comment 14 recognizes that resource constraints may impede fulfillment of the right to health, and explains that the Covenant provides for “progressive realization . . . over a period of time”: states with limited resources should take deliberate, concrete 1

These include Article 12, Convention for the Elimination of All Forms of Discrimination Against Women (CEDAW); article 24, Convention on the Rights of the Child (CRC); article 28, International Convention on the Protection of the Rights of All Migrant Workers and Members of Their Families; article 24, Convention on the Rights of Persons with Disabilities; International Guidelines on HIV/AIDS and Human Rights; and United Nations Economic and Social Council, General comment No. 22 (2016) on the right to sexual and reproductive health.

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steps toward full realization of the right (Committee on Economic, Social and Cultural Rights [CESCR] 2000, para. 30). The Covenant also asserts two immediate obligations that states must uphold, regardless of resources. The first is to ensure nondiscrimination in access to health facilities, goods, and services. The second is a set of core obligations. Briefly, the list of core obligations includes essential primary health care; the right of access to health facilities, goods, and services on a non-discriminatory basis; the right to minimum essential food; access to basic shelter, housing, and sanitation; essential drugs; equitable distribution of health facilities, goods, and services; and a national public health strategy and plan (CESCR 2000, para. 43). In addition, states have “obligations of comparable priority”: reproductive, maternal, and child health care; immunization against the major infectious diseases; measures to prevent, treat and control epidemics; education and access to health information; and appropriate training for health personnel, including education on health and human rights (CESCR 2000, para. 44). It would be difficult to argue about any single item on this list, because all are important, but many of the core obligations are not upheld by even wealthy countries. The UN Special Rapporteur on Exterme Poverty and Human Rights has found that many people in the United States and United Kingdom, for example, lack minimum essential food and shelter, health care, and sanitation (Alston 2017; General Assembly 2019). Many have debated whether countries can in fact meet the standards, but the Covenant seems to presume that all states do have the funds to meet all these core obligations, that aid is sufficient to fill any missing gaps, and does not explain how to prioritize among core obligations if resources fall short (Tobin 2012). Similarly, how should donor states prioritize? While the Covenant underscores that states “in a position to assist” other states should assist them, it does not elaborate how a donor should prioritize when it lacks the resources to help everyone (CESCR 2000, para. 45). The General Comment is a powerful tool for health rights advocates, because it is aspirational enough to justify demanding that states meet any of a long and ambitious list of core obligations. But this very aspirational quality has left a gap in clarifying the obligations to governments to ensure that prioritization processes are fair and ethical, or in clarifying what principles should be used to prioritize, other than those that have been supplied by cost-effectiveness analysis. 111

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Other human rights scholars have addressed this question by focusing on the process. Notably, Gruskin and Daniels (2008) argued that a process of health resource prioritization should be principled, evidence-based, consultative, participatory, transparent, and evaluative: in their words, “the process is the point.” However, this leaves two important unanswered questions. First, it does not address on what basis the process should identify priorities. Is making a human rights–based decision simply a matter of who in the process can make the most persuasive case? The second unanswered question has to do with the surrounding context in which the process is convened. Any decision-making process will be shaped by the larger political context of inequality. In the HIV sector, the participation of marginalized communities in prioritization processes has been powerful, at times. However, there are real power asymmetries, even for relatively empowered civil society actors. Peter Njane, the Kenyan director of ISHTAR-MSM introduced earlier, said in a report to which I contributed that when he participated in processes of drafting funding proposals for HIV donors in Kenya, he found “[t]he moment you leave the room, your things go out the window. When Peter leaves, [men who have sex with men] go out the window, and the next time you come back, they have moved on to another chapter” (Esom et al. 2016, 16). Transgender women are another glaring example of the ways that marginalized and discriminated groups face challenges in advocating for their own inclusion. Though they face perhaps the highest rates of HIV of any key population globally, they “are often excluded from policy, program and funding decisions” at the country level (IRGT 2015, 5). Transgender-led organizations face significant barriers to fundraising for their work, making it difficult to sustain their engagement in policy processes (Howe et al. 2017). Thus, without a better-articulated set of principles for prioritization, putting the entire burden for addressing that discrimination on the process potentially shifts some of the responsibility for making the case for their own life-saving services to the weakest participants in that process. Human rights experts should revisit the International Covenant on Economic, Social and Cultural Rights. Building on Gruskin and Daniels’ work, they should articulate a rights-based approach to prioritization in contexts of constrained resources. In the absence of one, neoliberalism

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has filled that gap, shaping prioritization at both the global and country levels in line with the model of the market. CONCLUSIONS: DEPOLITICIZATION AND THE MODEL OF THE MARKET

When Dr. Martin said that after the CVC study was finished there would be a “fight for prioritization” in the budget to ensure allocations toward HIV and key populations, he was speaking the language of costeffectiveness. The logic of cost-effectiveness has spread inexorably, becoming a universal discourse used to shape thinking in global governance of the HIV response. While global health agencies have set ambitious human rights objectives, including targets of “zero discrimination” in the Fast-Track approach, these have been weakly integrated into the tools used to allocate resources. When it comes to making difficult decisions, cost-effectiveness principles have displaced human rights values. When Peter Njane leaves the room and his prioritization of men who have sex with men flies out the window, it may be in part because a Geneva-based consultant came in the door with costeffectiveness software on their laptop. While cost-effectiveness analysis as a tool could contribute toward ensuring that states allocate maximum available resources to progressively fulfilling the right to health, the value of cost-effectiveness is not explicitly balanced against other human rights principles in prioritization – principles that could, for example, emphasize the need to care for historically discriminated-against populations. Under the human right to health, countries with the resources to help others are required to do so, and the people whose right to health are not upheld as a result may have cause to complain to the treaty body. But in a market-driven model of aid, power shifts to the one who has the funds, with countries and subpopulations competing to receive investment. If the investment case is weak or if data is lacking, he who holds the funds may be justified in prioritizing a stronger investment case based on better data. Rights holders become either winners or losers. Competition is “the market’s root principle and basic good” (Brown 2014, 36). As we will see in the debates over the Global Fund’s Eligibility Policy, that fight for prioritization for small groups, in a small country, mirrors larger fights for prioritization among countries and populations globally. 113

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Ironically, the cost-effectiveness logic has now spread to the very global agencies that have promoted it at the country level. As funding becomes more contested, year after year, the list of global health agencies in Geneva publishing investment cases for themselves continues to grow. In 2019 the Global Fund published an investment case for its sixth replenishment campaign which committed to save sixteen million lives (The Global Fund 2019b). WHO published its first investment case also, arguing that its activities would “save up to 30 million lives” (WHO 2018a). Meanwhile, other agencies were preparing their own replenishment calls, measuring profits in lives saved (Burt 2019). And their bilateral donors, in turn, made their own investment cases to Congress, Parliament, and other legislative bodies, promising lives saved if their budgets were approved (Department for International Development [DFID] 2016; PEPFAR 2017). In these investment cases, donors drew on language, data, and thinking that had been framed by mathematical models that made the case for scaling up the global HIV response, and that were now used in cost-effectiveness analysis. To understand their underlying rationales, the next chapter examines the assumptions behind those models.

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5

MODELING THE E ND OF AIDS

During 2000–15, the world saw a rapid growth of the global AIDS landscape. A series of high-level UN commitments, and the establishment of the Global Fund and PEPFAR “catapulted AIDS from a narrow health concern to an issue of global security, human rights and development” (Chan 2015, 139). Scale-up of funding for these agencies and for national HIV programs funded by them created “an assemblage of vast resources, manpower, expertise, strategies and technologies, all of which are presumed essential for the implementation of complicated, multifaceted global health interventions” (Kenworthy and Parker 2014, 2). Some of this was due to predictions made using infectious disease models. This chapter follows on the previous discussion of cost-effectiveness to interrogate some of the assumptions behind the models used in costeffectiveness software. These began with a series of academic studies, and continued to develop as part of UNAIDS’ work to set out the FastTrack approach. The reliance on quantification created a kind of epistemological exclusion that kept qualitative data on human rights out of the models – both consideration of how human rights abuses might undermine optimistic future scenarios and of how addressing those abuses might facilitate greater success. It is important to note that critiquing how scale-up was modeled and implemented does not negate the real good it has done in the countries where HIV prevalence was highest, especially by sharply increasing enrollment on treatment in some locations, and significantly reducing HIV-related deaths across East and Southern Africa. Maurine 115

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Murenga, a Kenyan Global Fund Board Member diagnosed with HIV in the early 2000s, recalls: I have never seen so many people die in a given period of time. . . . Then came treatment. Then came the Global Fund. . . . We have had many more people stay alive because they get ARVs from the Global Fund. We have had malaria deaths reduced. Therefore, in terms of saving lives, the Global Fund has done quite a tremendous job. (Friends of the Global Fight 2018)

For Allan Maleche, the impact of scale-up was mixed. While he is a resolute champion of the Global Fund, he said, “I have seen increased mobilization around HIV . . . more investments in HIV programming . . . but also coming with that I have seen new forms of stigma and human rights violations,” such as discrimination against key populations by health care workers, and forced and coerced sterilization of women living with HIV. He had seen cases “where people want to use coercive methods to get people to test, or ways to collect their data that will put them more at risk with government or state agencies.” Without consideration of these complex on-the-ground realities, the models for scale-up facilitated what Biehl (2007, 2008, 2009) called the “pharmaceuticalization” of an HIV response, or what colleagues at the Global Fund sometimes call the “commoditization of grants,” in which grant funds are used to procure commodities instead of to address more difficult structural factors. As the Finance manager quoted in the previous chapter noted, the lack of quantitative research showing that addressing human rights would have a measurable impact on health, and that such work was cost-effective, meant that it was easy to exclude these and similarly unquantified considerations from plans to address the HIV response. Thus in many countries, the work of addressing stigma, discrimination, criminalization, and gender inequality, while frequently cited as rhetorically important, is in practice often an afterthought in planning, financing, and implementing the HIV response. The models behind the Fast-Track approach were in part narrative devices, aimed at making a case for ending HIV that would inspire the public, and donors. This kind of storytelling persists, even as the epidemiological trends increasingly show that HIV will not end by 2030: in 2019, as the Global Fund mobilized support for its sixth replenishment conference, celebrities signed onto an open letter pledging to all seven-year-olds to end AIDS, tuberculosis, and malaria by 2030 (The Global Fund 2019c). In 116

INFECTIOUS DISEASE MODELS

order to tell these kinds of compelling public stories, noble lies that inspire action and hope, the mathematical models must be persuasively grounded in science but must avoid confronting the realities that might, in the long run, undermine progress. This chapter begins by briefly introducing infectious disease models, and then reviewing the early academic models for Test and Treat, which laid out the initial case for scale-up, and the later models commissioned by UNAIDS to develop the FastTrack approach. Finally, the models are analyzed from the perspective of human rights and related, but unquantified, realities, suggesting some ways to integrate these considerations into future models. INFECTIOUS DISEASE MODELS

There are a variety of types of infectious disease models, including some that assume fixed parameters; others that compartmentalize parts of the population; models that incorporate networks of relationships; and dynamic models, which change over time as the number of infectious individuals changes. The purpose of the model and the kind of data available shapes the type of model selected. Having chosen the type, modelers then construct mathematical formulae, drawing on the following information, for example: • information on how an infectious disease is transmitted and how long the infection lasts; • estimates of the numbers of people who may be susceptible; • estimates for the number of people who are infectious; • estimates of the number of people who are recovered; and • calculations of the risk or rate of infection in a given time period, based on the predicted contact among the different categories of individuals, and the recovery rate (Vynnycky and White 2010, 13–40). Infectious disease modelers try to take account of the diversity of populations that may exist in a given context, segmenting groups based on their age, gender, risk behavior, or other characteristics, and modeling the interactions among subgroups. By combining these and other kinds of quantitative information, for instance on the impact of prevention interventions, models can create possible future scenarios for the disease. 117

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For the flu, models are relatively simple. HIV is one of the most complex infectious diseases to model, both because it is not curable and can persist for years and because one person can be exposed to the virus multiple times and in diverse ways, with different levels of risk each time. Models of HIV can be dynamic, factoring in subgroups and infectious periods; considering duration and overlap of sexual relationships; and factoring in individuals, such as sex workers, whose sexual contacts may crisscross different groups. A mathematical model that aims to capture these complexities within a large population must find ways to make the complexities manageable. Thus, reading an introductory work on HIV modeling can lead the reader to confront head-scratching statements like this one: “For simplicity, we will ignore . . . age and gender, assume proportionate mixing, . . . and assume that individuals do not change activity group over their lifetime” (Vynnycky and White 2010, 260). In the real world, of course, sexual contact is rarely mixed proportionately across age and gender, and people do change their sexual activity groups over their lifetimes. Nonetheless, some assumptions are necessary: in a quote often attributed to Einstein, “Everything should be made as simple as possible, but not simpler.”1 How simple is too simple? This is debatable; many modelers will say, when asked, that a model is only as good as its data and its assumptions. The assumptions behind the Test and Treat models that emerged in the 2010s were biomedical and optimistic, and excluded political risks. MODELING TEST AND TREAT

In the early 2000s, modeling grew to prominence as a tool for policy and management of the HIV response globally and at the country level. A series of academic studies using mathematical models began to make the case that scaling up testing and treatment for HIV would bring HIV prevalence down significantly in high-prevalence countries, resulting in increased productivity that would boost those countries’ economies, in turn resulting in a rapid drop-off in the level of external aid required (Granich et al. 2009; Granich et al. 2010; Hecht et al. 2010; Resch et al. 2011; Stover et al. 2006). Failure to scale up – the counterfactual was often maintaining 1

Ironically, what Einstein said was more complex: “The supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible, without having to surrender the adequate representation of a single datum of experience” (1933).

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coverage at existing levels – would, they warned, lead to a steady and continuous year-on-year increase in the amount of external aid required, as the number of people contracting HIV and needing expensive lifelong treatment continued to grow. In 2009 Granich and colleagues modeled a groundbreaking and theoretical strategy of universal voluntary HIV testing among all those older than fifteen years of age on an annual basis, with immediate treatment for those who tested positive, or “Test and Treat.” They found that this would result in increasing ART coverage to 90 percent within seven years, and “could bring about a phase change in the nature of the epidemic. Instead of dealing with the constant pressure of newly infected people, mortality could decrease rapidly and the epidemic could begin to resemble a concentrated epidemic with particular populations remaining at risk” (Granich et al. 2009, 54). This modeling exercise received intense attention. Other modeling studies attempted to replicate these results. Some questioned the assumptions behind the Granich study and its cost-effectiveness, arguing that elimination was implausible, and that failure to reach full treatment coverage could increase long-term costs (Wagner et al. 2010; Dodd et al. 2010). A review of twelve models found that while all the models of Test and Treat varied significantly in their assumptions and parameters, high levels of access and adherence to antiretroviral treatment could substantially reduce new HIV infections (Eaton et al. 2012). The consensus was emerging that Test and Treat could have a major impact. An important element of the case for scale-up, and some of what made it persuasive, relied on the prediction that scale-up would be a temporary obligation on donors: successful scale-up would increase the numbers of “lives saved,” and improve productivity, helping turn developing countries into middle-income-countries that would become capable of self-financing their HIV programs by 2020 (Hecht et al. 2010). In 2013 WHO reviewed the evidence and cautiously agreed with these findings. They issued new guidelines which recommended not Test and Treat, but a significant expansion of treatment: countries were now urged to provide antiretroviral therapy to all HIV-positive patients whose CD4 count fell below the normal standard of 500; as well as to all pregnant women living with HIV regardless of CD4 count, HIV serodiscordant couples, and others with active tuberculosis or hepatitis B (WHO 2013). 119

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WHO’s new guidelines gave the green light to the scale-up of global HIV financing, as procurement of treatment on this scale meant that national HIV programs would need significantly more funding than before. Scholars continued to argue for a further expansion of treatment beyond that recommended in the 2013 guidelines. Further reviews of modeling studies confirmed that the Test and Start approach could lead to elimination of HIV in South Africa (Hontelez et al. 2013) and confirmed that earlier eligibility for antiretroviral treatment was costeffective (Eaton et al. 2013). Stover and colleagues (2013), a group including experts at UNAIDS and WHO, created models that showed that an immediate scale-up that used the new WHO treatment guidelines could reduce new HIV infections by 80 percent and create significant cost savings, and they recommended that WHO go a step further to recommend a Test and Treat approach. In 2015 WHO responded to these new studies with updated guidelines recommending that all people diagnosed with HIV receive treatment immediately, regardless of their CD4 count (WHO 2015). The scale-up of HIV programming during 2000–15 was mirrored by the scale-up of infectious disease modeling as a powerful means of forecasting that now was central to monitoring and managing the global HIV response. Hallett and colleagues argued that modeling was enabling UN agencies to consider the consequences of decisions simultaneously in “many dimensions (morbidity, mortality, new infections, resistance, resource needs) and over a range of timescales, while also weighing the strength of various forms of evidence and accounting for the attendant uncertainties” (Hallett et al. 2014, S1). Similarly, UNAIDS began to draw more heavily on modeling after 2010. Today, many countries develop their own models using the Spectrum software introduced in the previous chapter. The academic studies that had been published during about 2009–15 inspired those commissioned for the Fast-Track approach by UNAIDS (Stover et al. 2016). In 2015 UNAIDS published its first introduction to the Fast-Track approach, explaining that advances in science, experience, and advocacy “have offered us an historic opportunity to end the AIDS epidemic as a public health threat by 2030” (UNAIDS 2015, 3). While the AIDS response had produced impressive results, UNAIDS argued, “maintaining today’s response at the current pace is not enough to end an epidemic that is constantly evolving” (ibid.). In order to save twenty-eight million lives, interventions would need to be scaled up (see Figure 5.1). 120

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2.5 Number of new infections (million)

2.5

28 MILLION Total HIV infections averted 2015–2030

Ambitious targets 0.2 0 2010

2015

2020

2025

Constant coverage

2030

Figure 5.1 UNAIDS model of the Fast-Track approach. Credit: UNAIDS

The Fast-Track approach was one of the first global health strategies to rely largely on modeling. Stover and colleagues (2016) published the models and data behind it. Modeling was now firmly entrenched in global health. However, infectious disease modeling as a tool for policy-making has never been fully interrogated, and it probably should be reviewed and discussed more critically. Scale-up was a massive global undertaking, directing billions of dollars to numerous countries. But the case for scale-up was in part hypothetical and faith-based, because the size of what was being proposed as a new global policy could not be tested through randomized controlled trials. What was being modeled was several orders of magnitude larger than what had been proven to date through scientific studies in towns and districts. In essence, the FastTrack approach was both an advocacy campaign and a vast global policy experiment. Models are abstractions and predictions used in decision-making, and anthropologists and human rights scholars have only recently begun to consider how they are used in global governance. While there are obviously major disciplinary differences between anthropology and infectious disease modeling, engagement across these disciplinary boundaries could be constructive. In thinking critically about the role of mathematical models, we can consider what choices are made in designing models, and how these may be unconsciously reflective of what modelers believe is important, visible, and measurable. How do 121

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broader economic and social forces, including gender and other inequalities, shape the assumptions in the models? What is the role of models in reinforcing or challenging those structural factors? These factors are what Seaver (2015) calls “the unquantified remainder that haunts mathematical models.” THE UNQUANTIFIED REMAINDER: HUMAN RIGHTS

Health sector stigma and discrimination, both against people living with HIV and key populations, is one of the most pervasive problems in the HIV response. Since 2008, more than one hundred countries have completed People Living with HIV Stigma Index questionnaires, which have shown that stigma is widespread and remains a barrier to accessing health care (People Living with HIV Stigma Index 2019). As discussed in earlier chapters, there is extensive research documenting health sector discrimination, by UN agencies, civil society organizations, and academic researchers. But the academic models that predicted epidemic control referenced above nearly all omitted reference to health sector discrimination and how that might discourage testing and adherence in the global scale-up of Test and Treat. For example, the Granich study modeled Test and Start for all those over the age of fifteen but failed to consider how widespread discrimination might affect its predictions, or that in many countries, restrictive age of consent laws limit access to testing for many people under eighteen. This is a critically important subgroup for the model, as incidence is high among adolescents in southern Africa. The study also does not discuss violence and transactional sex among adolescent girls and young women, or how the resulting stigma and hidden nature of their transactional sexual relationships makes it difficult for them to access health services. Granich briefly mentions that scale-up at the level and speed recommended “could raise concerns around human rights and coercion,” similar to those raised by sex worker advocates in an earlier chapter of this book. However, the study’s reference to this is in passing, and it does not consider the possibility that these abuses might undermine the modeled epidemic control; rather, Granich and colleagues argue that the benefits would outweigh any harm (2009, 55). Furthermore, they say, “appropriate training, engagement with the community, and supervision should keep problems to a minimum,” a broad description of a range of interventions that 122

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would have needed funding but are also not factored into the models (ibid.). While Granich and colleagues’ passing reference to human rights is somewhat dismissive, at least they reference it. The other academic studies that made the case for scale-up, mentioned above, made not even passing reference to the problems created by health sector discrimination for their predicted outcomes. One systematic comparison of models for treatment as prevention rightly notes that each model frames the questions and assumptions slightly differently, but even that helpful review does not note that the one thing all the models have in common is a state of cheerful ignorance of the human rights environment, the context of stigma, discrimination, criminalization, and violence in which people access (or often fail to access) HIV treatment (Eaton et al. 2012). Perhaps the modelers assumed widespread and entrenched stigma and discrimination would vanish if scale-up happened fast enough. It is difficult to say, as that assumption is not explicitly stated either. These modeling studies did not tend to address key populations specifically, as they were focused on high-prevalence countries with generalized epidemics. However, as scale-up rolled out, concerns began to arise about the emphasis on funding treatment at the expense of prevention. In 2018 UNAIDS reviewed Global Fund data on investment in primary prevention and warned that there was a steady decline in investment in these allocations since 2014; they urged the Fund to do more to promote investment in primary HIV prevention by funding recipients (UNAIDS 2018a). In the 2010s another series of studies emerged modeling prevention interventions, such as condom use, male circumcision, or pre-exposure prophylaxis (PrEP). These modeling studies found that scaling up prevention interventions would have positive impacts for key populations (Stover et al. 2006; Pretorius et al. 2010; Smith et al. 2016). But these also emphasized the commoditized approach, relying on procurement of goods and distributing them, without discussing the human rights barriers to accessing these goods for key populations, or the need to strengthen community engagement in order to ensure prevention commodities, such as condoms and syringes, reached those who needed them. For example, an early study arguing that scaling up interventions to prevent sexual transmission of HIV among people who inject drugs could avert twenty-eight million new HIV infections between 2005 123

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and 2015, and concluded that it would save costs in most regions (Stover et al. 2006, 1476). But the authors did not discuss how to attain the goal of 80 percent coverage, considering that most countries criminalize drug use and possession for personal use, or include harm reduction interventions such as needle exchange programs and opioid substitution therapy. In 2016 a major Gates Foundation–funded study in the Lancet HIV predicted massive impacts from increased investment in prevention, drawing on coverage data for key populations in Nigeria and South Africa, without discussing the impact of criminalization in both countries (Smith et al. 2016; Davis 2016a). In South Africa, police use condoms as evidence in criminal charges against sex workers (Open Society Foundations 2012). Globally, Shannon and Csete (2010) show that lack of legal protections, coupled with violence against sex workers, are associated with reduced condom use and increased HIV risk. The study could also have drawn on a systematic review of community empowerment interventions for HIV prevention among sex workers, which shows positive impact on HIV outcomes (Kerrigan et al. 2013). In particular, Smith and colleagues could have drawn on an important study in Nigeria that had been published in the same journal, in which an ongoing study of prevention and treatment of HIV among a cohort of more than seven hundred men who have sex with men happened to be underway at exactly the moment when Nigeria began to implement laws criminalizing same-sex sexual behavior (Schwartz et al. 2015). Schwartz and colleagues were able to quantify the immediate impact of the law on that cohort, including fear of seeking health care and avoidance of health care. When it came to gender, some of the modeling used assumptions that also included significant blind spots. A 2003 version of the manual for GOALS, the cost-effectiveness software, explained that its mathematical model calculated risk to women at high risk of HIV as “a combination of the number of high-risk men, the number of contacts with [sex workers], and the number of partners per [sex worker]. The percent of women in the low-risk category is calculated as the percent of men in the low-risk category divided by the average number of wives per husband” (Futures Group International 2003, 11). It is troubling that a widely used tool for resource allocation assumed that adult women could not have a variety of sexual partners themselves – that their risk was limited to that of their polyamorous husbands. It is positive that these assumptions were fixed in a later edition. 124

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GOALS is one of the few cost-effectiveness software tools to publish its assumptions, while others do not. Though the mistaken assumptions have been fixed, they remain an example of why it is important to make all modeling and cost-effectiveness analysis assumptions visible and transparent, so that they can be interrogated from other grounded perspectives. While the earlier academic studies carefully avoided dealing with human rights realities that were hard to quantify and that might have resulted in less optimistic scenarios, UNAIDS did not ignore the problems posed by discrimination in the Fast-Track approach. They clearly set a target of zero discrimination globally, though they did not establish a baseline (Davis 2015). In the Fast-Track approach, rather than quantifying the negative impact of discrimination on the scenarios predicted in the models, UNAIDS instead favored promoting interventions, the “social enablers,” that should be funded as part of the Strategic Investment Framework. But the UNAIDS Strategic Investment guidance itself states that while critical enablers are “indispensable,” they are also “context specific and difficult to measure” (UNAIDS 2012, 11). Thus in cost-effectiveness tools they are clearly add-ons, and weakly costed: OneHealth includes community mobilization as an intervention but provides only a strangely expensive “default value of US$118,” estimated based on uncited “information from various national strategic plans” (Avenir Health 2016, 67). A human rights costing tool piloted by UNAIDS was not designed to be integrated into existing costing tools, and was not widely adopted (UNAIDS 2012a). Thus, given the general discomfort with pinning down human rights interventions and costing them, as well as the lack of quantitative evidence of the impact of social enablers on health outcomes, it is not surprising that a 2018 report to the UNAIDS Programme Coordinating Board on financing community-led responses, to which I contributed as a consultant, finds that despite an international commitment to increasing funding for them as part of the 2016 UN Political Declaration on HIV, social enablers were at that point not yet meaningfully defined or funded (UNAIDS 2018b, 26). An Asian regional analysis cites the UNAIDS Strategic Investment guidance to explain that these interventions are “context-specific” and “difficult to measure,” and that this is why they are rarely funded, even when they are included in national AIDS strategic plans (United Nations Economic and Social Commission for Asia and the Pacific 2016, 30). 125

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From the outset of the Fast-Track approach, AIDS activists viewed the promised “end of AIDS” with skepticism, in part because it was optimistic and did not factor in the concerns with which they wrestled daily. South African AIDS activist Mark Heywood wrote: “[A] very different picture is emerging to the optimistic one that government officials, ours included, wanted to make the AIDS story. There are medicine stock-outs in many countries. Sex workers and drugs users are humiliated, imprisoned and sometimes murdered” (Heywood 2016). In April 2016 African civil society groups wrote to the UN HighLevel Meeting that would approve the Fast-Track approach with a common position, warning that “we cannot become complacent or proclaim the end of AIDS prematurely,” while the HIV response is threatened and exacerbated by an increased focus on biomedical interventions, reduction in funding, shifting political priorities, humanitarian emergencies, war and conflict, gender inequality, punitive and other harmful laws and policies, harmful cultural and religious norms and practices, corruption and mismanagement of funds, poverty and other development challenges as well as a high dependence on external financing. (ITPC 2016)

Activists from key populations groups who participated in health financing meetings in those countries often found it difficult to get the interventions included in funding requests (Esom et al. 2016). When I worked as a consultant for a regional African LGBT network to document challenges faced by key populations in global health financing consultations, I interviewed Brian Macharia of the Gay and Lesbian Coalition of Kenya, who said: The fact that we need to create a safe and enabling environment for services is not resourced. But it is critical. If you’re going to walk outside with condoms and lube and you’re arrested or harassed by police because you’re carrying them, then the next time you will not carry condoms and lube. It rolls back the gains we have made. (Esom et al. 2016, 15)

Getting these interventions funded is challenging for many reasons, including their exclusion from cost-effectiveness software. But another has to do with the underlying logic behind scale-up, reified in the infectious disease models, which predicted that the end of AIDS could be reached through purely biomedical approaches that made human rights an afterthought. These human rights realities, unquantified and 126

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uncounted, became another example of the data paradox in which absence of evidence becomes evidence of absence. MODELS AS ANTI-POLITICS MACHINES

No model, or theory, can ever capture the totality of the real world, but any model can be interrogated and improved. Derrida (1978) saw language as a system of signs whose assumptions could be questioned and undone. Writing about Derrida, Caputo says, “Whenever it runs up against a limit, deconstruction presses against it. Whenever deconstruction finds a nutshell – a secure axiom or a pithy maxim – the very idea is to crack it open and disturb this tranquility” (Caputo 1997, 32). Math is a language, and perhaps cracking open the models behind 90-90-90 can suggest ways to reassemble them differently. The models were designed to make the case for scale-up, something both the modelers and UNAIDS believed would fulfill the right to health for millions of people living with HIV unable to access treatment. These models were able to forecast success in reaching 90-90-90, but it is success that is unlikely to materialize, because they were an abstracted scenario far from the real world that rights activists and communities have long documented: a world of corruption, discrimination, stigma, gender inequality, and abuses of power. When we spoke in July 2019, Ghys said that the Fast-Track models did not factor in problems with access such as health sector discrimination because of a lack of data on “how discrimination affects incidence,” he said. “At the time when this Fast-Track modeling was done. . . . I think there was not much evidence.” As I transcribed this, I cringed a little for Ghys; I had met him by chance over a cheese fondue after a group hike near Geneva, and he seemed generous – an avid hiker who enjoyed introducing the mountains to newcomers. But I could practically hear the howls of outrage that would come from human rights colleagues when they read this; many had spent years of painstaking, sometimes dangerous work, accumulating reports documenting the widespread nature of discrimination and violence affecting the HIV response. Actually, I was one of them (Davis, Triwahyuono, and Alexander 2009; Human Rights Watch 2003). But here was where diverging methodologies created epistemic exclusion: by “not much evidence,” Ghys of course did not mean that 127

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there was not much of any kind of evidence, because there were numerous qualitative studies, including some published by UNAIDS itself. That kind of evidence, however, could not be easily integrated into mathematical models in 2014. (The solution UNAIDS used was to group together programs to address stigma and discrimination with other “social enablers” as a group, and to factor them into estimates of what the Fast-Track approach would cost. There was little data on what this should cost, however, so the costing was based on what countries reported they currently spent.) What Ghys meant, I believe, was that in 2014 there was not much quantitative evidence to show either (a) a quantifiable harmful impact of discrimination or other rights violations on HIV incidence, or (b) conversely, that investing in access to justice or advocacy could reduce discrimination and have a measurable impact on reducing incidence. The quantitative and qualitative people had been at the same meetings, but had been largely talking past one another; the qualitative evidence was, in essence, invisible to modelers. But in service of making that argument, UNAIDS focused on the strictly biomedical aspects of what has always been a political virus. The models were engines driving the “anti-politics machine,” one of the outputs of which, Ferguson warned, would be repeated failures of development strategies due to failure to consider political factors. The science has moved on since 2014, and as the failures to reach 9090-90 are reviewed and as UNAIDS prepares to draft the next Political Declaration, there is more quantified evidence of the impact of human rights on health that can be potentially factored into future predictions. In 2019, at the time of our interview, UNAIDS had consulted with experts and begun soliciting public input into approaches to measurement of stigma and discrimination, and Ghys believed it could be possible to include human rights quantitatively in the next global strategy. In an email on September 10, 2019, Keith Sabin of UNAIDS noted that they have begun collecting some data from countries on avoidance of services due to stigma and discrimination through countries’ periodic reporting using the Global AIDS Monitoring indicators. Further research has developed this field since 2014, though mostly it has identified a need for still more research: one review of qualitative and quantitative research find that criminalization of sex work results in “extensive harms,” but that quantitative studies are too heterogeneous to assess associations (Platt 2018). An LGBTI inclusion index now 128

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offers a set of proposed indicators to measure inclusion of LGBTI people in the Sustainable Development Goals, which will need to be widely adopted to generate quantitative data, but which offers promise (Badgett and Sell 2018). Another approach to integrating human rights considerations into the models could move away from the link to incidence, looking instead at each stage of the treatment cascade and how rights violations affect access: to testing, treatment, and adherence. For instance, while the national PLHIV stigma index reports showing the depth and extent of health sector discrimination globally are of variable quality and reliability, they at least give a rough idea of the widespread nature of discrimination in the health sector; and they could be used to generate a percentage of the estimated national number of people living with HIV who may attempt to seek testing or treatment and who are simply refused, or who encounter stigmatizing attitudes and give up. Similarly, the Schwartz study suggests a way to quantify the negative impact of criminalization on adherence to treatment. Given that adherence and loss to follow-up are critical problems for the FastTrack approach, links between human rights violations and uptake and adherence to testing, treatment, and care services should be easier to quantify than a link to incidence. Graham and colleagues (2019) found that while criminalization of same-sex sexuality in Kenya weakened trust in health care providers for men who have sex with men, connection to LGBT organizations and other forms of community support improved adherence. Models could also factor in how age of consent laws might make it impossible for adolescent girls to take a test. Including quantitative data on rates of cash absorption in highprevalence countries would also give some indication of the barriers to scale-up. In fact, there are a number of approaches that could be tried, but they were not. Part of the reason, I suspect, that the modeling studies failed to factor in these barriers to access was that doing so would have weakened the case for scale-up, which was in equal parts an evidencebased argument and a passionate credo among those who had published the models, and who used them to tell a powerful narrative about the end of AIDS. As Peter Ghys of UNAIDS put it in our interview, mathematical models help set targets that persuade people: “You have to be a little bit ambitious for that field because you want that field to go a certain direction, and as far as is possible, right?” He explained: 129

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You have SDGs, things that say here is a target and a future, we should try and get there. . . . But often the target itself will come from some prospective modeling that says yes, this is possible. . . . Targets [should be] ambitious yet possible; otherwise they will not be useful. If they are not ambitious then we will underplay what the world can achieve, and if they are completely not attainable then they are also not useful, because they will just create frustration.

In other words, mathematical models help tell stories that are both inspirational and credible: they use science, but they are not themselves science. As Rebecca Henderson put it in a personal communication, referencing Geertz (1973), “Models, even those that appear to be simply representational ‘models of,’ are in actuality always transformative ‘models for.’” Thus, at the peak of the rise of cost-effectiveness, UNAIDS modeled the targets first and costed them after the fact. Health economics – the limited bucket of funding that requires countries to select winners and losers – stigma, discrimination, gender inequality, and criminalization, all these considerations were left unconsidered, in order to construct aspirational targets. The estimated cost included “significant uncertainty,” and did not factor in the “real-life inefficiencies associated with the scaling-up of HIV/AIDS programmes” (Moses et al. 2019). In response to a relentless barrage of withering activist criticism about the real-life obstacles to reaching 90-90-90, and as data begins to emerge showing that HIV is not going to end by 2030, UNAIDS has gradually begun to publicly acknowledge the challenges to reaching these goals, warning that as of 2018, despite real progress, “the global AIDS response is at a precarious point . . . the pace of progress is not matching the global ambition” (UNAIDS 2018). UNAIDS’ 2019 update underscored these concerns again, and by 2020, the gap between ambition and achievement will be clearer. When I met with Ghys, the latest UNAIDS update said that globally, new HIV infections among adults have declined by 16 percent since 2010, and new AIDS-related deaths have declined by 33 percent over the same period (Ghys 2019). But it also shows that the decline in infections and deaths is slowing year after year and fell short of the scenarios predicted by the models (UNAIDS 2019a, 7). I asked him about this, and he said: Of course, as we get closer to 2020, we are more and more recognizing in many places we don’t actually see [the scenarios predicted by the

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models]. . . . It doesn’t say that the model was wrong. It just says that the world, or certain governments, or certain agents within a country, they didn’t do enough to achieve the target; therefore the impact was not seen. In any case, that’s how I like to think about it.

In other words, the models were right; the failure was at the country level. But an introductory textbook on infectious disease modeling takes a different view: “If the model ends up not behaving like the real world, then this is evidence that its basic assumptions were either wrong or insufficient in some important way – a recognition which should encourage revision and redescription of the problem” (Vynnycky and White 2010, 9). The ways infectious disease models are constructed have real-life effects. Given their increasing power and influence in policy-making, it is critical that modelers and those who use them wrestle with the challenges of capturing that complexity. This means human rights scholars and anthropologists should also work with them to ensure that the unquantified remainder haunting targets like 90-90-90 – human rights violations, stigma, corruption, gender-based violence – are factored into future global goals. * “A LOT OF COOKS IN THE KITCHEN”

In early 2017, while I was deep underwater in a sea of infectious disease models and cost-effectiveness software, the CVC study in the Eastern Caribbean began to pick up steam. It was given fuel by the threat of diminishing global resources for health and the sense that this might be the last opportunity to have funding to get data on key populations that could break down silence and invisibility, and deliver evidence of the populations whose needs had not been met and whose existence was sometimes denied. As seen above, mathematical models, indicators, and costeffectiveness software that are used to plan, allocate funds, and monitor progress in the HIV response have faced numerous challenges with quantifying and addressing the needs of criminalized and stigmatized key populations. In the CVC study, civil society researchers and academic researchers were working together to gather long-absent data on hidden populations, including men who have sex with men and sex workers. This work was especially challenging, given the impact of 131

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some decisions made by global donors based on numerical indicators about numbers of people living with HIV and country economic capacity, as well as by the decision to abruptly transition out of some small countries and require them to hand back their only existing programmatic data on key populations. This abrupt donor transition had undermined community trust and willingness to cooperate with HIV studies. As I observed the CVC study get underway, it revealed gaps in trust that needed to be addressed, and real tensions also at the community level over what to measure, and how to measure it. As the first step, the research team needed to draft the research protocol and agree about what questions the research would focus on. This process of very local prioritization focused on the questionnaire to be used in the study. With limited time and limited financial resources, the community activists and government officials were forced to negotiate with the research team about what they would include in the study and what would remain uncounted. Ria Hearld, a demographer from University of Alabama at Birmingham, was excited about the opportunity to get local knowledge and insight into the populations, which she usually viewed from “twenty thousand feet,” but worried that there were too many competing demands from diverse stakeholders and “a lot of cooks in the kitchen”: “At the end of the day, we have a budget and timeline. You want to accommodate everybody, but you can’t.” As the groups and stakeholders came together to develop their research, they had to first agree on what they would measure. * In March 2017 CVC held a series of week-long meetings that brought together civil society representatives and government officials from the six countries in small groups. The participants all flew to the Dominican Republic from around the region. Some had previously met at other meetings; for others, it was the first time. I joined for the second of the series of week-long meetings, along with John Waters, Henna Budhwani, and her colleague Ria Hearld, a demographer also from University of Alabama at Birmingham. A graduate student was along to help with demonstrating and setting up tablets to be used for interviewing. The plan was that interviewers would prescreen interviewees to see if they were eligible, but the actual interviews would be completed on tablets, so the respondents didn’t 132

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have to look a stranger in the eye and answer difficult questions. When the questionnaire was completed on the tablet, the interviewer just hit “send,” and the anonymized interview responses were uploaded directly onto a secure server. This meant getting the written questions right – delicate nuances of tone, avoiding stigmatizing language that might turn people off – were even more important. We met in Santo Domingo, in the old colonial town, which looked fresh from the pages of a Garcia Lorca novel: elegant, sleepy, hot. The pastel low-rise facades opened in to elaborate enlaced corridors, courtyards, ironwork balconies, lush gardens. In the shady cafes that lined plazas baking in the midday sun, dapper gentlemen in suits set down their walking sticks to sip coffee and read the newspaper. We gathered in the blissfully air-conditioned back room of a museum. The meeting, typically for the region, started with a third of the participants stuck in flight delays. This did not slow down Julia Hasbún, the research director and meeting facilitator, who was up on her feet, working the group, making eye contact with everyone, attuned to their body language, egging them on. Participation from all, civil society and government alike, was crucial: many would join countrylevel steering committees to manage the actual research. She led them first to talk frankly about how they would overcome the barriers to finding hidden populations, then to tackle the questionnaire. For John, this first study in a long time offered a rare opportunity to identify and find hidden subpopulations, subgroups within the key populations who might not be reached by traditional programs. He remembered the example he had shared with Nigel at GrenCHAP from a beach community in his own country, the Dominican Republic, where there was quite a lot of anecdotal evidence that a lot of LGBT youth were involved in transactional sex, and some were very young, dying of HIV. They designed an intervention that was based on collecting some evidence and data. It was particularly complicated because this involved minors. One of the lessons from that, is that if you can do it with as tricky a group as LGBT minors, you can be successful with almost any other subpopulation.

He wanted to use the size estimation study to identify those groups and their needs, and prepare civil society participants to be ready to use the data to implement them as soon as the resources come through. Working together in small groups, the meeting began to tackle the problem of how they could break through layers of denial and fear to 133

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win trust of communities. The activists told government officials they would need to identify and win over gatekeepers: influential people within specific cliques. They would reach out through closed groups on social media, working their charm on a network of trusted hairdressers and barbers. Rather than brothels, most sex workers found clients through private parties: “We have strip clubs in someone’s house, you may get special invitations.” Sex workers were more likely to join a survey if they saw some direct benefit from participating, the activists advised, such as support to address intimate partner violence, selfdefense classes, or HIV rapid tests. To find men who have sex with men, one civil society activist recommended trying the churches: “Many pastors are linked to or involved in these things.” The room fell quiet as the rest of the participants absorbed this statement. The research partnership was already revealing practices, even thoughts, that had long been hidden. After a thoughtful pause, one government official replied to him, neutrally, “Our situation in the Caribbean is unique. We have to find these intricate opportunities.” After this brainstorming session, Julia and John introduced the questionnaire they proposed to use and distributed it to the group. It had been first developed by Johns Hopkins University, which conducts population size estimation studies in many countries; John and Henna, as co-investigators, liked the fact that it included questions on violence and stigma. But as they shared it with researchers and civil society groups, the list of questions just seemed to be growing. Julia urged the participants to be frank: “This research will belong to you, so you need to understand it.” However, cuts would need to be made, she said, because “this is a bus questionnaire – everyone is on it.” The community activists and government officials would need to make difficult choices, and the process of doing so revealed some tensions. In the ensuing two days, I watched as the group of about a dozen participants worked their way through the questionnaire, discussing and fine-tuning nearly every word of the questionnaire. Each of the civil society groups wanted to ensure their constituencies were addressed: transgender people and male sex workers were taken out, then added back in again. Questions about mental health, tobacco, and drug use were added, deleted, revised, and put back in. Henna pushed them to explain how the data would be used, and she had her own preferences: “I’d like to include mental health and drug 134

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use, because strategically, there’s funding out there to address those issues.” For an academic researcher, then, it was compelling to include questions that could lead to further research and funded services. But the week earlier, activists had flatly rejected all of the questions about tobacco use, drug use, and mental health, calling them stigmatizing. One activist warned Julia, “If I’m not 85 percent confident about this questionnaire, I won’t share it with anyone.” Julia reassured the activists that their input was essential: “Since the beginning this is a participative methodology. Their opinions are in each step that we do. They are in, and nobody is imposing.” Some of the work on the questionnaire focused on minute finetuning to language used in questions to avoid alienating interviewees; with a highly stigmatized, hidden community, one wrong turn of phrase could shut down the whole conversation. For example, early on, the group debated how to ask about interviewees’ ages. Dr. Martin thought this was unnecessary: “Patients don’t lie to us about their age,” he said. A civil society activist from the small country of Dominica told him that he needed to understand that this research project was different: “You’re talking about people who come to you, because they are seeking a service. This survey is people we have to go find.” This activist felt that asking women about their age would break a taboo. Kerlin Charles, from GrenCHAP in Grenada, agreed with her: “You have a tablet and you’re putting in their age. Caribbean women will never tell you their age. You might be married to a woman and never know her age.” The participants laughed. They agreed to set the age question aside for the moment and move on. By the time they had finished reviewing religious affiliations and levels of schooling, it was four in the afternoon, the group was exhausted, and they were only on part four of the first question. They edited together some of the questions on stigma and discrimination: “I know I’ve come across two questions that repeated themselves,” said one woman wearily. Ria worried about creating “interview fatigue” for participants: the interview was intended to be about twenty minutes long, but it was currently closer to ninety. What would happen to their survey, she worried, if the first few participants told others, “Don’t take the survey, it takes forever”? That afternoon, Ria, Henna, and Julia sat in an intense negotiation behind the scenes over what to cut and what to keep. John, meanwhile, had vanished: it turned out he had been consumed in intense negotiations of his own with the Principal Recipient for the grant, which had 135

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asked him, again, to ensure the study collected geolocated data on key populations. John had, again, refused. Staying up late in her hotel room, Julia “took an axe” to the questionnaire overnight, cutting out seventeen questions, including some of Henna’s mental health questions: “I don’t want to alienate them by suggesting that because they have sex with men, or are sex workers, they have mental health issues.” As at the global level, when debates over Global Fund KPIs reshaped indicators and how they were reported on, the very local process of developing this questionnaire for use in small countries was revealing the challenges with capturing nuances of local behavior and identity with a quantitative tool. The following day, the group came back to the museum for another hard slog through the questionnaire. This time, debate erupted over a question about intimate partner violence. How to measure it? The group focused first on fine-tuning the language to fit the Caribbean vernaculars, which varied from one island to the next: the merits of saying “hitting” instead of “beating,” “threat” instead of “intimidation,” “withholding money” instead of “deprivation of resources,” “restriction from going out” instead of “denial of freedom of movement,” “sexually ignores you” instead of “sexual deprivation.” Then a government official put his foot down. He did not understand why the questionnaire only asked about violence by men, and not about violence by women: “If it’s a woman beating up a woman, it’s not gender-based violence? Does this not create a bias, that it implies it’s only males that engage in violence against women?” Some women in the room bristled quietly. Violence against women is a fraught topic in the Caribbean, widespread but often denied. The official persisted: “For me I would not feel comfortable with this particular question, how it is phrased. My thing is, we are missing an opportunity to assist in an intervention.” Julia said no: “There is a universal definition right now (of gender-based violence) that all countries are using.” “What if a lesbian is playing a male role?” asked the official. The room exploded. Kerlin said firmly, “She’s not playing a male role. She’s playing her role.” Others in the group agreed with Kerlin. Julia told him to park the gender-based violence question and move on to other questions. Of all the difficult topics facing the group, the topic of how to capture gender-based violence had sparked the most heated debate. Later that day, Ria, Henna, and Julia sat John down (“We are kidnapping you,” Julia jokingly told him) to get his agreement to cut 136

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the questionnaire. Over coffee in a sunny plaza the next morning, Ria worried about competing interests: You have a lot of people who have competing interests, with a lot of different organizations involved. . . . The budget is so limited, I don’t want to be ungrateful, but the scope is getting bigger and bigger, and what are we going to do? Travel and different islands . . . are you being Jesus and making wine out of water? How do you do this?

What they were negotiating, researchers ruefully agreed, was a consensus across diverse constituencies about who and what would remain uncounted. But while the group was frank in their disagreements, they stayed unified in their mission. On the last day of the workshop, John organized a barbecue reception in the upstairs room of a small local restaurant. As the group laughingly argued about which Eastern Caribbean country had the most beautiful beaches, showing off photos on mobile phones to make their case, the graduate student who had been helping with tech support for the tables sat with a beer watching them, marveling at the rare cohesion. She said she had never before seen such a diverse group come together with so little ego or territorial dispute, united by a single purpose: to reach key populations. Dr. Martin, Grenada’s senior medical officer, said that the biggest surprise for him over the course of the week was to realize that the longundone population size estimate “is possible. It is possible.” He was pleasantly surprised that civil society activists were so willing to work with government. Phil Leon, a biostatistician I spoke with later from St. Lucia, said the study had helped him understand that there was a real gap in community trust of the health ministry: “When you go to the grassroots, when I speak to NGOs and communities like at Planned Parenthood and what-not, your scope begins to widen. I’ve encountered persons who go overseas to manage their HIV. They don’t trust the ministry or the HIV clinic, [thinking] ‘they will rat out our business.’” His engagement he said, had helped him understand that the community his health ministry needed to work with might be much more extensive than the health ministry currently knew. I needed to fly back to Geneva, as I had consulting clients such as Allan Maleche asking for urgent attention; but the Dominican Republic trip did not end when the workshop participants finished revising the questionnaire. 137

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The subgrant from the Global Fund was for a broader body of work that included training, community mobilization, and onward granting to local groups: training of trainers on the minimum package of services and outreach strategies for key populations, a risk reduction program for women vulnerable to HIV, developing and printing HIV prevention materials in Spanish and Creole for sex workers, creating a sexuality and sexual health manual for at-risk youth, police training materials, and more (CVC 2017). John could not make wine out of water, but he was not one to use an expensive regional airfare for only one purpose when he could use it for two or three. On just this trip, he had planned several more days of site visits up-country with the group, where he would take them to see some of the Dominican Republic’s groundbreaking community-led responses to HIV: a lesbian group doing HIV prevention work with female sex workers, a group led by trans women, and a tourism project he was developing which offered vocational training to young men who have sex with men. At the end of the night, I swapped numbers with a young activist working with sex workers in Turks and Caicos. She told me it was her first time traveling overseas, and while I made my way on a series of flights back home, my phone buzzed with her selfies, beaming with veteran Dominican activists all over the country. The meeting in Dominican Republic had produced stronger bonds, both among the workshop participants and with their peers running local programs. A few weeks later, I called Henna to see how the questionnaire was coming along. In particular, I was curious about how the questionnaire would count sex workers given the widespread practice of transactional sex. The questionnaire was still too long, she worried, and “If we have to cut the survey from one and a half hours to thirty minutes, I don’t know if we have space to capture transactional sex.” But the need to cut might be hard for civil society activists to appreciate, she worried: “They could feel upset if they have needs no one is fulfilling, and if you’re not listening.” While they waited for ethics review approval, she and John continued refining the questionnaire, itching to start the data-gathering. Zooming in and out between global and country levels had exposed striking parallels and differences in processes of quantification in a complex HIV context – and underlying problems of power and autonomy. The global-level mathematical models and related tools were aiming toward simplicity in order to create visual objects, such 138

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as charts, that would drive certain kinds of decisions effectively. By contrast, the CVC study was wrestling with the problem of how best to capture local complexities and nuances of language in order to protect the thin, fragile thread of trust they were beginning to establish with communities. The Global Fund Board was at this time, preparing to revise its Eligibility Policy, while also trying to resolve the apparently unending controversy over Venezuela, just across the Caribbean Sea from my field site. I was beginning to get text messages from Allan Maleche again, this time about the massive challenge facing his delegation as they confronted the cracks in the indicators used to assess eligibility for the Global Fund. As I started on the long series of flights back to Geneva, it was striking that the role of global health policy-makers seemed often to be to try to find ways to make decisions as simple and clear as possible, while civil society seemed perpetually to demand consideration of difficult complexities. These tensions would come to a head during the year-long contest over the Eligibility Policy.

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“Hey Meg. How booked are you for September?” Allan Maleche was texting again, this time while he worked his way through Amsterdam’s busy Schiphol airport with his wife, child, and baby. Somehow, he managed to carry the baby, handle “random screening” by security once again (“They’re going to question the baby, not sure in which language,” he joked), and strategized about the Global Fund Board, all at the same time: “Am looking at a paper that says if we want to end the epidemic, Global Fund needs to do x and y together with stakeholders and partners. . . . And be realistic: without the necessary money, we will not end the epidemics, but just maintain them.” In 2017 the Board began its work to revise the Eligibility Policy, which sets out the criteria for which countries are eligible for Global Fund financing, and for which disease. The three civil society delegations on the Board, including Allan’s delegation, had agreed to hire a consultant to do some research that they could use to advocate together: “To align our positions, speak in one voice, and articulate the issues,” as Allan put it later. Representing thousands of organizations, and with the implied threat of a combined vote on the Board, the three delegations could negotiate more effectively for changes demanded by their broader constituencies. I told Allan I would bid on the consultancy for the three delegations and asked if he had read a recent article by Laurie Garrett (2017) raising the specter that without increased financing for HIV, there could be a second global HIV pandemic. He had. “Second pandemic will be a disaster, Meg!” Allan replied. “She was spot on.” 140

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Figure 6.1 Civil society and community representatives at the Global Fund Board table, 36th Global Fund Board meeting (L–R, foreground): Allan Maleche, Maurine Murenga, Mike Podmore, Rico Gustav. Credit: Rachel Ong Communities Delegation

In this chapter, we step away briefly from focusing on the problems with data and quantitative metrics to consider the impact of decisions made using those indicators, and to see the role of civil society in highlevel contests over whether numerical indicators adequately capture the complex needs. In this urgently-formed transnational coalition, activists from the global north and global south, some living with HIV and some not, joined forces to advocate at the highest levels of global health finance for resources for key populations, winning some government support to their arguments. Once again, civil society advocates were trying to introduce messy realities, the ignoble truths not captured by the simple elegance of numerical indicators. The data paradox, in which denial of the existence of key populations by some governments results in lack of data and lack of prioritization of their needs, was only one of several ways in which politics entered the numbers. More broadly, though, the focus of the contest in the revisions to the Eligibility Policy had to do with the issues discussed in the first chapter: the question of how to allocate funds across diverse countries given ambitious global goals and limited funds. Here, the rise of costeffectiveness and the narrowing of focus promoted by the Fast-Track approach found its logical culmination. The donors on the Board were 141

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under pressure to demonstrate impact in a limited number of countries, and to this end they were opposed to expanding eligibility; if anything, some were curious to see whether eligibility criteria could be narrowed so that more countries transitioned out, freeing up more funds for highprevalence, low-income countries. Donors also needed the Fund’s policies to align with other bilateral and multilateral criteria used to determine eligibility, to ensure policy consistency between the Global Fund and donor foreign aid policies. On the other hand, implementing governments on the Board, those receiving funds, were generally interested to preserve whatever they were getting, and naturally, some hoped to get more, instead of less; this meant that African governments with generalized epidemics were largely in agreement with donor priorities on HIV, priorities shaped by the Fast-Track approach and cost-effectiveness values. Civil society representatives on the Board, on the other hand, pushed to ensure eligibility for those most vulnerable and marginalized, wherever they were; this meant that the Board representatives from middle-income countries might be more sympathetic to civil society delegations. While the Fund was far from the only donor wrestling with these problems of prioritization, its transparency and accountability made it the most public example. It was also facing the worst of the problem because in many countries it was the last remaining external donor for HIV to transition out; bilateral donors had often already left, expecting the Global Fund to cover remaining gaps. When some middle-income countries with concentrated epidemics among key populations saw multiple donors divest at the same time, programs for key populations, such as harm reduction, were put at risk (UN Foundation, RESULTS and ACTION 2017; Bridge et al. 2016). As this chapter will show, in revising the Fund’s Eligibility Policy, the high-stakes contest was focused on a brief document of just a few pages, in which changing a single indicator – even the wording of a footnote – could have sweeping consequences, shifting millions of dollars from one country to another. This chapter begins by summarizing the context in which the policy was reviewed and debated, then introduces the three civil society delegations and how they worked together to advance a shared position. It delves briefly into the emergence of the Eligibility Policy during the Global Fund’s history, and explores some of the key areas of debate: over use of GNIpc to determine country economic capacity, as well as over an interlocking 142

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jigsaw puzzle of exceptions and exclusions to manage middle-income countries. Finally, it summarizes the resulting outcomes. ALARMING TRENDS IN THE GLOBAL HIV RESPONSE

The landscape that shaped the Eligibility Policy debate took shape during the July 2017 International AIDS Conference on HIV Science in Paris, where UNAIDS shared its annual updates. The agency had worrying news: as noted in the previous chapter, while there was a decline in HIV incidence globally and a drop in HIVrelated deaths, especially in Southern Africa, where rapid scale-up had made some real gains against the epidemic (see Figure 6.2); there was also, UNAIDS said, “an alarming rise” of new infections in the middle-income countries of Eastern Europe and Central Asia (EECA; see Figure 6.3). There was also a visible spike in incidence among key populations globally: the UNAIDS 2017 update said that outside of Sub-Saharan Africa, 80 percent of new infections were among key populations and their partners (UNAIDS 2017b, 9). UNAIDS also reported at that time that infections were on the rise in Eastern Europe and Central Asia (2017b, 7). Two years later, this spike in new infections would become evident in three regions of the world where international aid agencies had been transitioning out: Eastern Europe and Central Asia (29% increase), Latin America and the Caribbean (7% increase), and Middle East and North Africa (10% increase) (UNAIDS 2019a, 7). Globally, investments in programs to serve key populations were not keeping pace with the rise in incidence: less than 1 percent of people who inject drugs lived in countries with adequate coverage of harm reduction services (Larney et al. 2017). This was especially true in Eastern Europe and Central Asia, the place where the spike was visible already in 2017. The bulk of the 25 percent increase in AIDSrelated deaths in that region occurred in the Russian Federation, where an estimated 30,550 people died of AIDS-related causes in 2016 (UNAIDS 2017b, 172). Faltering Russian government commitment to addressing HIV had made antiretroviral treatment and basic information hard to access for many; the epidemic was a “public health crisis,” in the words of experts, with potentially many thousands of cases untested and unreported (Cohen 2018). HIV prevention was underfunded, opioid substitution therapy was prohibited, and a 2013 anti-gay propaganda law hampered outreach to men who have 143

DECLINE IN DEATHS SHARPEST IN EASTERN AND SOUTHERN AFRICA 600 00 Number of AIDS-related deaths

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AIDS-RELATED DEATHS, BY REGION, 2000–2016 Source: UNAIDS 2017 estimates

Figure 6.2 Global decline in HIV-related deaths, 2017. Credit: UNAIDS

Latin America Middle East and North Africa

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Caribbean New HIV infections, all ages, global, 1990–2016 and 2020 target Source: UNAIDS 2017 estimates.

Figure 6.3 Alarming rise in new infections in EECA, 2017. Credit: UNAIDS

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sex with men; only 9 percent of Moscow men who have sex with men living with HIV were on antiretroviral treatment (Beyrer et al. 2017). Russia’s influence was shaping responses in neighboring countries: one study of harm reduction laws found that Central Asian laws had tended to adopt Russian laws taking a punitive approach to drugs (Utyasheva and Elliott 2009). China, formerly one of the Fund’s largest recipients and a significant contributor to the global burden of HIV, was another example of the damage done through abrupt transitions. For years, the Global Fund had struggled to get through Chinese government restrictions in order to fund community-based groups on the front lines of the HIV response. The Fund “opened doors for [civil society organizations] to operate in China,” but ultimately withdrew in part over lack of their inclusion in government health programs and financing (Huang and Ping 2014, 5–7). Little funding reached grassroots groups, due to corruption and funding mismanagement; numerous “fake” NGOs with government ties sprung up to absorb the funds (ibid., 10, 13). In 2010, my organization, Asia Catalyst, had brought a group of Chinese key population activists to the International AIDS Conference in Vienna, where they had met with senior Global Fund officials and shared that the Fund’s financing trickled through state agencies, with each taking a cut, but reached the grassroots late, if ever. But in contrast with Kenya, where key populations had been able to negotiate for funding and autonomy through establishing strong unity, toxic infighting among cliques of Chinese NGOs had undermined their negotiating power with the Fund and the state (Gadsden 2010). While the Fund withdrew from China gradually, few other donors stepped forward to fill the gap for civil society. When new government leadership took the helm in 2012, a sweeping crackdown on civil society and foreign funding ensued. A revision to the Eligibility Policy rendered China and other G-20 members ineligible as of 2013. Since then, HIV incidence has grown in China, surging especially among criminalized key populations (Zheng 2018). These were just two examples. Meanwhile, the problem of donor transition was widening across middle-income countries, with dozens of countries facing an end to their eligibility from one or more of the global health funders by 2040 (Silverman 2018, 11). The most catastrophic example was Romania, a middle-income country with growing poverty. Global Fund’s support for national HIV programs ended 146

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abruptly in 2010, causing “a collapse in services, especially the availability of needle/syringe programmes for people who inject drugs. This lack of funding coincided with a dramatic increase in HIV among PWID . . . [which] rose dramatically to 6.9% in 2012 and spiked at 53% in 2013” (European Harm Reduction Network [EHRN] and ICASO 2016, 4). A persistent challenge post-transition in all these diverse contexts was that, predictably, government funding for HIV services lagged for key populations, who were getting “lost in transition,” in Rico Gustav’s words. A UN report in the Asia-Pacific region noted: The reality is that HIV and AIDS are competing for attention and resources against numerous other priorities, particularly in this region, where AIDS is not a leading cause of death. Moreover, stigmatization and discrimination against key populations is still prevalent in most of the countries in the region, and generally social conservative governments can find allocating public funds to benefit such populations . . . a struggle. (UNESCAP 2016, 35)

As its bilateral donors withdrew, the Global Fund was also steadily narrowing eligibility over time. Yearly, a few more components in middle-income countries were eased out of Global Fund eligibility, gradually focusing its investments in a shorter list of components and countries. As of 2017, thirteen countries were in the transition process, meaning that one or more disease components (HIV, TB, or malaria) was preparing to reach the end of its funding. Two countries, Algeria and Dominican Republic, increased disease burdens during the transition process, meaning that more people might be accessing treatment, but raising questions about the future sustainability of their programs. Four countries became newly eligible in 2017 due to changes in their disease burden or national incomes: Kazakhstan, Lebanon, Montenegro, and Palau. The Fund had to deal with the reality that for some governments, the presence of the Fund’s support was an excuse to not take responsibility themselves. One Fund program officer I met at a social event in Geneva described mobilizing massive resources and UN engagement in response to a country that wrote in a panic saying they had run out of treatment for TB. But afterward, she said, the country was slow to plan and place procurement orders for the future, because, she believed, they 147

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expected the Fund would rescue the government again in an emergency. This raised the question that some engaged with the Fund called a “moral hazard,” a situation when one party takes a risk believing that the other party will bear the cost of the risks. Would the Fund’s (or indeed any external donor’s) continued engagement contribute to lack of political will by former aid recipients to take increased responsibility for their disease responses? Meanwhile, other countries were waiting in the wings: uppermiddle-income countries currently ineligible due to the various exceptions in the eligibility policy, but with rising HIV rates among key populations and vulnerability to economic shocks that could spark a crisis in the future. In response to documented issues with abrupt transitions out of countries such as Romania, in 2016 the Board passed a Sustainability, Transition and Co-Financing (STC) Policy. This listed a set of measures countries should take to prepare to transition out of Global Fund support (The Global Fund 2016d). Early reports on the policy’s implementation were setting off some alarm bells for civil society groups and researchers: countries had gaps in data and national planning processes, and lack of information for civil society groups about what the national transition plans were and whether key populations services would be covered (Sustainable HIV Funding in Transition [SHIFT] and Australian Federation of AIDS Organisations [AFAO] 2018; Oberth and Whiteside 2016; Burrows et al. 2016). In 2017, with the eligibility discussions kicking off, the Global Fund Secretariat insisted it was too early to judge the impact of the STC Policy, which had only just been approved. In Southeast Europe, there had been some more successful transitions, thanks in part to civil society advocates who had received small amounts of bridge funding that enabled them to work closely with governments and coordinate the transition process (Open Society Foundations 2017). But overall, the feeling was that while parts of the global HIV response were ticking along as planned, significant parts were veering close to crisis. The civil society delegations hoped to course-correct through the Eligibility Policy. THE THREE DELEGATIONS

The timeline for the work on the Eligibility Policy was going to be tight. The Board’s policies are first worked out through standing 148

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committees, including the Strategy Committee, Audit and Finance Committee, and Ethics and Governance Committee. The Strategy Committee would develop the proposed revised policy. They had already begun discussing broad principles and would agree on these at a meeting in Geneva in October. The Strategy Committee would share their recommendations with the full Board when it met in November, and would aim to get the green light on these so that they could move onto the finer points of the revisions in the spring, with the proposed new policy scheduled for approval by the Board when it met again in Macedonia in May 2017. Assuming that all went according to plan, based on the Eligibility Policy, the Strategy Committee would then have a year to revise the allocation methodology, determining how much funding each eligible country could receive. As noted in the first chapter, the Global Fund Board is huge and has a uniquely inclusive structure, which includes voting roles for civil society. There are twenty voting Board Members leading larger constituencies: ten donor seats, and ten implementer seats. Each delegation of between ten and twenty delegates also leads a larger constituency of countries or organizations. Board Members vote on decision points on behalf of their delegations. The three representatives from civil society and communities include a Developing Country NGO Delegation, representing civil society organizations in all of the countries implementing Global Fund financing; a Communities Delegation, representing communities living with and affected by the three diseases; and a Developed Country NGO Delegation, representing all countries not implementing Global Fund grants. Together, the civil society and communities delegations make up several universes of individuals, organizations, and networks, thousands of them, from small community-based groups in African deserts, to vast urban networks of people living with HIV in Eastern European metropolises, to international associations of health professionals. While there are only three civil society delegations, as noted in the first chapter, the Global Fund Board was intentionally designed to give them real power. In cases where the Board fails to reach consensus, motions that go to a vote require a two-thirds majority of both the implementing and donor groups to pass. If all three civil society delegations joined together and won support from one other implementing country, the implementer half of the vote would not pass and the motion would fail. 149

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This implied threat of a blocking minority is almost never used in practice, but its implicit power, and the role of civil society in giving the Fund legitimacy with donors, gives them a certain amount of clout on the Board. The Global Fund counts on civil society to advocate with donor governments to renew their financial pledges every three years; if they truly lost faith in the Global Fund, civil society could refuse to go out and push for replenishment, and this would almost certainly lead many bilateral and foundation donors to lose faith. But that outcome would be a disaster for Rico Gustav’s Communities constituency, he said: “If the money does not come in, it’s peoples’ lives.” In 2017 I was hired for a consultant role for the three delegations. I worked with their three leaders: Allan Maleche from Developing Country NGOs, Rico Gustav from Communities, and Mike Podmore from Developed Country NGOs (see Figure 6.1). I have introduced Allan previously. Rico, who was diagnosed with HIV at the age of seventeen, is an Indonesian activist in his midthirties who came up through community-based organizations working with people who use drugs. His intellectual brilliance – he had previously studied mathematical formulations of quantum mechanics – was balanced with a strong sense of absurdist humor. After doing peer outreach work for many years, he went on to jobs in the UNAIDS country office, and then to regional advocacy work and a series of international organizations. He also had a coveted seat on the powerful Strategy Committee, so his was one of the voices the three delegations could use in shaping the Eligibility Policy. He said: The Eligibility Policy is important because it determines who’s in and who’s out. [It’s] about how Global Fund decides who lives and who dies, and how they prioritize their resources. So it is important for us to actually make sure the policy is as global as possible, to make sure all our constituency comes into that picture.

For the work on the eligibility policy, Allan and Rico would join forces with the Developed Country NGO Delegation. This built on earlier work they done together earlier in the year as part of a working group that included other delegations, which had identified the Eligibility Policy as being a key problem in regard to long-term sustainability of national disease programs. In 2017 the lead for this work was Alternate Board Member Mike Podmore, whose work on the policy helped him win election to Board Member in 2018. Mike is a British activist in his midforties who 150

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brought a keen instinct for common sense and strategy, and a helpfully deep vein of stubbornness. He noted this quality was evident when he was a teen who was small for his age, but still played in his school rugby team, moving fast and never letting go of the ball in the face of hulking opposition. He had a postgraduate degree in development, and had also worked for several international organizations before his appointment as director of STOPAIDS, a British network of seventy international organizations working on HIV globally. Like Allan and Rico, he was a quickly-rising figure in the global HIV advocacy world, increasingly invited to speak to Parliament and other government meetings on health aid. Allan, Rico, and Mike were from three different geographic regions, and had come to the Fund from different life paths, but they found commonalities sitting together at the Board table: they were all dedicated fathers of young children, with careers on the rise, a shared passion for the cause, a knack for working a room, level-headed temperaments, and quick senses of humor. While I tended to get immersed in the minutiae of policies, Allan did his perennial scan for pragmatic, forward-looking solutions; Mike had a cool strategic view of the playing field; and Rico brought in flashes of insight, thinking several chess moves ahead. As Mike put it, “We’re more effective when we work together.” Rico agreed: “[Communities Delegation] can bring the human face into the conversation, but sometimes we don’t also have that technical perspective from the donor country side, or the narrative that actually can work for implementing governments.” For Allan, “speaking with one voice” to the donors was always the goal. Maintaining this unified voice among three large and sometimes fractious constituencies of strong-willed activists is no simple feat. It takes sophisticated leadership skills to pull off that kind of unity within one country. Here, the constituencies represented broader transnational coalitions of activists riven by differences of nationality, language, class, race, gender, gender identity, sexual orientation, HIV status, priorities, and agendas, and all with diverse experiences of discrimination, exploitation, and exclusion. Rumors and allegations flew fast across social media and WhatsApp chat groups, and keeping their constituencies working amicably toward shared goals required intense efforts from all three of my clients. When the three representatives sat at the “Board table,” the octagon of seats where voting Board Members have the microphone and the vote, decisions moved quickly, allegiances and 151

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moods shifted rapidly, and politics was played at a high level. Meanwhile, their delegations sat behind Allan, Rico, and Mike in the board room, or in a nearby live transmission room, or followed along in other countries, watching anxiously and sometimes texting and emailing them with talking points or reactions. The Strategy Committee was a smaller group of Board delegates, but a powerful one, and they were due to meet in October. The Implementers Group would meet the week before. It was agreed that Mike would be the focal point for the project. In early September, Mike and I raced to set up our first call around his packed travel schedule. After attempting to shout through the line while he rode the London tube and getting cut off, we wound up talking while he sat on the sidelines of his daughter’s tae kwon do class. The plan was for the three civil society delegations to present a joint position to the Implementers Group in Bucharest in late September, aiming to align the ten implementing delegations on the Board around their shared position. The donors and others would have teams to analyze options, run numbers, and generate different scenarios for possible changes to the policy, but the civil society delegations had just one part-time consultant. “First off, we’ll need you to do a background report for our meeting with the Implementer Group,” said Mike, over the echoes of children shouting in class, as I scribbled. “What were the historical changes to the Eligibility Policy and what were the reasons for them? What is the history of countries’ eligibility? Go through the old eligibility lists and see if there are any patterns. And we’ll need a few case studies to really show the impact of the policy.” We had heard reports that the donors would push to simplify the many interlocking criteria on the policy and rationalize it to make it more consistent. On the face of it, this was sensible, but the simplifications being considered could result in a few more countries becoming ineligible. There were concerns about Indonesia, which has high prevalence of HIV among key populations, but whose rising GNIpc might soon see it fall under one of the rules that excluded certain uppermiddle-income countries. We also had heard that there were ominous questions being asked about a rule that preserved eligibility for small island economies, like Grenada. We talked about possible countries for case studies. I suggested Russia. As noted above, HIV is spiking there among key populations, especially people who inject drugs. While the country is technically no longer eligible, there is a policy exception, the NGO Rule, which 152

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had previously allowed Russian civil society groups to qualify for a small amount of funding for legal aid, advocacy, and harm reduction work. I suggested it could be a good place to highlight the positive impact the Fund can have with a small grant to a middleincome country. It was also timely: Russia’s eligibility was ending soon, and in three months, thousands of people who use drugs would be without harm reduction services. There were rumors that some people wanted to cut the NGO Rule out of the policy altogether, because it was a small amount of money, therefore unlikely to deliver large numbers of lives saved, and Russia’s government strongly objected to it. Meanwhile, Mike said, the Board was going to tackle the problem of Venezuela again, where things were getting worse. Despite the suppression of official medical data, a courageous Venezuelan doctor had presented research in Paris showing total stockouts of antiretroviral medicines for more than seventy thousand people living with HIV, as well as long-term lacks of diagnostic tests and other medicines. Measles and diphtheria, once eradicated from Latin America, were resurgent, as was malaria (ICASO and ACCSI 2018). After a May decision point on emergency funding failed to pass, the Board had established a separate working group to develop an approach to “non-eligible countries in crisis,” including Venezuela. Jorge Saavedra, a Mexican medical doctor and researcher working with AIDS Healthcare Foundation, was a member of the Developing Country NGO Delegation led by Allan, served on the Strategy Committee with Rico, and had been appointed to this working group. Saavedra had been invited by community activists living with HIV to visit Venezuela in 2016. He had been harrowed by the deprivation and suffering he had witnessed there and had become one of the leading champions on the Board for emergency funding to the country. In the world of global health politics, establishing a working group was a victory: it meant there was hope that a solution might be found. “What is the problem we are trying to solve?” asked Mike, thinking about the big picture. “The problem is, we’re not going to be able to deliver on the Global Fund’s strategy with this approach. Lots of countries are being cut out by eligibility. PEPFAR is now focusing on just thirteen countries – all the more reason for the Global Fund not to do the same.” Mike’s daughter ran up then, breathless with excitement. Tae kwon do was done for the night, and they had to go to home to deal with 153

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dinner and bedtime. We would follow up via email. Mike was getting ready to travel again, while I was heading to Nairobi to work with KELIN to write up their report on biometrics. “Can you get me a draft of the background report in a week?” Mike asked. No problem, I said. While standing on the security line in Geneva’s airport, nudging my carry-on bag along with my knee, I began speedreading eligibility policies and board reports on my mobile. While the Global Fund is relatively new, the problem it faces is not: How do you prioritize in a health crisis? This is not just a question of resource allocation but also an ethical question – one of the most persistent and troubling in health policy. The Eligibility Policy, as I read through its multiple iterations, is an interlocking set of indicators and exceptions, with each part of the policy dependent on some other part. But it hadn’t started out that way. The Fund began small, and its early approach was a set of fluid principles designed to ensure maximum discretion in response to a global pandemic, a humanitarian crisis. Over fifteen years, these fluid principles had become a rigid jigsaw puzzle of indicators and rules. This was a perhaps natural result of its shift from being a small emergency fund with millions of dollars to manage, to a large bureaucracy handling billions. Most of these rules were contortions created to address a problem created by one of the criteria in the policy: the problem of middleincome countries. To understand how these indicators and exceptions developed as levers to steer funds toward an ever-narrowing group of countries, it’s necessary to see how the Fund grew and how its role changed from a small fund for emergencies to providing core support for health programs in dozens of countries. FROM FLEXIBILITY TO A JIGSAW PUZZLE OF RULES

When the Global Fund was founded in 2002, it was in a world without indicators. Gradually, over time, these were added on, piling one on top of another, to manage the complex needs of both donors and implementers. The Global Fund’s Framework Document is an inspiring document to read: it reflects the activist energy, optimism, and urgency of its founders. I had visited the Fund’s then small office in Geneva in 2003, as a researcher on China at Human Rights Watch, and met a young official who was proud to share that the Fund’s grant documentation 154

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and policies were all published on its website. He said, “The Global Fund was created to be different” from other global governance agencies, committed to transparency and accountability. The Framework Document set out flexible criteria for eligibility, to be determined by the Board. It left open the option that the agency could fund not only governments but also directly fund civil society groups; it created exceptions for countries in special circumstances and an appeals process for unsuccessful applicants (The Global Fund 2001). The Fund had given several grants directly to coalitions of civil society groups in some cases where governments failed to work with civil society, for instance in Thailand, where people who use drugs were excluded from government partnerships and won the right to receive their Global Fund financing directly (Kerr et al. 2004). The early days of the Fund were euphoric, remembered Michel Kazatchkine, then a French diplomat appointed to the Board as one of its founding delegates. In the early days, he recalled, “No one thought there’d be serious money: the kind of money that could turn around the trends of the epidemic globally.” The organization was small, and it was moving at high speed; he was asked to head the Technical Review Panel (TRP), a team of external experts that reviewed applications and recommended the strongest ones for funding. He recalled, “At the first grant-making, countries had four weeks to apply, and the peer-review panel had two weeks to review. It was urgent humanitarian work. . . . We were in high spirits.” With this dynamism and sense of urgency, and the backing of a strong network of advocates at all levels, the Fund grew rapidly. At a Board meeting in 2003, members debated over how to prioritize among applicants for its available funding – in its first two years, the agency had signed grants of $32 million among twenty-seven countries (The Global Fund 2003, 9). Moving forward, should they focus on the “poorest and neediest countries” or prioritize proposals that had previously failed? Some noted that there was no clear strategic vision yet to guide priorities. And how would they manage conflicts of interest, as some of those approving funding on the Board were also becoming implementers of funding? The Board discussed these questions, and delegated the Secretariat to meet with the World Bank and other partners to draft a policy (The Global Fund 2003, 12–15). This eventually produced the first of the Global Fund’s Eligibility Policies, revised periodically to reflect the changing epidemics and 155

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changing strategies (The Global Fund 2007). A decade later, $32 million, the amount of grants given in 2003, is about the amount of a line item in the budgets of some high-prevalence countries. But as the money grew, paradoxically, the demands grew also. Prioritizing did not get easier. There were more organizations dependent on the Global Fund to meet their payrolls. In the first decade of operations, under the flexible approach to awarding funds, to be eligible just meant that when the Global Fund announced a new competitive round of funding, a country could submit a proposal for review. From 2002 to 2012, the Global Fund issued calls for proposals, applicants applied, and those assessed as strongest by the TRP received some portion of available funds in a given replenishment cycle. Over time, though, it emerged that this was an approach that favored those countries that could write strong proposals – because they had either strong support from some international agency, or the resources to hire sophisticated proposal writers who would hole up in a hotel room for a couple of weeks and produce a funding request, with little interaction with anyone in the country. As a result, some countries were very successful: in fact, some received disproportionately high sums relative to their disease burdens (Dieleman et al. 2014; Burrows et al. 2016). Flexibility did not necessarily ensure fair resource allocation, and left a lot to the discretion of individuals. In January 2011 published reports of fraud and corruption sparked a public debate over whether Global Fund financing was at greater risk of corruption or was simply being more transparent about the corruption it had found than were other aid agencies. Several months later, Round 11 of funding proposals was launched, and abruptly cancelled due to a gap between overcommitted grant funding and inaccurately forecasted revenue. Kazatchkine, then executive director, resigned under pressure from the Board (Couronne 2015). The Global Fund went through a period of crisis, with less funds disbursed through a transitional mechanism. An extensive external consultation and restructuring was led by a general manager who was also a former banker, Gabriel Jaramillo, and a team of management consultants. Three years later, the Fund made the decision to shift to an allocation approach. With available funds of $14.82 billion, 20 percent more than it had ever disbursed before, the Fund would determine which countries and disease programs were eligible using the Eligibility Policy. The Secretariat would divide the 156

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$14.82 billion among the three diseases, and then allocate funds across groups of countries and individual countries using a complex mix of mathematical algorithms and qualitative factors approved by the Board (The Global Fund 2014a, 3–4). Over a decade after its launch, the factors first set out by the World Bank and others continue to frame Global Fund eligibility. Faced with three quite different diseases that largely track the vectors of inequality, poverty, human rights abuses, and discrimination, national income became the paramount criterion, with other indicators and rules used to sort through the middle-income countries. The next section explores some key indicators used in the policy, as well as the challenges they create. KEY ELEMENTS OF THE ELIGIBILITY POLICY

As described in Chapter 1, the first cut in eligibility is made by a single numerical indicator, GNIpc. The World Bank calculates GNI per capita as the sum of value added by all resident producers, plus any product taxes (less subsidies) not included in the valuation of output, plus net receipts of primary income from abroad, including employee compensation and property income (The World Bank 2019). Most countries report data that the World Bank can use to assess their GNIpc, and one of the important factors in selecting eligibility criteria was the availability of data. When there is enough data, an indicator can take on a life of its own. While it was a crude indicator of “ability to pay” for health, enough countries consistently reported enough data on it, and enough donor countries had incorporated it into their policies, that GNIpc had been widely accepted as a reliable criteria to use for eligibility across a range of funders. Under the Global Fund’s Eligibility Policy, all high-income countries are automatically ineligible, while all low-income countries are eligible. Middle-income countries are a vast range of diverse countries, from deserts to farmland, from small islands to huge and diverse nations, from settled states to countries riven by active armed conflict – essentially, a long list of places whose only shared feature is that their GNIpc falls within certain limits. The World Bank had created a wholly imaginary category, the “middle-income countries,” a vast grouping of countries that have little in common, which the Global Fund had to use a raft of other indicators and rules to sort through. Critics have pointed out three key problems with GNIpc as a tool for determining health aid eligibility. 157

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First, the classification of a country as low, middle, or high income is arbitrary. As Jorge Saavedra, a member of the Developing Country NGO Delegation to the Board, noted when we spoke on July 1, 2019, “When you see just the numbers from the less developed country to the most developed country in the world in terms of economy, the middle is not $1,025, which is when a country starts being classified as middleincome” (see Table 6.1). Countries may also veer over these thresholds due to unpredictable shocks, such as a hurricane or a military coup. Second, a problem with using it to decide whether or not to allocate health aid is that GNIpc does not reflect how income is distributed across the country, or the need for aid to address poverty or structural changes (Glennie 2013). An estimated one billion poor people, or more than 70 percent of the world’s poor, now live in middle-income countries (Sumner 2010, 2012). Large middle-income countries are significant contributors to the world’s poverty and the global burden of disease, creating a “new geography of global poverty” (Kanbur and Sumner 2012; Ottersen et al. 2017). But at the lower end of the middle-income country classification, even if wealth could be redistributed equally, Saavedra argued, “You don’t get rich people, not even middle income people; you get poor people.” This inequality is linked to poor health equity (Ottersen et al. 2017, 266). South Africa, for example, is one upper-middle-income country with a higher under-five mortality rate than several low-income countries (Ottersen et al. 2017, 270). In Africa, Allan noted, “you [have countries] such as Botswana, South Africa, Nigeria, who despite reaching the upper-middle income threshold . . . also remained having high burdens. So we still need not to either lock them out or reduce their allocations.” Although economic data may be more reliable than some other kinds of data, it also has gaps; the third problem for GNIpc as a sole determinant of eligibility is created by flawed economic and demographic data. As Jerven (2013) shows, unrecorded economic TABLE 6.1 World Bank Country income classifications by income level, 2019–20 Threshold

GNI/Capita (current US$)

Low-income Lower-middle income Upper-middle income High-income

< 1,025 1,026–3,995 3,996–12,375 > 12,375

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activity, and arbitrary political decisions that shape quantification and aggregation of economic data, all create sharp differences in how GNI is estimated across countries. When countries rebase their GDP (that is, recalculate it based on updated information and assumptions), their estimated GDP may change significantly (Dolan 2016). Some countries have been accused of manipulating GDP to either artificially inflate growth, or to deflate it and remain eligible for international assistance (Kerner et al. 2017; Martinez 2017). Moreover, measuring “per capita” is also problematic in many countries which lack an accurate census. In Nigeria, one of the largest Global Fund recipient countries, active conflict and political contests in certain regions impeded an agreed national census for decades; in India, another major recipient, nearly two million people were left off a register in an effort to eliminate illegal migration (Aluko 1963; Fawehinmi 2018; Bhattacharya 2019). Thus, Saavedra frequently noted, the World Bank themselves considered numerous other political and economic factors beyond GNIpc in determining which countries to transition from (World Bank 2016). In the Eligibility Policy, as the only economic criterion considered at all was GNIpc, the Fund needed another way to sort through the morass of middle-income countries (see Figure 6.4). Thus the policy applied a second indicator: disease burden. To be eligible for funding for HIV

High-income country?

Yes

Not eligible

Yes

Eligible

Yes

Apply other criteria to determine eligibility, such as: • Disease burden • G-20 • OECD DAC List • Small island economy • etc

No

Low-income country?

No

Middle-income country

Figure 6.4 Diagram of Global Fund eligibility assessment 159

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programs, upper-middle-income countries needed to demonstrate that they had a “high, severe or extreme” disease burden, defined as national HIV prevalence of greater than 1 percent, or prevalence in a key population of greater than 5 percent, based on data provided by WHO and UNAIDS (The Global Fund 2016). Here there was a second problem for many countries with concentrated HIV epidemics, the one discussed earlier in this book: for criminalized key populations, there was often no data on HIV. Because lack of data was treated as a zero by the Global Fund, countries that might otherwise be eligible were disqualified when they had no data on key populations. Here the data paradox was appearing again, in which denialism and criminalization led to lack of data on key populations, and this absence was reinforced by lack of resources. As noted in Chapter 1, this lack of data on key populations had been one of the factors keeping Venezuela ineligible. In addition to the two indicators, GNIpc and disease burden, numerous other rules and exceptions had accumulated in the policy in order to enable the Global Fund to sift through upper-middle-income countries and determine which should be eligible. An upper-middle-income country could be a “small island economy,” under a rule added in 2006, early in the Global Fund’s history, to keep some funding going to small Pacific and Caribbean countries. This recognized that despite high income, smaller countries often lacked technical and financial resources to do all the things needed for HIV, TB, and malaria. The rule allowed the Eastern Caribbean countries, such as Grenada, to apply collectively for shared funding. In 2017 some people connected to the Fund were quietly asking about the cost-effectiveness of continuing to invest in these small, expensive countries. Another rule made any upper-middle income country that was a member of the Group of 20 noneligible, unless it had an extremely high disease burden (The Global Fund 2016, 8). This was a rule that had been added to keep some countries with high disease burden and large populations off the list, because their large size meant they would receive a large allocation. A third rule advocated for by donors was added to state that to be eligible for HIV funding, countries needed to be on the list of countries approved by the Organization for Economic Cooperation and Development (OECD)’s Development Assistance Committee (DAC) (The Global Fund 2016, 8). This rule more closely aligned the policy 160

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with the overseas aid policies of bilateral donors to the Fund. After this new rule made Russia, Bulgaria, and Romania ineligible, because they were not on the list, national HIV programs in Russia financed by the Global Fund began drawing to a close. The Russian government, despite pledges to fund HIV services, had not taken steps to do so. To compensate for these cuts, an NGO Rule was put in place by Kazatchkine, at the time executive director of the Fund, with support from civil society. The countries excluded from the OECD DAC list could still be deemed eligible for an allocation for HIV only if the country had a sufficiently high disease burden, and only if the country confirmed that the allocation would be used “to fund interventions that are not being provided due to political barriers and are supported by the country’s epidemiology”; if the country could confirm that the funds would be submitted by a multi-stakeholder coordination body and managed by an NGO; if the government would directly receive no funding; and if the applicants met other conditions aimed at ensuring long-term sustainability (The Global Fund 2016, 9). The term “political barriers,” in a footnote of the Eligibility Policy, had no definition under international law and had never been clearly defined by the Global Fund. The vague term gave the Global Fund Secretariat leeway in deciding whether countries should be determined to be eligible. In practice, only Russia ever had been, from 2014 to 2016, because its national laws limited provision of harm reduction services. Romania and Bulgaria were not on the OECD DAC list, and both did have high HIV burden, but both were assessed as ineligible by the Global Fund Secretariat due to lack of the undefined “political barriers” (EHRN 2015, 2016). In the discussions with Mike, Allan, and Rico, I mentioned that I had gotten to know some of the Russian activists involved in the NGO Rule grant. A relatively small grant of less than $11 million in a large country had been used to build national networks into a coalition. The grant brought together networks of key populations and people living with HIV, who worked together – as well as with provincial and local officials, police, and health care providers – to gather data, advocate for human rights and law reform, and provide harm-reduction services to some twenty thousand people who inject drugs. Financing for some of the services was taken on by local, provincial, and national authorities. One of the Russian funding implementers shared the Global Fund’s written evaluations of the program, which said that the community systems strengthening and human 161

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rights interventions had had “excellent results” (The Global Fund 2017d). Despite this, the activities would come to an end when the grant closed in December 2017, without any alternate sources of funding identified to keep the programs going. Russia had lost its eligibility when its GNIpc veered up to $12,700 for one year. The next year the income had dropped again, but that one year of high income was enough to end the country’s eligibility. The clock was now reset on Russia, which would need two years of classification as a middle-income country in order for civil society groups to be able to apply under the NGO Rule again. Word was that some key players working with the Fund were hoping the NGO Rule would be cut out before that could happen, when the Eligibility Policy was revised. It was cumbersome work for the Secretariat to manage a relatively small amount of funding unlikely to deliver large numbers of “lives saved.” Moreover, the grant was politically sensitive, and Secretariat staff were also needed to work on high-prevalence countries with large populations and large allocations, some of which were not performing very well. The Global Fund strategy committed to focusing on locations and populations most vulnerable to the three diseases, but the Eligibility Policy was focused on nation-states. The use of GNIpc as the first cut among those states ensured that would continue to be the focus: data on GNIpc was reported by most countries, and the indicator was used by most donor states. GNIpc was a blunt instrument and was being put to tasks for which it had not been designed. But the more data countries reported against it, the more power the indicator had as an analytical tool. It is a problem when absence of evidence is used as evidence of absence, but sometimes having a lot of data can cause problems as well. ALTERNATIVE INDICATORS

As I summarized for Mike, Allan, and Rico what I had seen in the evolution (or devolution) of the policy, and all the interlocking aspects of the indicators as well was what they failed to capture, Mike asked, “Has the Global Fund ever looked at other indicators?” They had, through the Equitable Access Initiative. We took a look at that report. In 2013 then executive director Mark Dybul recommended to the board that the Fund develop a multi-tiered pricing framework, a multistakeholder initiative that would have included some pharmaceutical 162

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companies (The Global Fund 2013a, 7). Civil society advocates and some government officials raised concerns that a tiered pricing system would hamper access to treatment in middle-income countries (Barton 2014; Saez 2014). In response, Dybul revised the plan to look more broadly at the problem of access to commodities in middle-income countries (The Global Fund 2014b). As this was discussed, the objectives of the initiative were changed to focus on considering alternative indicators beyond GNIpc. The project was launched in 2015, and brought together the World Bank, GAVI, UNAIDS, UNDP, the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), Unitaid, the Global Fund, and WHO (The World Bank 2016a, 4). The Equitable Access Initiative panel, headed by a former head of the World Trade Organization, recruited four academic research teams to develop options. In reviewing their reports, the panelists concluded that “the largest share of disease burden is now concentrated in middleincome rather than low-income countries, a reality that GNI per capita alone cannot capture” (ibid.). While GNIpc “continues to be relevant, it may be inadequate” as the principal basis for determining aid eligibility (ibid.). Rather, the panel recommended that policy-makers develop “a more comprehensive framework for decision making that accounts for countries” position on a health development continuum, based on the analysis of countries’ needs, fiscal capacity and policies” (ibid.). This seemed like a sensible recommendation. However, it was not taken on. The Global Fund made just one change, adopting “a rolling average GNI per capita” that used three years of income data, instead of only one year (The Global Fund 2016, 4). This slightly slowed transition for some countries, but the recommendation to develop a comprehensive framework was not adopted. The Equitable Access Initiative had been largely imposed on the Global Fund, and its resulting recommendations would have undone the delicate balance between diverse interests that made the Eligibility Policy a workable compromise. This GNIpc, income classification modality was difficult to shake, in part because it aligned with the concept of a “development continuum,” the idea that countries “move up” a ladder of development, growing in income, until they become upper-middle163

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income and “graduate” from development aid. However, as Jonathan Glennie notes, this model does not apply to the health sector: There is no typical route for the development of health provision – there are a range of policy responses which can often be better grouped by region or political system than by some kind of income-related “continuum.” And this is clearly the case in work around HIV and TB which requires working with communities and key populations, addressing stigma and discrimination and deeply rooted obstacles in gender equality and systemic obstacles around human rights. (Glennie 2018, 4)

The notion of a linear “development continuum” that underlay the Global Fund Eligibility Policy was a hangover from a previous era of international development, one that no longer fit the fluid twenty-first century world of globalization, mobility, and transnational epidemics. When a basic scientific premise does not work, it gradually produces a crisis; for example, when the world accepted astronomer Ptolemy’s theory that the sun orbited the earth, his followers had to develop numerous exceptions to explain away all the data that clashed with this incorrect theory. As Zizek notes, a Copernican revolution “takes place when, instead of just adding complications and changing minor premises, the basic framework itself undergoes a transformation” (2008, vii). I recommended to Mike, Allan, and Rico that they should push for a Copernican revolution in eligibility. The Global Fund should eliminate GNIpc altogether in considering country eligibility. Instead, the Fund should put disease burden first, and fund everywhere where there was high disease burden in the general population or among key populations. The Fund could then use a more nuanced analysis of the economic resources available and the political climate in countries where disease burden was not high, which would be a subset of countries. They could decide on eligibility in those countries on a case-bycase basis and tailor their investments to the specific needs – for instance, funding civil society groups where governments were reluctant to address needs of key populations, as in Russia. The Fund could transition out of countries only once it seemed that the epidemics were under control. This approach would entirely eliminate the false category of middleincome countries, which, I argued, did not really exist. The diverse middle-income countries had almost nothing in common: they were an 164

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artifact of the GNIpc indicator and of the World Bank’s income classification system. We agreed that this approach would be logical, but also that it would never be accepted. Rico’s delegation was concerned that it might still leave upper-middle-income countries out of eligibility. There would still need to be a solution for countries where there was no data on key populations. He suggested they try to persuade the Implementers Group to at least recommend that the Fund find a better approach to assessing income classification than the blunt tool of GNIpc. Mike, Allan, and Rico agreed to raise the concerns about GNIpc in their presentation to the Implementers Group, referencing the Equitable Access Initiative report. They would push for an approach recommended in that report, which was to analyze fiscal space for health. The World Bank had itself outlined an approach to doing this, which analyzed macroeconomic conditions, national budgets, tax policy, and other factors; in fact, the Global Fund’s own health economist co-authored a study recommending something similar (Barroy et al. 2017). My three clients also agreed to argue for eliminating the G-20 and OECD DAC exclusions, bringing the excluded countries back into eligibility again. They agreed to push to retain the small island economy exception that kept Pacific island and Caribbean countries eligible. They would push to slow transitions down so that these were less abrupt. Lastly, they agreed to propose a clause to address middle-income countries where a lack of data on key populations kept upper middleincome countries ineligible. Referencing Greenall and Baral’s blog about the data paradox, we called this the “where there is no data” clause, soon shortened to just “no data.” We discussed the work of health economists who had debated the balance that should be struck between cost-efficiency and equity at the national level. In a context of sparse resources, these health economists had asked, do you invest in the cheapest interventions that have the most impact (cost-effectiveness), or do you ensure at least some key services of varying cost to all those that need them, wherever they are (equity)? Some had argued efficiency should always be balanced against ethical and social principles (Berghmans et. al. 2004; Brock n.d.; Cookson et. al. 2010; Johanssen and Norheim 2011; Pinkerton et. al. 2002; Williams 1992). Certainly, it seemed important to weigh explicitly what the tradeoffs would be in a context of rationing, to have a robust discussion about the underlying bases for making such difficult decisions, and to properly 165

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discuss the new UNAIDS data that reported spiking incidence in regions where the Fund had or was currently transitioning out. This was the question Mike kept asking: “What is the problem we are trying to solve?” The meetings ahead, with the Implementers Group and the Strategy Committee, were short meetings with much at stake: by selecting indicators and economic criteria, significant resources could be shifted in one direction or another. Though my three clients, all managers or directors at small NGOs, were vastly under-resourced in comparison with others at the table, they had the backing of the broader civil society movement that had put them there and would hold them accountable for the results. THE GREAT WALL

“Session went great,” Mike texted me on September 22nd, after the Implementer Group meeting ended. “There was general agreement to [invert] disease burden and GNI.” An intense but upbeat flurry of messages flew among the three delegations. The following week, Mike was asked to speak at the OECD on transitions. He reported afterward with excitement that middle-income country representatives around the table there had expressed widespread dissatisfaction with the eligibility and transition processes, blaming the current development cooperation paradigm for being stuck in the twentieth century. He said they had made strong calls for a new development approach. This was the euphoric mood when Jorge and Rico sat down at the Strategy Committee meeting in October, with the backing of the Implementers Group, to start the discussion about general principles in the Eligibility Policy: beginning with whether to continue using GNIpc. Mike and Allan sat in as observers; they would not be able to speak in the meeting, but could support Rico and Jorge as needed. I stood by at home, waiting for questions by text message or email, and stress-baking cakes to cope with the anxiety. The discussion did not turn out the way they hoped. After the meeting concluded, Mike, Allan, and I sat huddled on my balcony, grim and silent on a chilly night with Chinese takeout and a large quantity of cake; Rico had flown home. A later update to the Board, published by the Secretariat, summarized the results of the Strategy Committee’s deliberations. 166

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Actually, all you really need to see is one slide. The slide laid out a kind of Great Wall of GNI per capita, asking the rhetorical question, “Why GNI?” On the Great Wall were the answers: “Country validated, predictability, stability, proxy, alignment” (The Global Fund 2017e, 10; see Figure 6.5). The presentation said that the Strategy Committee had “confirmed the continued use of GNI per capita (3-year average) as a measure for economic capacity. Despite noted limitations, GNI per capita remains best available measure to quantify average economic capacity in a country” (ibid., 9). Mike had had to sit on his hands during the Strategy Committee deliberations, unable to speak in his role as an observer. He found it frustrating that in briefing the committee, the Secretariat had presented the findings of the Equitable Access Initiative to say that the EAI found that [GNIpc] was the most reliable indicator, which it did say. But [the EAI] also said there should be a range of other indicators that should complement it, because it’s insufficient on its own. This was completely ignored in the presentation and the discussion. We made really very little progress on that, trying to get anything else on the table.

Why did the Secretariat omit these more nuanced findings that GNIpc was insufficient on its own to measure country economic capacity? Mike, Allan, and Rico agreed, separately, that this was an attempt to

1

Economic Capacity Capturing economic capacity using GNI per capita: Why GNI?

Produced by the World Bank jointly with National Statistics Bureaus

Produced annually, publically available and based on a transparent methodology Relatively less sensitive to volatility than GDP or GNI growth rate Measures output produced by residents in the country and abroad Developed by WB in 1981 to inform operational lending by IDA and IBRD

Country Validated Predictability Stability Good Proxy

Alignment

Figure 6.5 Global Fund presentation on rationale for GNIpc. Credit: The Global Fund

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steer the conversation in such a way as to reinforce the status quo and avoid triggering an open conflict on the board that might potentially alienate the donors at a delicate moment. Donors had made it clear they wanted to continue the gradual reduction in the list of countries, and certainly not expand it. Adhering to GNIpc, not making any major changes to the policy, made this feasible, without rocking the boat. Allan said that “a number of donors felt that the job had been done in certain regions, particularly Eastern Europe and a bit of Latin America,” while other donor representatives on the board were operating under strict instructions from their capitals to “focus on Africa, or on specific regions in Africa.” This was, Mike reflected afterward, certainly the attitude of the British government at that moment: in the controversy surrounding Brexit, the UK was playing to an increasingly conservative British electorate whose reluctance to “fund countries like India with space programs” had been egged on by misrepresentations about aid in the media. Rico reflected later that despite efforts on the Board to give civil society a meaningful role, “money and funding is an unregulated power in any kind of board”: There’s a lot of protocols to make sure that the tables are even. But the tables are not going to be even, right? . . . If donor countries say “Well, we’re not going to give funding to this,” then it’s going to be difficult. So those who are not bringing any money to the table, we have to work extra hard to actually put our argument.

A fuller and franker discussion about the different perspectives of each constituency would have helped build what Mike called “epistemic trust” among the diverse board delegations: Unless you do that, you never understand each other. You assume nefarious motives. . . . [If we had had], as we had asked for at the start of the process, an open, getting-back-to-basics discussion laying out our assumptions and the principles we should apply for making decisions, we may not have agreed at the end, but at least we would have understood each other.

Sands joined the Global Fund after the policy was approved. As a relative newcomer to global health when we spoke in 2019, he also said he felt a need for a franker discussion about the trade-offs: “In the business world, metrics and KPIs and investment cases are used not just 168

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to make the case for doing X, they’re used to say should we do X rather than Y.” Told that a civil society delegate had said almost the same thing, he replied, “I’m not sure all would be comfortable with a discussion like that,” but acknowledged, “it’s easier in the business world, when you’re thinking about the return on investment of doing X or Y, than it is in the global health world, because the return on investment is essentially lives. And it’s right that we are uncomfortable making those trade-offs. But the reality is, we are making those trade-offs.” * As Allan and Mike flew back to their own countries, and Geneva’s gray chilly autumn sank in, I got an email from Mikhail Golichenko. A former police officer, he had served as a UN peacekeeper in Liberia, where he first was inspired to work on human rights. He was in Geneva for advocacy work. Anya Sarang, president of the Moscowbased Andrey Rylkov Foundation for Health and Social Justice, was with him. She was an award-winning leader of the harm reduction movement in Russia, a dedicated activist with a contagious smile running the only harm reduction program in Moscow. Mikhail was leading a legal technical assistance project for the Canadian HIV/AIDS Legal Network, and he and Anya were in town for the UN Committee on Economic, Social and Cultural Rights periodic review of Russia’s compliance with the International Covenant on Economic, Social and Cultural Rights. They had been joined there by some Russian key populations activists whose travel was one of the last activities under the Global Fund’s program in Russia. We met at a British pub. At a wooden table below a giant TV screen, we shared French fries and talked about what the chances were of the NGO Rule being kept in the next Eligibility Policy. Doing harm reduction and human rights advocacy in Russia was never easy, but recent crackdowns and online censorship had just made it harder. Nonetheless, Mikhail and Anya still had some successes to share. One of the main achievements, they said, was getting human rights monitoring entrenched in key populations-led organizations, and having a national platform where those groups took full responsibility for governance, delivery of services, developing advocacy plans, and implementing them: “I’m not sure there is another example of such strong community work fully running a Global Fund grant by key populations,” said Anya. 169

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Over the years of the NGO Rule grant, they had brought numerous key populations activists to speak to UN human rights mechanisms; as a result, those mechanisms had made specific recommendations to Russia, which the networks could use in local advocacy. Some local governments had even started to fund the harm reduction programs. It was hardly glamorous – more like the long, hard slog of advocacy – but in the Russian context, it was impressive. This kind of work – bringing communities together; creating a platform for them to coordinate their work, strengthen their administrative skills, engage with governments, and advocate for evidencebased programs – this was what the Global Fund could do, and what no other donor did as well. But in Russia, where the HIV epidemic was spiraling out of control, that work was about to grind to a halt. “Rylkov’s money will be all out this year,” said Anya. The NGO Rule grant would end in a matter of weeks. Some of the organizations were being targeted and harassed in an ongoing crackdown. Worse, she said, “We have no money for syringes and we’re losing all our services. The Global Fund was the main vehicle.” In 1986 Jonsen coined the term “rule of rescue”: the humanitarian impulse to rescue someone in immediate danger, which he contrasted with cost-effectiveness analysis that aims to distribute limited resources fairly across a larger populations. The global AIDS movement was built on the rule of rescue. Communities have repeatedly rescued one another when resources were scarce. The global AIDS response had been created based on the idea that they shouldn’t have to do it alone. The Global Fund opened its doors in 2001 as a fund for an urgent response to a humanitarian crisis. Over time, the institution and its policies had grown more elaborate, with rules and exceptions accreting on top of one another, as funding and responsibilities increased. But it did seem strange – as we sat mulling over the future of the global HIV pandemic at that back room table with football games blaring overhead – that any small bank, when deciding which individuals to target for credit cards, had at its fingertips richer and more nuanced financial data than the largest international bank for health. * The process of revising the Eligibility Policy proceeded in late 2017 and through 2018, and the work by the three delegations continued, with numerous papers and rounds of talking points. When the policy was approved by the Board in May 2018, there were some wins for the civil 170

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society delegations that Mike later called “small but important.” The advocates succeeded in preventing expansion of a rule that would have affected eligibility for a few countries, and worked with others on the Board to eliminate the G-20 rule, keeping Indonesia eligible; though a grandfather clause kept other G-20 countries off the list. The small island rule was kept, so that Grenada and other Caribbean countries were still eligible, at least for now. My clients successfully pushed for and won a provision that enabled some countries with increasing HIV incidence to transition more slowly out of eligibility. The NGO rule was kept in, with a longer (though still rather vague) footnote defining political barriers. Anya got back to work with her civil society peers to develop their plans for a new proposal. Most satisfying of all the small wins was the change my clients pushed through in footnote number 9, which read: In the event that there is no officially reported prevalence data for key populations, or if the data is significantly different to the previous year’s data, and this results in a change in eligibility, the Secretariat will seek clarification from UNAIDS to determine the disease burden data that should be used for assessing eligibility. (The Global Fund 2018d, 4)

In other words, if a country denied the existence of key populations and failed to gather data about HIV among them, UNAIDS could give the Global Fund other sources of evidence, such as peer-reviewed journal articles or reports from civil society organizations that UNAIDS determined were credible. These could now be used to demonstrate high HIV burden among key populations and potentially make that country eligible: absence of data would no longer be treated as a zero. This serendipitously enabled the research in this book to be used to make a small but measurable difference in policy. Meanwhile, however, in the absence of a Copernican revolution, the inexorable trend toward donor divestment continued. In 2018 the World Bank announced plans to grow India into an upper-middleincome country by 2030 (All India 2018). Though India remains eligible for aid, the Global Fund informed the country that it should prepare to transition out from its more than $1 billion grants by 2023 (Mienies and Garmaise 2018). Several other African countries are expected to move into middle-income status in the years ahead. The inevitable logic of cost-effectiveness is coming for Africa and India just as surely as it has for Latin America, the Caribbean, Asia and 171

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the Pacific, Eastern Europe, and Central Asia. Given the 90-90-90 goals and its high rates of HIV, Kenya was a key country in which to demonstrate success. As Kenya was also moving toward upper-middleincome status, I asked Allan whether the country was ready to start thinking about transition. He said: “We haven’t figured out as a country where our gaps are. . . . I don’t think we’re prepared, and I don’t think we’re even having those conversations to see how the government takes over if any major donor decides to say, ‘It’s time to move on.’” In the immediate future, the gap between demand and funding will only grow. More donors and countries will face wrenching questions of prioritization – questions that are only likely to present starker choices. For Mike, the frustrating reluctance by some donors to tackle the real problems of income inequality within middle-income countries represented what he called “the dying last breaths of the twentieth-century development perspective” – one he was continuing to advocate be replaced in the UK’s bilateral aid with a more sophisticated approach. And for Rico, the elephant in the room not being discussed by any of the actors in the eligibility debate was the climate of scarcity that existed in the first place: “We’re sabotaging ourselves with these zerosum conversations. Of course, the resources are limited. But we as [the Global Fund], or as a global community, we’re not having a conversation about how to increase the overall pie. We actually need to have that conversation really badly.”

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LISTENING TO W O MEN

“The new craze ☺”

In April 2018 this was the note on an email Allan forwarded, an invitation he had received to a workshop in Nairobi about Assisted Partner Notification Services (aPNS). It was the first email from him on this topic, though far from the last. Given ambitious goals and limited funds, as discussed in the next chapter, donors were also facing an urgent pressure to increase enrollment on treatment – or as a US official I spoke with put it, “find the positives” and “increase the yield” of testing programs. East and Southern Africa, the region hit hardest by HIV, has made major strides by following the Fast-Track approach. One of the major challenges remains finding more of the thousands of people estimated to be living with HIV in Kenya and persuading them to take a test and learn their status – the first 90 of the 90-90-90 targets. Increasing testing rates was critical for donors and national health officials. Kenya was one place where experts believed the end of HIV as a public health threat was within reach. But after an initial push to get more people tested, year on year, the numbers had begun to level out. Most of those testing were women; men were harder to recruit for testing (WHO 2016a, 2). The “new craze” in this case was only really new for the global HIV response: it has long been used for other diseases. With index tracing (or index case-finding, as it is sometimes called), health care workers use someone known to be positive – the “index patient” – to track down 173

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others to whom they could have transmitted the disease (Ahmed et al. 2017). In partner notification services, a health care provider obtains the consent of the index client to actively recruit the client’s sexual partners, or persons with whom the client may have shared a needle, to take an HIV test. In a passive approach, the index client is encouraged to contact their partners. Assisted partner notification services, aPNS, is more aggressive: the health worker contacts those at risk directly and informs them that they may have been exposed to the virus and should test for HIV. The health care provider and patient sign a contract that states which approach they are taking, spelling out what each will do. For many, this approach raised serious concerns about privacy, confidentiality, and the risk of retaliation for women living with HIV whose partners are notified that they may have been exposed to the virus. As the aPNS approach began to scale up across East and Southern Africa, driven by active PEPFAR support, debates erupted in Kenya about the approach and the potential risk it created for women living with HIV to intimate partner violence. PEPFAR had prioritized addressing gender-based violence in a special initiative; but more broadly, under pressure to deliver results, the donor was promoting aPNS in order to improve “yields” or “find the positives.” Their recommendation was grounded in WHO guidelines (2016), based on WHO’s review of evidence from randomized controlled trials. This review concluded that aPNS could generate higher numbers of tests for HIV, speeding progress toward 90-90-90, and that reported cases of intimate partner violence were rare. Reports of intimate partner violence are always rare. But when it comes to these most hidden forms of violence, can absence of evidence be taken as evidence of absence? Kenya’s growing economy, strong civil society, and dynamic social media are reshaping these debates locally and globally. Kenya is also rare in having strong constitutional protections on human rights related to health, which have been used by Kenyan civil society organizations, including some representing women living with HIV, in litigation. Here, an empowered sector of women living with HIV, combined with a rise of African activist engagement in both global health governance and social media, made index tracing and aPNS a focus of intense debate 174

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over privacy, visibility, and violence against women living with HIV. This chapter explores how data-driven programming, along with the absence of data around difficult phenomena, may create realworld effects. It begins with the concerns raised by women living with HIV about aPNS online, then explores how PEPFAR has focused on data in order to manage the race to “find the positives” (as one US official put it in our interview) and reach 90-90-90 in East and Southern Africa. By examining the problem of documenting intimate partner violence and how this is addressed in the studies on which the WHO based its guidelines, it raises questions about what things may be left uncounted in the race to get more people to test for HIV. “WOMEN ARE BEING USED AS BAIT” What is being done is driven by foreign governments, in the name of donors, as they collect data in our countries – something we can’t do in [their] countries. Patricia Asero

In September 2018 Maurine Murenga’s Facebook page blew up with messages about aPNS. Maurine is openly living with HIV and a gentle, patient, but relentless advocate for the rights of Kenyan women and girls living with HIV. She is founder of the Lean on Me Foundation in Kenya, which provides care and support for adolescent girls living with HIV and TB. She also serves on the Board of the Global Fund. In 2018 she was elected Board Member for the Communities delegation, replacing Rico Gustav in that role. Her deputy, EriKa Castellanos, was the first transgender delegate elected to be Alternate Board Member, and perhaps the first elected to such a prominent role in any global health financing agency. Activists like Allan Maleche and Maurine Murenga have risen to international prominence through their outspoken rights-based advocacy for marginalized communities. In addition to their roles on the Global Fund Board, both are active in championing the Fund’s replenishment campaigns across Sub-Saharan Africa, and occupy advisory roles in WHO and UNAIDS. At the same time, they and other civil society groups have sometimes been outspoken critics of rights violations in Kenya in the context of the national HIV response.

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These included major lawsuits that have influenced government health policies. In 2015 the AIDS Law Project successfully sued the government over provisions criminalizing HIV transmission in the HIV and AIDS Prevention and Control Act and won: the court found the provisions were unconstitutional (Raw 2015). In 2016 Allan’s organization, KELIN, represented a group of petitioners who successfully sued to overturn a presidential directive ordering the collection of real names of people living with HIV, including names of school children (KELIN 2016). In 2016 KELIN also successfully filed suit on behalf of two patients with tuberculosis who had been forcibly confined and isolated for non-adherence to treatment; the judge found this practice unconstitutional and directed the Ministry of Health to develop new guidelines. And in 2018–19, KELIN filed suit with an NGO on behalf of four women living with HIV, charging that the women had undergone bilateral tubal ligation without their informed consent at hospitals and medical clinics operated by the government, MSF and Marie Stopes International. That case was still in process as of this writing. On another occasion, KELIN had supported the national network of women living with HIV when they publicly raised concerns about a government event to promote prevention of mother-to-child transmission of HIV. The event had “parad[ed] women living with HIV and their children on live television . . . publicly disclosing their HIV status. . . . We are reliably informed that most of the women paraded had not yet disclosed their status to their loved ones, including their immediate family members” (ICW-Kenya, ICWEA, and KELIN 2017). Kenyan women living with HIV are, in other words, a group with a strong and vocal leadership who are not afraid to challenge authorities over practices they feel violate their rights. On September 25, 2018, Maurine raised concerns about aPNS. She posted the following to her approximately five thousand followers on Facebook: So the last two days we have been having discussions around the anonymous call from the health facility. This is what the government is rolling out. If you test positive for HIV, you give names and telephone numbers of your sexual contacts. These people will be called and informed that you tested positive for HIV and mentioned having had sex with them in the recent times. They will be asked to go to the facilities for the test. 176

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She invited comments from her followers. Dozens followed, within days: • Doomed to fail, bad approach. • Murder cases will be on the rise . . . couples hacking each other to death. • How is partner notification supposed to end stigma, promote access and adherence to ART? Whoever comes up with such strategies . . . • I’d go get tested, so I know exactly how to kill them when I get my hands on them. • I will go. After serious prayers and fasting. • aPNS will cause more broken families, due to domestic violence. One rare dissenter wrote: “I don’t see a problem with this. People will know their status earlier and take action earlier.” Murenga replied to the comment: “Empowered people like you. Some are so disempowered they will kill.” The friend replied, “True, a bigger population in Kenya is still not empowered. . . . I shared this with people in the office and a good majority said they would sue or kill.” Another friend commented, If someone has ever been inside a person who has tested positive you will never know how it [feels]. The monster here is stigma . . . from the pulpit to the facility to the community to the self, and anywhere you can imagine. If you don’t know that when you are #HIV positive you are branded, know it today. We must try hard to erase this branding.

A Ugandan AIDS activist also commented, “New ways of doing business. My country launched revised guidelines with same. Waiting for law courts to fill up.” Patricia Asero had made the comment about foreign donors driving data collection in Kenya (see Figure 7.1). She is chair of the Kenya chapter of the International Community of Women living with HIV (ICW-Kenya). She has spoken frequently about the role of poverty, gender-based violence, and lack of information about sex education and human rights in high rates of HIV among young women and girls. In an online interview with the Global Fund Advocates Network, for example, she had previously said, More often than not, [adolescent girls] live in financially unstable households. Many have parents who have died, which means the burden of caring for the family falls on them. They have siblings to feed, clothe, 177

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Figure 7.1 Patricia Asero speaking at a PEPFAR meeting, Nairobi, Kenya. Credit: Patricia Asero Ochieng

keep healthy, and keep in school. They are forced to make impossible decisions every day and sadly, this leaves girls open to exploitation. Sometimes neighbors, family friends, or even relatives, take advantage of them, marrying them off or taking them in as house help. There is incest, there is rape, and for a large majority, it can feel like there is no hope. (Ochieng 2016)

I called Patricia Asero in Homa Bay, a high-prevalence area on the shores of Lake Victoria where she was visiting to work with local PEPFAR-funded sites. I asked her how she had first heard about aPNS. Asero said community members had contacted the national network: “At health facilities, they are getting asked about partners, partners’ details are taken and being called. We said, ‘What?! Our laws do not allow that. How is that happening?’” In Kenya, she said, “women have the best treatment-seeking behavior,” but were also extremely vulnerable to intimate partner violence. The moment their status is disclosed, she said, “everything changes.” In one example, “somebody from Makwene, a woman, was tested. . . . Her husband was 178

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called. . . . There was violence; the woman was kicked out of the house. You have children, you’re dependent. [The health clinics are screening only for] physical violence, not emotional, psychological, or financial violence.” The United Nations definition of intimate partner violence supports Patricia Asero on this point: it includes emotional or psychological abuse, and controlling behaviors such as isolation, monitoring of movements, and restricting access to finances, employment, education, or medical care, “including threats of such acts, coercion or arbitrary deprivation of liberty, whether occurring in public or in private life” (General Assembly resolution 48/104). The result of aPNS, Patricia predicted, was that across the board, Kenya’s gains on HIV among women would be rolled back: They say a person is “lost to follow-up.” That person is not lost; they have just gone to another clinic where they’re not being asked those silly questions. There’s already treatment interruption, there’s already a problem. People are not going in for testing. There’s a lot of fear that partners are going to be called.

She said, in frustration, “It’s numbers, it’s numbers, it’s targets, it’s targets, and human rights has gone out of the picture.” The very women with whom Kenya’s health clinics had made progress, she said, would be lost through the new focus on their partners: “Now you no longer matter, you’re just an ‘index.’ They’re going to use them to take the ‘yield.’ . . . It’s like you are crop. Women are being used as bait.” PEPFAR has honed the use of data in its financing more than any other donor financing the HIV response. In its efforts to focus funds for maximum impact, PEPFAR had concentrated more resources in SubSaharan Africa and had actively promoted index tracing and partner notification services. To understand PEPFAR’s position, I spoke with Ambassador Deborah Birx, the head of the agency. She was emphatic that the purpose of aPNS was about reaching people: “This is not about putting numbers on the board; this is about ensuring that people have access to life-saving services.” Speaking later about another program, she said, “The way I look at this is, the client is always right. If the client has left treatment, that’s on us, and we need to figure out how to make it an acceptable place with the services that they need.” Ambassador Birx has sharpened the agency’s focus both on the needs of key populations, women and girls, and on the use of granular data to 179

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monitor program performance down to the site level. To understand the tensions between this use of data and the concerns raised by women, the next section briefly summarizes the agency’s evolving approach to data. PEPFAR AND THE DRIVE FOR DATA

PEPFAR was founded in 2003, under the administration of President George W. Bush, and has been considered one of the most successful public initiatives in global health (Fauci and Eisinger 2018). PEPFAR is housed in the US Department of State, headed by a Global AIDS Coordinator with the rank of ambassador whose team coordinates work across seven US government agencies. These then subgrant to other agencies and civil society organizations to implement programs.1 The first appointee to the role of Global AIDS Coordinator, Randall L. Tobias (2003–6), was a vocal proponent of abstinence, and of a Congressional requirement that US aid recipients commit to opposing sex work and sex trafficking. Congressional champions linked to faith-based programs in Africa played an active role early on, and they continue to be key to reauthorization of the budget in Congress (Igoe 2018). Tobias resigned in 2007. He was succeeded in the office by Mark Dybul, later executive director of the Global Fund; and then by Eric Goosby. In April 2014 the Senate confirmed Deborah Birx in the role. Ambassador Birx was the first woman to head PEPFAR, and one of the few occupying a leadership role in global health. She quickly earned a reputation for pragmatism, political acumen, and a focus on measurable results. As the Board Member representing the Global Fund’s largest donor, she often took the microphone at Board meetings to deliver clear directives to managers and implementers to work harder at reaching key populations and young women. A medical doctor, virologist, and retired US Army colonel, Ambassador Birx had been engaged on HIV from the beginning of the epidemic and promoted greater precision to PEPFAR’s targeting of medical interventions: “We harness the latest data and science to direct resources where the HIV/AIDS epidemic is the largest, the need is the highest, and they are the most efficiently used to have the greatest impact per each dollar invested” (Birx 2018). Drawing on data to make 1

The seven agencies are the Department of State, US Agency for International Development (USAID), Department of Health and Human Services, Department of Defense, Peace Corps, Department of Commerce, Department of Labor, and Department of the Treasury.

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the case for PEPFAR’s impact, the ambassador shored up support from PEPFAR’s Congressional and White House supporters. She managed to sustain strong support from evangelical Christians in Congress, while remaining an outspoken advocate for services to key populations, adolescent girls, and young women. Her initiatives at PEPFAR included the DREAMS (Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe) partnership, a package of services developed to reach women and girls, and a key populations initiative that provided funding to community-led groups. Birx has shown leadership in raising the issue of violence against adolescent women and young girls, for example in a blog for International Women’s Day in 2018, in which she described the rape of a nine-yearold girl who later tested positive for HIV, and committed PEPFAR to expanding programs that aim to prevent sexual violence and support survivors in accessing and adhering to antiretroviral treatment (Birx 2018a). In 2015, when – as described in Chapter 5 – WHO reviewed available evidence and recommended countries use the Test and Start approach, Ambassador Birx’s statement welcomed the news, saying, “We have no excuses – it is up to us to seize this moment and chart a bold course together to end AIDS as a public health threat” (WHO 2015a). PEPFAR began to use data to push for faster progress, both reallocating funds across countries to areas where HIV prevalence was the highest and to specific districts and sites within those countries. This included changing allocations for countries from one year to the next. In our interview, Ambassador Birx said, “We’re really trying to match our resources to the need. That means when you have a specific budget, resources have to move between countries that have greater need.” Some implementers, she said, assume if they get aid at one point, they will continue to get it, even when their epidemic has changed: “That has been a very difficult conversation, because we see across all of the countries, and across all the epidemics. . . . It really forces you to right-size your investment according to the need.” The ability to rigorously and objectively evaluate performance of specific regions and sites within countries was, she said, key to this approach to prioritization: I think the granularity of the data becomes critically important: both having program data, and the large surveys in the field, has given a much 181

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more honest analysis of how we are doing, where we’re doing great, and where we still have substantial gaps in the program – [we are] really forcing ourselves to understand those gaps.

This is reflected both in the allocations received by countries, and in the changing tone and focus of national Country Operational Plans (COPs) that set out the strategy PEPFAR would use in that country. Between 2014, when Ambassador Birx was appointed, and 2018, while the budget for the agency stayed the same, PEPFAR managed to allocate increasing amounts from other countries to Sub-Saharan Africa: by 2018, this amounted to $500,000 more per year than the region received in 2014, an increase of more than 14 percent (see Table 7.1). In addition, allocations shifted among countries, as we saw earlier in the discussion of PEPFAR’s approach in the Caribbean. While the focus was on countries with high HIV prevalence, this does not appear to have been the only consideration. Some countries that did well received significantly greater allocations: Malawi and Zimbabwe received more TABLE 7.1 Changes in PEPFAR allocations for countries with high HIV prevalence, 2014 and 2018

Country

Est. number PEPFAR PLHIV, allocations 2018 2014

PEPFAR allocations 2018

Côte d’Ivoire Cameroon Ethiopia Malawi Zambia Zimbabwe Uganda Kenya Tanzania Nigeria* Mozambique South Africa Totals

460,000 540,000 690,000 1,000,000 1,200,000 1,300,000 1,400,000 1,600,000 1,600,000 1,900,000 2,200,000 7,700,000 21,590,000

$108,651,084 $41,866,230 $71,600,590 $137,530,942 $374,113,258 $145,357,200 $375,108,250 $444,832,321 $393,759,298 $245,490,052 $383,865,418 $572,355,198 $3,294,529,841

$116,254,920 $36,250,000 $126,564,339 $81,192,326 $259,888,666 $95,682,412 $316,679,051 $375,000,000 $375,000,000 $458,614,281 $277,075,909 $259,000,000 $2,777,201,904

Difference − 8% + 15% −43% + 69% + 44% + 52% + 18% + 19% + 5% − 46%* + 39% + 121%

Sources: UNAIDS (2019c); amfAR PEPFAR Country/Regional Operational Plans Database. Percentages are rounded up. * Nigeria’s prevalence was est. 2.8% prior to 2019, when updated estimates reduced it to 1.4%. 182

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than 50 percent more in their 2018 allocation than in 2014, while South Africa’s annual allocation more than doubled during this time. Other countries did not increase their allocations, despite having high HIV prevalence: in Ethiopia and Nigeria, the annual allocation for 2018 was more than 40 percent less than in 2014. Year by year, PEPFAR was reviewing the data and reallocating funding among countries, and even among districts and sites, to reward and encourage faster results. As one US official working in global health I spoke with observed, “Some of this was driven by a Congress that increasingly questioned the level of aid to anyone for anything. Congress likes PEPFAR because it shows results, and can answer almost any staffer question thanks to the quantity of data they have.” The growing emphasis on numerical target-setting and granular data is also evident at the subnational level. Early each year, PEPFAR publishes guidance for annual Country Operational Plans, introducing the updated priorities and expectations. In the 2019 guidance, using epidemiological data to drive performance is emphasized. Countries “such as Namibia, Eswatini, Lesotho, Uganda, Ethiopia and Zimbabwe” are praised in this guidance for “making significant progress across the three 90s,” in part due to their continuous review of and “real time” adaptations to the data (PEPFAR 2019, 25). The 2019 guidance emphasized filling these gaps by “continuing to focus on finding the people and populations we have been missing, getting them on treatment and achieving viral suppression” (PEPFAR 2019, 10). In reviewing the annual PEPFAR COP guidance from 2014 to 2019, it becomes clear that over a five-year period, PEPFAR increasingly embraced more hard-driving approaches like index tracing and partner notification, in order to pinpoint and identify people living with HIV who had not yet started on treatment, and persuade them to test and begin treatment. Reviewing specific Country Operational Plans produced by country teams between 2014 to 2018 show a change in tone and focus, in line with the global PEPFAR COP guidance. In Zambia, for example, the 2014 Country Operational Plan paints a vague but rosy picture of progress: Zambia has reached “the tipping point,” with more than half of people living with HIV on treatment (PEPFAR 2014b). While nationally reported data published by UNAIDS in 2018 does show an impressive 75 percent of people living with HIV 183

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are on treatment, there are gaps in data, including for testing and adherence (UNAIDS 2018c, 64–65). Two years after Ambassador Birx took the helm at PEPFAR, Zambia’s Country Operational Plan is a quite different read: the short, vague papers transform into long, dense tomes packed with precise numbers. The country would “scale-up services in 258 sites, sustain services in 488 sites, and centrally support 624 sites,” with a target of “946,472 HIV infected persons on treatment by end of FY 2017” (PEPFAR 2015, 3–6). The Country Operational Plan for Zambia began to include charts listing the number of people living with HIV estimated to be residing in each priority district. And though Zambia lacks official guidelines on how to implement index testing, the Country Operational Plans begin to speak about scaling up index tracing, with the aim of using this approach to find 49,974 new cases (PEPFAR 2016, 2018b, 22). Zambia is just one example. National HIV strategic plans and COPS for other high-prevalence countries in the region reflect a similar approach: pinpoint the specific districts where HIV is most prevalent, and roll out aggressive approaches to index tracing, testing for HIV and starting on treatment, with a mix of interventions aimed to get people tested and linked to treatment. Index tracing and aPNS is at the heart of this outreach approach. A joint presentation by PEPFAR with USAID, the US Centers for Disease Control, WHO, and the US Department of Defense (2018) explains the high impact this approach can have in persuading more people to test and cites studies showing that index testing has resulted in “yield rang[ing] from 35–62%, with no reports of serious intimate partner violence” (PEPFAR et al. 2018, 6). While the PEPFAR COP guidelines stress the need to retain the index client’s confidentiality and focus on “the needs and safety of the index client,” they also deliver a clear warning: programs that fail to reach at least 80 percent rates of elicited index client contacts will be “reviewed” (PEPFAR 2019, 343). For a program director whose payroll is covered by PEPFAR, failure to reach 80 percent elicited index client contacts would certainly create anxiety, especially given the agency’s clear track record of cutting funding for programs due to poor performance against numerical targets. Ambassador Birx underscored in our interview that index tracing and aPNS should always “be voluntary, it should not be forced.” She affirmed, “We want to always be on the side of supporting the 184

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client and the human rights of the client.” At the same time, she said, she felt an urgent need to reach male partners who had never accessed treatment before; as well as older children of women living with HIV. PEPFAR had funded community surveys that had shown “how many children we’ve been missing that are older, that survived, that by all rights – by what we have been taught – should not have survived into adolescenthood without receiving antiretroviral treatment, but did. And now finding them will be absolutely key.” She emphasized that she expected local partners to frankly say if they did not believe they could reach PEPFAR’s targets. However, given that the COP guidance sets clear targets of 80 percent compliance with aPNS, and that PEPFAR has a track record of abruptly ending funding for poor performers, a local organization might be hesitant to admit its concerns. THE BURDEN OF PROOF

The assertion in the PEPFAR guidance that there were “no reports of serious intimate partner violence” linked to aPNS is at the heart of the debate between community advocates and national and global health agencies in Kenya. Once again, it brings us into the terrain of the data paradox, in which painful realities that are difficult to quantify may often remain hidden, leading to lack of programming to address the problems, reinforcing the lack of data. In this case, while intimate partner violence is not impossible to measure, it does require specific steps and services be in place in order to elicit disclosure safely and ethically. The impacts of intimate partner violence (or domestic violence) are profound, ranging from injuries, depression, and anxiety to negative sexual and reproductive health consequences, and can even end in death. It has a number of specific links to HIV. Women living with HIV who experienced intimate partner violence are “significantly less likely to start or adhere to antiretroviral therapy, and they had worse clinical outcomes than other HIV-positive women” (UNAIDS 2018, 14). Disclosure of HIV status can be a trigger for dissolution of the relationship, blame, and violence, according to studies in Zimbabwe, Swaziland, Kenya, and Uganda (Shamu et al. 2014; Mulrenan et al. 2015; Colombini et al. 2016; Maeri et al. 2016). Studies in Tanzania, South Africa, and Kenya found that fear of violence was a barrier to 185

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disclosure of HIV status for 16–51 percent of women living with HIV (Medley et al. 2004). Intimate partner violence is generally widespread, but also generally underreported (Palermo et al. 2014). This is because those who are vulnerable to intimate partner violence are concerned about the risks of reporting, which can include stigma, retaliation, social isolation, and even death. There are few services for survivors, and perpetrators generally benefit from a climate of impunity, so the incentives are reporting are minimal. In many cases, victims do not know that services exist that could help them; in many others, they believe that the violence is normal, or that it was triggered by the victims’ own behavior. Underreporting is generally the problem facing program managers who aim to address all forms of gender-based violence, including intimate partner violence. As a survivor myself, and coordinator of academic courses for program managers on responding to sexual and genderbased violence, I had seen and heard of numerous cases in which programs are established to specifically serve survivors but sit in empty offices: it can be difficult to reach survivors and to establish the environment of trust needed to elicit disclosure without exposing the survivor to either retraumatization, social stigma, or other dangers. Male and transgender survivors of sexual violence are, if anything, even more hidden than female survivors. In short, because survivors are the most hidden of hidden populations, winning their trust and eliciting disclosure requires special efforts. Passively waiting for them to disclose, or even doing cursory screening, will generally not be sufficient to gather robust data. The International Committee of the Red Cross (ICRC) has confronted this problem in addressing a related problem of conflict-related sexual violence. They concluded: Despite its prevalence and grave consequences during armed conflict, other situations of violence, and detention, sexual violence is often underreported because of various factors that prevent victims/survivors or witnesses from coming forward. As a result, the full extent of the problem is often concealed, with official figures failing to reflect reality. Such factors can include the stigma, guilt and shame associated with sexual violence, fear of retribution from the perpetrators, family or the community, or mandatory reporting requirements. In addition, cultural barriers to speaking out about incidents of sexual violence are often significant. (ICRC 2019, 10) 186

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Furthermore, they note, misconceptions are pervasive, “even among professionals such as health-care workers and other service providers” (ibid.). As a result, many programs responding to sexual violence are “not specific enough to the needs of the victims/survivors” (ibid.). Because it is so difficult to elicit disclosure, studies that aim to gather data on intimate partner violence use specific methodologies and take special ethical precautions. WHO and other UN agencies have developed fine-tuned screening tools to perform the delicate work of eliciting disclosure (WHO, LSHTM, and South African Medical Research Council 2013; WHO, UNWOMEN, and UNFPA 2014). Critical steps to elicit disclosure include careful selection of interviewers to screen for bias and stigma; giving these interviewers extensive training; taking precautions to protect confidentiality and security of information; and perhaps most important of all, preparing to meet the needs of those at risk immediately when they are identified, by putting referral systems in place to provide medical care, mental health and psychosocial support, protection, and access to justice when someone does disclose intimate partner violence. In other words, undo the stigma, protect confidentiality, acknowledge that the violence is not normal and is a crime, and provide services so that reporting becomes something useful for survivors, not harmful. In fact, based on its written report, Kenya’s 2014 Demographic and Health Survey seems to have taken these measures before attempting to gather data on the prevalence of intimate partner violence. The authors describe taking steps to ensure the safety and privacy of respondents and reduce the risk of retraumatization for those who disclosed they were victims, as well as having referrals in place to support services for victims identified during the survey (Kenya National Bureau of Statistics and ICF 2014, 291–93). These measures were consistent with WHO’s recommendations on ethics and safety in research on intimate partner violence. The fact that the DHS took these measures demonstrates that it is certainly feasible for others to do so in Kenya. Their resulting report was a disturbing, but plausible, 39 percent prevalence of intimate partner violence among ever-married women. Further, 23 percent of ever-married women reported physical violence by their spouse in the previous 12 months (Kenya National Bureau of Statistics and ICF 2014, 306–7). 187

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This is an alarmingly high percentage, but it is consistent with broader trends. WHO has found that globally, 30 percent of everpartnered women have experienced intimate partner violence; in Africa, the prevalence rose to 36.6 percent, an estimate consistent with the Kenyan survey referenced above (WHO, LSHTM, and South African Medical Research Council 2013, 16). I discussed these estimates with Maurine, Patricia, and Allan, and they agreed they seemed plausible; if anything, they might be underestimates of the extent of intimate partner violence in Kenya, because of the reluctance of many people to disclose. With this in mind, how are we to understand the assertion by PEPFAR, based on WHO’s guidance, that studies of aPNS had “no reports of serious intimate partner violence”? If 30 percent of everpartnered women have experienced intimate partner violence, the aPNS studies were reporting rates of violence that were far below the baseline. Had researchers in these studies taken the measures recommended by WHO to persuade women that it was safe and in their interest to report intimate partner violence? I went to the studies to find out. WHO’S

APNS

GUIDELINES

The WHO Guidelines on HIV Self-Testing and Partner Notification (2016a) were a supplement to the 2015 Consolidated Guidelines on HIV Testing Services. They provide recommendations on self-testing and partner notification based on their process of review and consultation. The systematic review uses the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) process, in which recommendations are assessed and weighted based on the strength of the evidence. The initial search yielded 1,407 citations, which were screened for inclusion in the study. Based on this screening, four randomized controlled trials were deemed eligible and were included in the review to produce the guidance (WHO 2016a, 46–47). The new evidence was largely from one study of aPNS in Kenya (Cherutich et al. 2016). Collectively, WHO found that the four studies demonstrated that use of the aPNS approach resulted in higher uptake of HIV testing among partners of people with HIV than passive referral methods, as well as other positive outcomes (WHO 2016a, 47). WHO also found that, as quoted by PEPFAR, “reported social harm and other adverse events following HIV partner notification using passive or assisted 188

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approaches have been rare. . . . [C]oncerns about potential social harm, including violence resulting from partner notification, have not been borne out in the scientific studies conducted to date” (WHO 2016a, 5). Furthermore, WHO said, there was a need for guidelines on aPNS as countries and other key stakeholders have indicated the importance of this new guidance to enable them to make decisions about whether, or how, to adopt these two approaches to HIV testing so as to enhance their ability to strategically focus on and scale up HTS, with a view to achieving the UN 90–90–90 goals and fast-tracking the end of HIV by 2030. (WHO 2016a, 5)

With WHO’s guidance on measures to elicit disclosure of intimate partner violence, including putting in place remedies to meet the needs of those who do disclose, I reviewed the four studies used to develop WHO’s guidelines on aPNS. In all four studies, it was difficult to assess whether the four studies had done what was needed to elicit disclosure and protect survivors, as most did not discuss this. Two of the studies were published before the WHO guidance existed. This includes a 1992 study in North Carolina by Landis and colleagues (1992), and Brown and colleagues’ study in Malawi (2011). It would not be fair to assess whether these studies were implementing measures that had not yet been recommended by WHO, so perhaps best to set them aside for the purposes of this discussion. In 2011 WHO published guidelines on responding to intimate partner violence; so two of the four studies WHO used in its aPNS guidelines could have known about and incorporated the recommended measures. Rosenberg and colleagues’ study of aPNS in a maternity hospital in Malawi came after publication of those guidelines. It describes onemonth follow-up visits with participants, but the article does not describe what measures were put in place to elicit disclosure, protect privacy and security, and refer victims to services. Few study participants reported any social harm to the researchers (Rosenberg et al. 2015, 7). The fourth study by Cherutich and colleagues (2016) was unpublished at the time the WHO aPNS guidelines were published. Their conference presentation, cited in the guidelines, is not available online. A similarly titled presentation by the same authors for a USAID webinar held a few months later is online (Cherutich 189

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et al. 2016, 2016a). As described in the slide presentation, the study spanned eighteen sites in Kenya. It did include periodic follow-up to assess social harm and identified a small number of cases of intimate partner violence (3.3 percent new cases and 4.8 percent repeat cases), only two of which appeared to be possibly study-related (Cherutich et al. 2016a, slide 15). However, from this description it is unclear whether WHO-recommended measures were used to protect privacy and security, elicit disclosure, or refer victims to protection or other services, along with whether the screening tool was nuanced enough, whether interviewers had been adequately screened and trained, and whether the other measures recommended by WHO to elicit disclosure had been utilized. In sum, WHO’s finding that aPNS produces high yields is clearly supported by the studies it identified in its review. Its assertion that intimate partner violence was rare is not. If they had been focused on the impact of aPNS on intimate partner violence, these studies would have started with a premise that it does affect at least 30 percent of women in Kenya, and would have put in place the measures that WHO recommends accordingly. Indeed, Landis and colleagues did acknowledge the limitations of their study in this respect, and did recommend future operational research to investigate the effect of aPNS on social harms in African settings (Brown et al. 2011, 442). This recommendation was not reflected in WHO’s guidance. The fact that the reported intimate partner violence in these studies of aPNS fell far below the baseline rates in the general population of women in Kenya suggests the troubling possibility that the studies simply failed to elicit disclosure: perhaps some survivors either did not feel safe to report, did not know that reporting was an option, or felt that the risks of reporting outweighed any potential benefits. WHO’s guidelines do underscore that aPNS should be voluntary and based on informed consent, but do not clearly state that intimate partner violence is widespread, that it affects more than 30 percent of the female population globally, and that it is frequently underreported. They suggest using support services but present these as optional add-ons: “Trained providers should offer partner notification services appropriately and safely. Associated counselling and support services, such as helplines and intimate partner violence screening tools, can also be utilized to reduce the potential risk of harm” (2016a, 42). WHO’s own guidelines on preventing, responding to and managing cases of intimate partner violence are referenced only once in 190

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passing (2016a, 60). WHO found, “While programme implementers should be sensitive to the potential for harm arising from disclosure of HIV status, this should be balanced against the benefit of diagnosing HIV infection and linking people to treatment” (2016a, 5). But as Asero had pointed out, this is the difference between the “crop” and the “yield.” The harms and benefits do not accrue to the same people: if the woman might experience harm, who decides her risks are less important than the benefits to her male partner, or to the larger community? I reached out to WHO’s HIV department to ask for their perspectives and to understand the process behind the guidelines. Rachel Baggaley, Coordinator of HIV Testing and Prevention at WHO’s HIV department, led the process of developing the guidelines, including consultation with people living with HIV. Her approach was nuanced and grounded in many years of personal experience working in clinics in diverse settings. She affirmed that “do no harm” was her team’s first principle, and that they had commissioned other studies and reviews to look at social harms linked to HIV testing. They had recommended several different approaches to partner notification, she said, in part to avoid pushing women living with HIV into a situation where partner contacts would be coerced, or where they would be exposed to risk. “Not everybody is the same,” she said: While there are extremely high amounts of intimate partner violence everywhere, not just in Kenya, likely more so in South Africa, but on the other hand there are lots of great relationships, and people can be really, really supportive – for example, if they can share results and support each other to take treatment or choose HIV prevention options.

Linking specific incidents of intimate partner violence to HIV disclosure is also challenging, she argued. Research WHO had supported in Malawi found it difficult to pinpoint the specific incident that might have triggered a specific incident of violence, and how that might play out later. In one example she shared, a woman whose partner had been tested for HIV was evicted from her home, but three months later, after her partner had come to terms with his HIV status and started treatment: “Scroll on three months, they’ve reconciled, he’s on treatment, and they’re back together. She’s supporting him with his treatment and she remains HIV-negative. So these are very complicated, dynamic things.” In the end, she said, it was better to encourage partner notification, because 191

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whatever happens, if you’ve got HIV, you will be diagnosed at some stage, because you will become sick. . . . It’s not great to find out you’ve got HIV at any time. It’s much better to find out when you are well, and you have support to get on treatment and cope with the transition to living with HIV.

Finally, she argued, in her experience of working in the HIV response, the trends in acceptability of different forms of testing tended to change: while activists sometimes object to a certain HIV testing method at one point in time, over time these objections sometimes fade as the practice becomes accepted, and meet some peoples’ needs. In the end, Baggaley stressed, obviously having intimate partner screening services is important, but on the other hand, [what is important is] just listening to women. Women will know whether it’s sensible to involve their partners or not. If they’ve got a partner that they don’t want to involve, that should be respected, absolutely. . . . Clinics should listen to women.

Andy Seale, an adviser on the same team, shared that WHO had now established an advisory committee of women living with HIV who would discuss aPNS and other issues in the future. The WHO team’s commitment to and concern for rights of women living with HIV was evident in Geneva. However, in the global context of ambitious goals and limited resources, Kenya was under very specific pressure to “find the positives” and demonstrate progress toward the end of AIDS by 2030. As the political and economic pressures ratchet up on high-prevalence countries that are key to the Fast-Track approach, human rights of women living with HIV may be jettisoned. Real questions emerged about whether someone dependent on a health care worker for access to life-saving treatment can freely give informed consent. This became clear in hearing reports from Kenyan civil society organizations about the discussions they had with national health authorities. One key recommendation in WHO’s guidelines on aPNS is that health providers assess the legal and policy environment to see whether there are laws and policies that criminalize HIV transmission, criminalize key populations, or require mandatory HIV testing (WHO 2016a, 58). They urge countries to respect “five C’s”: consent, confidentiality, counseling, correct results, and connection, and address legal barriers to service access (WHO 2016a, 7). The guidelines also note that few countries have “legal 192

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provisions to protect HIV-positive individuals against potential harm following disclosure of their HIV status and partner notification” (WHO 2016a, 45). Given that these kinds of laws exist in most countries, it is not clear how any country should proceed with aPNS before an ambitious program of law reform; the guidelines appear contradictory in this respect. Kenya’s national health authorities were certainly concerned about whether the laws would allow them to roll out aPNS. Patricia Asero said that when she went to Kenya’s first national workshop on aPNS, as I sat down to listen to what they were presenting, they were focused on the law. The reason was that they had been taken to court, and they know civil society can take them to court [again]. So they were looking at the law, and how can they use law to impose aPNS without repercussions.

The government cited a provision, section 24 of the HIV Prevention Act, which they said empowered a medical practitioner to notify anyone who has sexual contact with an HIV-positive person of that person’s status. Patricia Asero argued with them that it did not give that authority, because this provision had already been found unconstitutional in the 2015 AIDS Law Project lawsuit. “No one was listening to me,” she said. “So I called in KELIN.” * “The new craze ☺”

While this was not the last message Allan sent about aPNS in Kenya, it was the last to include a smiley-face emoji. The message it was attached to was his invitation to a workshop on aPNS organized by NASCOP, the national HIV and STI program introduced in Chapter 2, and the US Centers for Disease Control. The invitation explained that a team of US experts had drafted national aPNS guidelines to be reviewed and finalized in the meeting. Instead, the workshop sparked a months-long battle with KELIN, ICW-Kenya, and organizations representing people living with HIV and key populations. At one point, the national human rights commission got involved. Throughout this process, KELIN argued that in accordance with the East African Community HIV Prevention and Management Act, African Commission guidelines, the Data Protection Bill, and Kenya’s 193

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Constitution, partner notification would be a breach of the right to privacy. The 2015 AIDS Law Project lawsuit had resulted in the court finding that section 24 of the HIV Prevention Act was unconstitutional. Donor-driven imperatives could not trump the Kenyan Constitution, they argued. The guidelines for clinics on how to implement aPNS became stuck in the review process. NASCOP shared drafts with civil society a few times for comments, but as Allan wrote of one version: “All the references to the HIV Act are wrong. That’s where I stopped reading! The section they claim to be using was declared unconstitutional.” Furthermore, as Patricia Asero had flagged, the intimate partner violence screening tool proposed by the guidelines was “inadequate,” according to Saoyo Tabitha Griffith, deputy executive director of KELIN. In an email to me on September 4, 2019, she wrote, “It has three questions and is not even in line with the common forms of violence reflected in the Protection against Domestic Violence Act. The tool does not also give mechanisms to address violence should an index patient report violence post the testing.” Furthermore, Griffith had a list of other concerns, as she summarized in a message to NASCOP on August 8, 2018: • The need for plans to respond to needs of survivors of GBV when it did occur • A plan to ensure that aPNS implementation also upheld the rights to privacy and confidentiality, defined in a Data Protection Bill before the senate as including telephone contacts • Ensuring that index clients were not coerced, which Patricia Asero had reported was happening on the ground (Would service quality assurance checks be incorporated?) • The need to bring more stakeholders into the process of reviewing the guidelines, including women living with HIV Tabitha warned in her message that if these concerns were not addressed, we are likely to put women, particularly in rural settings, in harm’s way, with heightened risk of violence from partners aggrieved when they trace back who shared their contacts. We risk losing key populations such as sex workers, who may not be keen to share the contacts of their clients, due to their trade and the “silent oath of privacy” that accompanies their work. (Griffith 2019) 194

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Furthermore, if communities did not feel their input was being taken seriously by health authorities there was “a higher risk they will litigate.” In KELIN’s characteristically personable style, she finished off this list of specific demands and implied threats of litigation with an offer to provide support, and signed it, “Warmly, Saoyo Tabitha Griffith.” KELIN’s leadership was nothing if not kind and friendly while they were escorting you to the door of the courthouse. By December 2018, when we checked in by phone before switching off for the holidays, Allan was increasingly frustrated with Kenya’s aPNS craze: We broke down the issues we had [with NASCOP], particularly [how] aPNS was being rolled out in a more coercive manner by health care workers. They hadn’t put into place any measures for GBV. They were reaching out to partners without [clients’] knowledge, and trying to [say this is] within the legal frameworks. [WHO] keep saying we have put safeguards in place, but there is no evidence from NASCOP that they have put those safeguards in place. The communities told them to stop aPNS taking place and to consult with communities. . . . This was in October. NASCOP took the line that they’ve heard the feedback and will get back to civil society on the issues. Of course they haven’t. . . . NASCOP is stuck. They have to deliver results to PEPFAR.

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Facing the pressure to meet the end of AIDS by 2030, global health agencies, including WHO and HIV finance programs, have been pressing to increase access to treatment, and to reach those who have not previously been tested. Recognizing that women, especially adolescent women and young girls, face especially high rates of HIV in Sub-Saharan Africa, they have made strong commitments to addressing gender equality and human rights. However, in the race to develop tools and scale up treatment coverage in order to demonstrate quantitative progress, these commitments may not have been fully integrated into all the guidance, tools, and approaches promoted in high-prevalence countries. Data-driven accountability may come into tension with these rights commitments. A senior US official working with PEPFAR noted that while WHO has leaned toward advising countries to “do no harm,” PEPFAR’s approach has been to say,

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“It’s optional, but we judge performance based on whether you can show results.” [We tell] “X program, we expected you to reach this number and this positivity rate, and you didn’t achieve it. . . . Therefore you’re failing, and face a budget cut.” In that environment, people are really desperate to have better tracking systems.

In fact, the official said, the approach at PEPFAR has been to “find the positives” to a degree that may undermine their work on prevention: If you lower prevalence in the population, then you’re seen as failing for not finding enough positives. We’re chasing positives to a degree that sometimes feels out of balance. . . . We’re also trying to keep negatives negative. . . . You have to do both.

This pressure to demonstrate impact may have undercut the other work underway to combat gender-based violence, empower women and girls, and uphold the rights of people living with HIV. Thus, despite strong commitments to addressing gender-based violence including through targeted programming such as the DREAMS initiative, guidance on aPNS that may have been rushed out to facilitate donors’ and UN member states’ demand to improve treatment enrollment and meet 90-90-90 targets did not incorporate or address UN data showing high rates of intimate partner violence, or the delicate steps needed to elicit disclosure from the 30 percent or more of women who had ever experienced intimate partner violence. Seale said that WHO guidelines were dynamic: “We’re constantly reviewing and updating our guidelines with revised versions, as evidence comes to light. We’re doing that now.” Waiting for evidence of gender-based violence to revise the guidelines raises difficulties, though. Simply gathering that evidence can expose vulnerable survivors, many of whom may be economically or otherwise dependent on their abusers, to numerous risks: retraumatization, stigma, and retaliation. Absence of evidence should not be taken as evidence of absence. For this reason, ICRC’s policy is, without assigning legal blame on any party, that the institution takes a “reversed burden of proof” approach to sexual violence in conflict; the organization “operates under the assumption that sexual violence occurs in a given context, and therefore acts proactively in order to address it” with programs designed to meet the needs of survivors (ICRC 2019, 11). This is a radical shift in perspective. But faced with the widespread nature of a hidden and stigmatized reality, why not demand proof that 196

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the problem does not exist, and design programs under the assumption that it does? WHO could adopt a similar position to ICRC’s in regard to the reversed burden of proof for gender-based violence. Better still, WHO could use its own published data showing that this is widespread, that it is a driver of HIV, and that HIV disclosure often results in violence, as a basis for developing new guidance on how to incorporate more nuanced screening and referral services for gender-based violence into all HIV testing services. PEPFAR and other donors could even support rolling this approach out across Sub-Saharan Africa. Given WHO’s new plans to consult with women living with HIV, perhaps this will be considered. Certainly, the four women I had had the opportunity to listen to while looking into aPNS – Ambassador Birx, Rachel Baggaley, Saoyo Tabitha Griffith, and Patricia Asero – could probably make some progress if they were speaking to, and listening to, one another. In July 2019, Patricia Asero expressed her frustration online again, in response to a UNAIDS tweet that discrimination is fueling HIV among marginalized populations, with her own tweet criticizing “Discriminatory strategies e.g. APNS being rolled out across Africa” (Asero 2019). When we spoke that month, she told me that clinics were still “using the index patients to get their partners.” I asked Patricia if she had any evidence. She responded with frustration: “I’m aware that women have been kicked out of [their] homes. Others have decided not to go back where they were tested, because they will be asked to come with partners. How I wish I had the means to document.” She asked if I could connect her to funding to document these cases. I looked online and found some information on small foundation grants for women-led organizations, and passed those along. But I could not find grants to support an investigation by women living with HIV into intimate partner violence linked to index tracing. It didn’t seem to be a priority.

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8

“S O MA N Y H URDLE S J UST TO L E A V E T H E H O U S E”

Across the oceans, in Grenada, community-led research did elicit data on intimate partner violence, as well as other hidden complexities of the real lives of key populations who had long been uncounted. Faced with pressure to complete their ambitious sixcountry size estimation study before their grant ended and donors transitioned out of the Caribbean, CVC focused its efforts on strong engagement of community field workers, who had the trust of their peers and could accompany them in overcoming the numerous barriers to participation. In summer of 2017, the ethics review board approvals came through at last, and the Eastern Caribbean key population size estimation study took off at high speed. It was given fuel by the threat of diminishing global resources for health and the sense that this might be the last opportunity to get the first ever data on key populations. The research team had to adapt their methods to the countries, shifting their focus from surveying locations to working through networks of trusted community gatekeepers, strengthening the role of the local community-based organizations. The data was difficult to get, but the hard work produced a real breakthrough: granular data about hidden populations, vivid pictures of the difficult realities they faced, and stronger bonds between civil society and health officials. Of the more than 1,300 men who have sex with men surveyed across the six countries, CVC ultimately found, 47 percent reported experiencing verbal harassment because they have sex with men, 198

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Figure 8.1 CVC size-estimation study partner site visit in Jarabacoa, Dominican Republic. Credit: Estandar Video y Media

22 percent reported physical abuse, and 26 percent reported fear of walking around in public places because of the treatment they might receive as men who have sex with men (CVC 2018, 74). The obstacles to the study were real. A civil society activist working with men who have sex with men said, We have to understand that there are so many hurdles I have to go through just to leave the house. As I go down the road, there could be one guy on the street who calls me names, another one who threatens me, and I have to pass all those hurdles to come to a social.

As the study began to make realities that were normally hidden more visible, the risk of violence was heightened, especially for those most dependent on others. But working together on tight timelines, the research team made progress. They refined their research methods, and the research subjects themselves demanded some changes. The resulting research was validated in country workshops which John and CVC held in one country after another. The one I attended in Grenada was frankly revelatory, with officials and civil society activists crammed together in the back room of a sports stadium, around plastic folding tables, watching as the realities of the country’s hidden populations were revealed on projected charts for the first time. The sense of empowerment was palpable. 199

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This growing network of community advocates and health officials had refused to be “left to their fate,” as Mike Podmore had put it, during donor transition from the Caribbean. Their hard work did produce rich data, but that data raised difficult questions. * After even more delays in disbursements and approvals, the data collection began at last in July 2017. This work now had to be crammed into a few intense months: staff and tablets were limited, and both needed to be shared across six countries. The final schedule had a study in each country for two weeks over a four-month period (see Figure 8.2). As the research continued, the team had to refine their approach, taking lessons (and sometimes personnel) from one country and applying them in the next, working with national steering committees to adapt to each island’s specificities. I arrived in Grenada in August 2017, and was met at the airport by Mr. B, who was doubling as both site supervisor for the arm of the study interviewing men who have sex with men and project driver, while also continuing to work another full-time day job. Mr. B was in his thirties, with long dreads, a dynamic activist who organized parties on the side: one of those people about whom it is often said, “If you need something done, ask a busy person.” As he drove the winding roads to the apartment rental where I would join the research team at Fort Jeudy, Mr. B broke down their current approach.

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Figure 8.2 CVC/UAB timeline for size-estimation study. Credit: CVC 200

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So far, Mr. B said, as he navigated the sharp and hilly turns of Grenada’s back roads, things were all moving a little slowly. Grenada’s Carnival had taken place the week before the research began; Carnival is an event that consumes Caribbean countries for days, if not weeks. While the researchers were under pressure to produce results in just a few days, many of the people they wanted to reach were still at home in recovery mode. It was the “cool-down week.” As discussed earlier, John had done pre-assessments, visiting three islands – Grenada had been one of them – to meet local organizations, get a sense of the challenges and sampling issues the researchers would face, and draft the research protocol. Now the actual research was underway, and Grenada was the third country in the project timeline. The team had already decided to change their methodology based on their experience in the first two countries in the study, St. Lucia and Dominica. The original plan had been to use respondent-driven sampling, in which researchers identify “seeds” who have large groups of peers, and offer incentives to recruit other interviewees; and time-location sampling, in which hotspots are visited repeatedly to capture respondents who visit at different times. The OECS, the principal recipient for the Global Fund grant, had approved this and, in addition, had also repeatedly pushed for geolocated data for the hotspots. In reviewing the protocol, OECS wrote in a comment box: Procedures/methods: . . . please clarify that global positioning system (GPS) coordinates of venues will be collected during the community mapping and observation component of the formative assessment. . . . Clarify that GPS coordinates of venues will be collected again during [time-location sampling] (to check against the coordinates collected during the formative assessment). . . . Clarify how collection of GPS coordinates will be done (following appropriate standards). (CVC 2017)

But as he had since the beginning, John continued to resist OECS’ repeated demands for geo-located data: because the countries were small, he insisted, combining locations with other data would make individuals easily identifiable, and would expose them to the police, to the public, and to related risks. The research team had now made the decision to omit time location sampling and any geographic mapping altogether as methodologies, in response to concerns about risk and emerging realities in the field. It 201

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was becoming clear that there were few if any hotspots, few stable locations where key populations gathered regularly. Where they existed at all, those venues tended to be mixed, with key populations identifying partners through coded communications. As a civil society activist working with men who have sex with men put it, “Straight guys [on the down low] . . . want to go to the ‘straight’ clubs where you get the real ghetto deal guys. Many of them bring women with them.” To replace the time location sampling, Mr. B explained as we drove, the team had added Indigenous Field Worker Sampling. From among the seeds, the research team had identified local individuals who could be trained in the aims of the study, fieldwork protocols, ethics, informed consent, interview skills, and safety procedures. These indigenous field workers were more than enumerators – they consulted with the supervisors, conducted active outreach, and recruited new seeds. In other words, this supported the participatory action research approach with a community mobilization element: the young key populations activists were being trained and given extra responsibility, and they were building community networks. These young field workers were being encouraged to work autonomously, making decisions as they went. They were developing both research and leadership skills, and strengthening networks that could potentially be used for program outreach later, once the study was done. Among them, some, such as Mr. B and Kizzy, the former outreach worker with CHAA, had now been promoted to supervisory roles. They were now responsible for overseeing whether other indigenous field workers who reported to them were producing authentic data, whether the times and locations of interviews reported by field workers aligned with what was shown on the tablets, and so on. They did all this work under the watchful supervision of Julia Hasbun, whom I had met in Dominican Republic when she facilitated the workshop. She and I shared an Airbnb apartment with Phil Leon, a young and enthusiastic biostatistician who had been recruited by John Waters during the research in St. Lucia. Phil was conducting long qualitative interviews with individuals identified by Mr. B and Kizzy. At night, Julia reviewed her numbers, pacing and chain-smoking on the terrace of our shared Airbnb apartment, as the sun dropped into the Fort Jeudy Bay and the crickets began their loud whirring. While challenging to manage on a tight timeline, this mobilization of indigenous field workers and supervisors emerged as one of the most significant factors in the evolving methodology CVC used, and the one 202

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that helped to deliver rich research results in the end. It shifted the dynamics of the study perceptibly. While most of this book explores approaches to data-gathering and decision-making that are top-down, CVC was experimenting with inverting that power dynamic, retaining local control over the process, as the data-gathering became a tool for community mobilization and the community itself subtly reframed what would be measured, and how. I followed the research team for a week, observing their efforts to reach MSM and female sex workers. A typical day involved about a dozen interviews. Julia needed double that number and was getting frustrated. “I don’t know what I’m gonna do with these people, they take all the time in the world,” she groaned. Phil Leon said that earlier, in St. Lucia, he had seen how “[e]specially in a small island country where everybody knows everybody, they only came out after three weeks of persons who know them very well having little conversations.” Mr. B later reflected how surprised he had been that even people he knew well were reluctant: I tried to argue, why? There’s no names, you can use the tablet and answer questions without me knowing. Why are you refusing to do the survey? I’m the one administering it, we know each other, I know about you. Why are you declining? I still maybe don’t understand it. . . . The persons declining to do the surveys, that affected me a bit.

Later, he reflected that some of the upper-class respondents “are living their golden lives, and have a wife at home, they’re just an MSM, they don’t need to share their story.” More time to do the survey, he felt, would have generated bigger numbers. But in the long run, Mr. B was optimistic: “I think I have a great team. I just need to motivate them a bit more. I told one of them, ‘Bring me three clients and I’ll raise your pay per head,’ and he brought in four. I know the numbers will be climbing.” As difficult as they were to recruit, men who have sex with men were far easier to enlist than sex workers. Kizzy said that CHAA’s abrupt closure had burnt many bridges with that community: “Me trying to rekindle the relationships with persons and build back that trust and get them interested in participating. . . . CHAA went down in 2014. Now I’m rekindling the fire [and] some people are trying to question your motives, saying, ‘Where have you been?’” CHAA had also had more to offer sex workers in exchange for their participation in studies than did CVC, including free mental health care. Mr. B agreed that the closure of CHAA made the study even more challenging: “A lot of persons we 203

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have would have been in CHAA before; now we’re reaching out to them and getting them back.” A few days into the Grenada study, we saw this firsthand: Kizzy, Mr. B, and Julia went together to Mont Tout, an area where some sex workers lived and worked. We drove up the gravel road in Mr. B’s car and ended up parked near a rum shop, an unmarked shanty with a television playing soap operas next to a wooden bar. A few men were in the bar, nursing beers. Kizzy used the back seat of Mr. B’s car to interview sex workers, several of whom were teenagers. One was really excited to participate in the research and said she could line up numerous interviews over the next few days. While she worked, Julia and I left her in the car and went into the rum shop to buy a drink for a field worker. On the spot, Julia asked the bar owner if they could rent a room in his apartment upstairs for interviews. The bar owner readily agreed, and soon Kizzy and the others were hard at work upstairs. Periodically they called out the window to Julia for technical support with the tablets. Kizzy said afterward that she had had the most interviews that day of anywhere on the island. This arrangement lasted exactly one day. A neighbor noticed all the women going in and out of the bartender’s apartment, including a white woman she suspected was a Russian escort (actually this author), and called the bartender’s wife overseas to alert her that the apartment was being used for international trafficking. That put an end to that arrangement. In the following days, the team switched locations frequently when reaching out to sex workers, moving to parks and other venues. Some people in the drug trade, who had a stake in the sex work industry, began to recognize Mr. B’s car during the research, and he had to switch vehicles. Another sex worker seed was threatened and had to go underground. Kizzy reflected that the sex workers had numerous burdens, including child care and clients to think about, and their partners were suspicious: “You don’t want to create problems for the ladies. The partners can shut it down immediately. We had ladies coming in, saying, ‘I’m eligible today. I wasn’t eligible yesterday but I’m eligible today.’” After the research was done, Dr. Martin reflected, “We found some things that we didn’t realize. It made us understand how well organized the sex workers were, and also made us realize how dangerous it was.” Mr. B, however, came to see some of the threats as a form of community protection: “We realized that the culture here is different, 204

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in terms of everyone in the community knows who is a sex worker, but they . . . don’t allow outsiders to come in and do what they want to [their] people. . . . Everyone kind of protects their own.” These are some of the complexities of doing a size estimate for sex workers: the public narrative, John observed, was that all sex workers were foreign migrants. The negation of the existence of local sex workers in Grenada was feasible, in part, because the industry was well-hidden. SEX WORK, TRANSACTIONAL SEX, AND INVISIBILITY

Another challenge in conducting the study had to do with the emergence of a previously hidden population of transgender people during the study of men who have sex with men and the challenge of quantifying sex workers in a context where transactional sex is widespread. CVC had to wrestle with these problems of quantification and commensurability of global health categories in a fluid local context in which some terms were challenged by participants. The team had decided, after much debate, not to include a question on transgender people, because there was so little evidence that they existed in the Eastern Caribbean. However, across all the countries, CVC found ultimately that nearly eight percent (7.9%) of respondents identified as female, 3% identified with both male and female genders, and 4% identified specifically as transgender. Taken together, respondents identifying as transgender and with a female gender identity make up a total of 12% of all respondents (11.9%). (CVC 2018, 82)

CVC explained that many biological males who identify as female must suppress this, given that “the macho culture of the Caribbean results in stigma against men who don’t act like men via hatred and violence for their refusal to conform to normative gender identities” (CVC 2018, 81). In a second complex challenge, the researchers had to wrestle with whether and how to quantify sex workers given that many women engage in transactional sex. Some of those engaged in the study explained that some men became “supporting friends” of women through gifts, paying cell phone balances, helping with the rent, or other contributions. Jeannine, from Grenada Planned Parenthood Association, commented that in advance of the carnival season, 205

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women had expenses to cover: hair, nails, outfits. To meet those costs, some women had a friend to call who would help financially in exchange for sexual favors. Kizzy agreed: as an example of how embedded this is culturally, she started singing a hit soca song by Chain from the previous season, “Come on the Thirty-First,” in which the male singer is “saying come on payday for whatever you need.” The song played on a pun, she said: “You gotta wine on my turtie first” (‘‘turtie” is slang for penis). “It’s just a norm,” she said. “There are more persons engaged in transactional sex, simply because of the unemployment rate.” Tourism opened up even more of these transactional sex opportunities, she said. Phillip’s history of women in Grenada shows that the practice of transactional sex emerged under British colonialism, as one of the diverse ways that slave women used their agency to gain power where they could (Phillip 2010). Grenada had a female to male manumission rate of 2:1, which Phillip suggests may in part have been because some women won freedom by becoming mistresses of their owners (Phillip 2010, 36). A few became successful property owners with estates on multiple islands and in London, passing the accumulated property on to daughters and granddaughters (Phillip 2010, 37–38). In the CVC study, to estimate the population size of sex workers was to impose an etic, external category on an emic or local practice; but it was an essential part of the work of creating a size estimate that would be commensurable across the region and internationally, and that would make a case for allocation of resources to meet the needs of sex workers – producing data that was sorely needed in the six countries being studied. The CVC research team decided to include a question in the survey about whether a woman’s “supporting friend” would still get sexual favors if he did not compensate her for them financially. Women who said no to this question were counted as sex workers. However, a number of women recruited for the CVC study rejected the term “female sex worker” (FSW), saying it was stigmatizing. Instead they insisted the research team use a new term, “females exchanging sex,” or FES (in the working language of global health, it seems that there must be always an abbreviation, so they coined their own). CVC’s solution was to defer to them in this choice and to use the term “females exchanging sex,” explaining what it meant in reference to the global health etic categories in their report (CVC 2018, 23). 206

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Paul-Gilbert at NSWP said the rejection of identification with sex work by some of the participants in the CVC study was not unusual in sex worker organizing in other contexts. He explained that the Global Network of Sex Work Projects began using the term “sex worker,” coined by Carol Leigh in the 1970s, “to put the activity of prostitution within a labor framework, so that means they could access their labor rights. That is why the NSWP board made a decision to constantly use this term, because that helps us in our advocacy with the labor movement.” Being a sex worker, he said, is not an identity but a job: “People will enter sex work for a variety of reasons, and for very a varying amount of time as well.” In countries where there is no funding to build sex worker-led programs and organizations, you don’t see champions, leaders of the sex worker movement that could make the link between that term and the labor framework, that could make the link [with] being out and being proud. I think that’s where networks have an importance, and especially regional and global networks, in ensuring exchanges – not to stifle the voice, but [enable sex workers] to make an informed decision, and see different opinions as well.

John Waters agreed, and drew the link to CHAA, again: the organization had done some work in the Eastern Caribbean to empower sex workers, but “as CHAA, not as indigenous organizations,” so when CHAA closed, that work had ended. He believed this lack of empowerment work was part of the reason for the discomfort study participants felt with the term “sex worker.” Other complex realities emerged in the course of the study. Troublingly, respondents began to share that many had survived child sexual abuse. Several members of the CVC research partnership described teenage girls they knew as having to “make my face” to get the funds for fees related to schooling – “making my face” is a local phrase for transactional sex. Kizzy worried that these adolescents engaged in transactional sex were one group who would not be captured in the study, because of the age of consent required of participants: That’s a subpopulation that’s going to get missed. They’re from an impoverished background, education is the only way out, they’re trying to finish the process. Their families can’t afford to finance their education, so they’re under pressure and they’re forced into transactional relationships with older men. 207

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Given entrenched gender inequality, transactional sex also exposed young women and girls to significant risks. When teenagers finish school and want to move on, Kizzy said, some faced threats from their former partners. She remembered a case from several years earlier in which a girl was murdered by an older man who had financed her education. The girl was preparing to go to college and ended the relationship; she was brutally murdered, left dismembered. “These are the kinds of girls who will be missed.” Hazel Da Breo, a psychotherapist and founder of Sweet Water Foundation in Grenada, also located the roots of child sexual abuse in Grenada’s painful history of slavery: Remember that during slavery, children were expected to pull their full weight in the fields, to take blows like adults, and to have sex like adults. We had hundreds of years of this. Now we are asked to not see children as small adults, but as children in their own right, with childhoods deserving of protection. That is new, you see?

The fluid nature of gender identity, the deeply interwoven nature of transactional sex and sex work, became points of debate among respondents in the Eastern Caribbean study. Anthropologists consider an “etic” analysis to be a description of behavior as seen from outside of the context, which describes behavior in ways that can be compared across diverse contexts. This often differs from the emic understanding of the behavior, which is a local interpretation made within different frames of reference and often carrying different meanings from the etic label. In the context of state mapping and representation, an etic classification requires a “disciplining” or abstraction of the observed reality: [T]he actual social patterns of human interaction . . . [are] bureaucratically indigestible in their raw form. No administrative system is capable of representing any existing social community except through a heroic and greatly schematized process of abstraction and simplification. . . . Their abstractions and simplifications are disciplined by a small number of objectives. (Scott 1999, 22–23)

As Merry and Wood note in Tanzania, indicators used in global governance translate in ways that are multidirectional: Translation takes place across continents, languages, and cultural contexts since indicators are designed to create commensurability and 208

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facilitate comparison across many different contexts . . . [Thus], local meanings are displaced by terms that enable global comparisons and conversations. (Merry and Wood 2015, 213–14)

By definition, a biobehavioral survey must map intimate local behaviors onto external categories. Hacking (1992) sees this as a top-down labeling to which the labeled person responds: “numerous kinds of human beings and human acts come into being hand in hand with our invention of the categories labeling them” (1992, 87). Boellstorff (2011) has rather shown how the category of “MSM” itself went through repeated shifts, creating new forms of public identity from what had been a behavioral category used in public health. Other scholars have explored the limits of the MSM category for capturing those who do not fit into its sexuality and gender frame (Kaplan et al. 2016; Khan and Khan 2006; Young and Meyer 2005). The lack of nuance in many resulting HIV studies of men who have sex with men, Gill (2018) argues, has been problematic in the Caribbean, even as it has also created a valuable basis for community mobilization. Because it was both a research and organizing tool, the CVC study strove to walk a thin line between etic and emic categories. The study was sometimes top-down – using established international social science methods to gather quantitative data that forced some local specificities into etic categories in which they were an awkward fit – even as it strove to be ground-up, using those categories to mobilize new networks to demand their right to health. John walked the thin line in the middle, translating for both sides. While the research team had to adapt to their context, their ultimate results were to some extent shaped by the agenda of the global health governance agencies funding the research: To count key populations defined in a global consultative process, making problems and populations visible to global health agencies. Budgets, timelines, and donor-imposed etic categories all played a role. But in most field research projects, there are moments when local experience overwhelms the frame imposed by the researcher. These realities can fragment and re-align social forces in new patterns, around different and shared missions. This may be especially powerful in a context where difficult complexities – of gender identity, of sexual behavior, of violence – have long been hidden and denied. 209

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By the end of the week, as the numbers began to grow, the anxiety shifted perceptibly into excitement about the future report. Phil, the biostatistician, could not wait to get his hands on the raw data: “We have no idea of their status, no idea of their behavioral issues. . . . When funding agencies want us to give them information we really can’t. I can see this would affect future funding, or even being taken seriously as a ministry.” A civil society activist working with men who have sex with men said: We do our own tally for men who have sex with men and sex workers and the number we get each month, with the numbers up on a sheet on the wall, but it’s not as precise. At the end of day, you want to tap in and tear the sheet to see who’s behind it.

* The research was completed at last, and the numbers compiled and analyzed. In 2018 CVC and the national steering committee held a series of Data Analysis and Validation Workshops in each of the six countries, including one in Grenada, before delivering the final report to the OECS. As we approached the meeting venue, John joked that there had been so much interest in the study, he’d had to book the national stadium. In fact, we met in a room inside the stadium, because the crowded Ministry of Health building had no available meeting rooms. But he was correct about the high level of interest: nearly everyone I had met in the course of the study was crammed into the room, along with many others. Dr. Martin from the Ministry of Health and some colleagues were there, of course; Kerlin Charles and Mr. B from GrenCHAP; Jeannine from Grenada Planned Parenthood Association; Hazel Da Breo with a young relative who sat drawing pictures while we talked; and Kizzy, now in her new role as an M&E officer. There were also representatives from Her Majesty’s Prison; the National Council on Disability; the Ministry of Youth, Sports, Culture and the Arts; the Ministry of Housing; the Ministry of Education and Religious Affairs; the national statistics bureau; and a community relations officer from the police force. All of us crammed together around folding plastic tables while Dr. Martin spoke. He was happy to share that there had been a slight drop in HIV incidence over the past few years, and that the ministry had tested more 210

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people than ever before, in part thanks to getting GrenCHAP and Planned Parenthood certified as community testing sites. He called them with pride, “our two flagship facilities.” But he warned, “That doesn’t mean we get to sit on our laurels; we have to be proactive and aggressive.” John leaned forward on the lectern, clasping his hands together. “I’ve brought you some goodies,” he said. They’re your goodies, so this is not a gift per se. At CVC, we felt it was important to do this exercise. All too often we as civil society are often asked to help, and civil society gets roped into recruiting, ensuring participants are involved in the study. Frequently afterwards, that’s where things stopped.

The purpose of this meeting, he said, was for Grenadians to see the “huge amount of data” they now owned, to examine and validate the data, and, he hoped, to suggest some ideas for secondary analysis to be done with this treasure trove, so that the data could be used to characterize and meet the needs of sub-populations. Altogether they had interviewed 1,328 men who have sex with men and trans women in five countries (St. Kitts and Nevis, Antigua and Barbuda, St. Lucia, Grenada, and St. Vincent and the Grenadines), including male sex workers and young men who have sex with men younger than the age of eighteen. They had interviewed 1,079 female sex workers, or females exchanging sex, in St. Kitts and Nevis, Dominica, St. Lucia, Grenada, and St. Vincent and the Grenadines. Using multiple methods, John’s colleagues at University of Alabama at Birmingham would identify an estimated size for each population in each country. Projecting charts on the back wall of the room, John highlighted some of the findings for collective discussion. Together, the data revealed the long-hidden populations. The majority of Grenadian men who have sex with men, it turned out, identified as either Catholic (nearly 27 percent) or Protestant (over 47 percent). More than 10 percent of men who have sex with men respondents were in a committed relationship with a woman, well over half had had sex with a woman in the past twelve months, and 30 percent were fathers. The majority, 67 percent, had said that they were not out to their families. The study also revealed some of the hidden violence that researchers and community members had spoken about: almost 13 percent of the men who have sex with men reported that they had had their first 211

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sexual experiences before the age of 10. Nearly 14 percent had had their first sexual experience with a family member. Nearly one quarter of the respondents in the study of men who have sex with men disclosed that they were survivors of some form of sexual violence. The overwhelming majority said that they had never disclosed this to anyone before. Mr. B’s team and his peers across the six countries had done impressive work in winning trust and eliciting disclosure from one of the most hidden populations – male survivors of sexual violence. Almost one-third of the men had never tested for HIV, and their level of knowledge about HIV and how it is transmitted was generally poor. Nearly one in three had not used a condom in their last sexual encounter. One in five respondents said they would avoid health care out of fear of being outed to others in the community. The gaps in services for key populations were becoming apparent. Finding these men again and persuading them to test for HIV would be critical to the regional response. John explained that the research team had originally planned that they would not try to estimate numbers of transgender people. However, as noted previously, 12 percent of those interviewed in the men who have sex with men arm of the study had identified themselves as female or transgender. Based on this, John said that CVC would work with the research team to develop a size estimate for transgender people in the six countries. The female sex workers surveyed had reported high rates of sexual violence and incest as well. Forty percent had had no information on HIV prevention, had low levels of knowledge about HIV transmission risk, and engaged in high rates of condomless sex. Thirteen percent had never had an HIV test, and 18 percent avoided health care. More than half reported having been physically abused by a man at some time. John paused on each slide to talk it through with the room, to give them time to absorb the new information, to gauge their reactions and gather feedback. For most participants, the most surprising data seemed to be the religious affiliations for men who have sex with men, given the frequent denunciations of homosexuality from pulpits across the region. “It’s important for the church organizations to see that, and for us to be in dialogue,” said Kizzy. One young woman from the Ministry of Health said they should present this data to the churches and promote acceptance: “Even if you don’t accept what they’re doing, accept them as individuals. . . . If we 212

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get [religious leaders] to see them as people, it could be different.” Kizzy retorted that acceptance was not needed: respect for human rights was. As the group worked through the data, each mulling over different questions it raised for their own work, they began to shift towards thinking about how they could work together. Another government official chimed in that the information John had shared was “very interesting, a little disturbing. It’s good to know the facts and from there try to put structures in place, bring together stakeholders to work together for the benefit, the objective of lowering HIV.” Dr. Martin agreed and homed in on the data showing key populations’ avoidance of health care. He was already thinking about what he was going to do to address stigma. Jeannine, now chairing Grenada’s Country Coordinating Mechanism (CCM) for the Global Fund grant, addressed the room: The purpose of having data is not just to call numbers. [A few voices called out, “Amen!”] It’s to use the information for programming, so that people who need assistance get it, and the work that needs to be done, gets done.

The CCM, she said, would use this data in the future. Kizzy advocated that in any planning, the group not forget that the needs of men who have sex with men and female sex workers were different: “We have to not forget the female sex workers; they are a unique community” who should have their own self-run programs. An indigenous field worker who had worked with GrenCHAP rose in front of the room and introduced himself. He said: I’m happy we were able to reach all these people. It was long hours, long weekends, long drives, but I’m happy to see the fruits of the labor. I’m sad, because I see we do have a lot of work to do [several voices called out “Yes!”], about how to educate people how to protect themselves; but I’m happy to see that it came out good.

The young woman from the Ministry of Health who had spoken earlier agreed. She had been in too many meetings with Dr. Martin, she said, where she had watched him get put on the spot, because Grenada “had nothing” in terms of epidemiological data: The data is a great step. It can act as a bridge to other things, not just to reaching government, but on a community level – so we can see the 213

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people there in a tangible form, in a way that we acknowledge we are still human beings and we have rights. The data looks at so many different questions. This is publishable data. We can put out the data and people know what is happening in our country. We now have something to say.

The gathering in that room was the beginning of what could be a new phase of Grenada’s HIV response. The community mobilization had gathered new data, developed new partnerships, and could now open a conversation about how best to meet the needs the study had revealed. The resulting size estimates are listed in Table 8.1: having them at last felt like a triumph, said Mr. B later: “We achieved something. We started, went through a process: here is the end result. That was good and really exciting.” The remaining question was how – or whether – these data would be used to make decisions; how they might shape eligibility for small populations in small countries that were all competing for limited resources.

TABLE 8.1 Estimated key population sizes for Eastern Caribbean, 2018

Population size estimates

Grenada

MSM Analysis of three method estimates1

Transwomen Analysis of two method estimates2

Females exchanging sex (female sex workers) Analysis of three method estimates3

Mean

Median Mean

Median Mean

Median

1923

2419

170

1000

170

1056

1. For men who have sex with men, the estimates are based on three methods: unique object identifier, wisdom of the crowd with truncation, and web/ mobile apps multiplier. 2. For transwomen, estimates are based on analysis of literature review and eligible study participants. 3. For females exchanging sex (female sex workers), estimates are based on literature review, unique object identifier, and wisdom of the crowd with truncation. Source: Waters et al. 2018.

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9

THE PANO PTI CO N A ND TH E POTEMKIN

The air was cool and crisp, and the sky blue over distant mountains. The Chinese prison warden, a hearty man in his forties, led me and my expat photographer friend through the entrance of the Yunnan Province Kunming Municipality Mandatory Drug Addiction Dropping Institute (known as Changpo), past a brutal photo display of the harms of drug use, through a landscaped visitor’s garden, and out into a gray courtyard walled by barracks. Seated in rows on child-sized red and yellow plastic stools, hundreds of men with shaved heads in track suits bowed their heads. Shaved heads are a mark of humiliation in China. I jotted notes as I walked. We were a long way from the CVC meeting, in time and space: a decade and a half earlier, and on the other side of the globe. This was Yunnan Province, China, in December 2002. As a newly hired researcher for Human Rights Watch (HRW), I had talked my way into a Chinese compulsory drug detention center, site of what I had heard were serious human rights violations. While the CVC study shows what kinds of mobilization and truth can be produced out of a trust-based government-civil society partnership that centers the empowerment of young leaders from key population groups, this was the opposite: covert civil society counter-surveillance of a tightly restricted facility under multiple rings of state surveillance, located at the outer limits of international regimes of monitoring and accountability. The warden stood in front of the rows of men, and gave a beaming smile and a tour guide’s speech about the detention camp for me and my 215

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friend. The detainees kept their heads down, avoiding eye contact. The center was the largest of its kind in Asia, said the warden. Detainees withdrew from heroin using an herbal remedy, received moral and legal education, and did manual labor: manufacturing and farm work, raising chickens, fish, ostriches, pear trees, and more. They even, he bragged, manufactured fake diamonds that were indistinguishable from the real thing. “How much do you pay them?” I asked. The warden laughed. “We don’t pay them. They pay us for their room and board.” He led us to a medical facility, where three men squatted on the ground, noses running freely. A man in a white lab coat stood nearby, smiling. Herbal remedy or not, these men were showing symptoms of sudden withdrawal from heroin, which can cause nausea, anxiety, pain, spasms, vomiting, and more. The UN Special Rapporteur on Torture and Other Cruel, Inhuman or Degrading Treatment or Punishment has since determined that forced drug withdrawal is a form of cruel or inhuman treatment that in some cases constitutes torture (Ezer et al. 2014, 34; General Assembly 2013; UNODC 2009). Then we passed through a shed, where from my notes, “several hundred men were inside a covered area mopping the floor, and several dozen more were outside mopping the courtyard floor. The men in the covered area were crouched over holding rags in water, and at a count they had to run across the covered area, mopping in a row.” Water, water everywhere. Why so much water? The warden had stalled us for an hour before he got the call that the facility was ready for visitors. What had been washed away? The facility shone in the sunlight. The men with bowed heads shot looks at us. My friend’s camera shutter echoed in the courtyard. We could not speak to them. However, working with local and international civil society organizations, I had already interviewed other Chinese people who use drugs, who had described their experiences in Changpo and related facilities. They had described being beaten by police, sent to camps for months or years of forced labor; about denial of food, water, and medical care. They were tested for HIV, to contribute to national surveillance data, but some didn’t learn their status or get treatment until after their release. In its gleaming contrast with this suffering, Changpo was a Potemkin village: a display aimed at deflecting accountability for grimmer realities. The people I had met had described torture, beating, overcrowding, filth, drinking out of buckets: “People slept everywhere, they filled up the 216

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floor,” said one. But in Changpo, we were shown spotless and empty dorms, well-equipped with gyms, pool tables, and badminton courts. As evidence that Changpo was an international model, the warden shared an English-language brochure with photographs of visiting international dignitaries, including a senior US government official. When the HRW report, Locked Doors: The Human Rights of People Living with HIV in China (2003) came out the following year, it included a short chapter on drug detention centers among other issues. It was met by international media coverage as well as Chinese government condemnation and denial (Kaiser 2003; Mayor 2003). In the ensuing months, though, a series of public events increased the pressure on China, and in 2004 the government announced it would begin providing free HIV treatment and care to all under the “Four Free, One Care” program. A few years later, I arranged HRW’s first meeting with a senior Chinese government official. He met me in the reception room of the Ministry of Health, where we were surrounded by bouquets of plastic flowers. He graciously offered me a seat and then proceed to denounce me for publishing “baseless lies and anecdotal research.” Why not work with the UN human rights office, I asked, and allow a full investigation? He declined. This chapter is a corrective to the more optimistic one that preceded it, and it is not very much about quantitative data. Rather, it reflects on the troubling limits of audit culture, the various systems of monitoring and surveillance put in place by international development agencies and human rights advocates. In 2013, ten years after the visit to Changpo, as senior human rights advisor at the Global Fund in Geneva, I was tasked with developing a corporate KPI on human rights. Part of the pressure demanding this came from international advocacy, which I had ironically helped to create a decade earlier, demanding that donors cease financing programs inside compulsory drug detention centers. The challenges of putting in place systems of compliance to ensure that aid money was not financing human rights violations, including in compulsory drug detention centers across the border from Yunnan in Viet Nam, became a public difficulty. They took me back often to my notes and photos from Changpo, to wonder: what can be known, from Geneva, about what really happens in places situated within multiple circles of top-down surveillance and display, where the panopticon confronts the Potemkin? Foucault (1995) has famously described the panopticon, a prison tower surrounded by cells that open toward the tower. Whether or not anyone is actually in the tower at any given time, its presence promotes inmates’ obedience. Foucault wrote, “Power should be visible and 217

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unverifiable. . . . The inmate must never know whether he is being looked at at any one moment; but he must be sure that he may always be so” (Foucault 1995, 201). The Changpo compulsory drug detention facility I visited in 2002 was a panopticon nested within the larger panopticon of Chinese society, which has since nearly perfected its system of high-tech surveillance and suppression of civil society. China was one node in a then-emerging global regime of a “war on drugs,” which has resulted in detention of and abuses against millions of people who use drugs, and extrajudicial execution in some countries, but has failed to curtail drug use. And it was also situated at the limits of a global governance panopticon, which uses civil society monitoring and accountability, the kind done by human rights organizations, to instill good behavior in states. In the end, peer-led groups and rights activists within and outside of China, Viet Nam, and other countries have managed to shift drug policy in small ways, but hundreds of thousands are still detained in these and other abusive facilities. Most of this book is about states monitoring key populations. As this chapter explores, key populations advocates and their allies also try to reverse the lens, monitoring and demanding accountability in order to influence the behavior of others. But their influence is partial at best. * The Human Rights Watch report (2003) which resulted from that trip to China included just a few pages about Changpo and the detention of drug users. In the ensuing years, Human Rights Watch and other organizations produced many more reports, as did other organizations, including peer-led groups of people who use drugs in Asia. The global war on drugs has cost billions of dollars and had vast casualties. Punitive approaches that target people who use drugs, arguably the most vilified of all the key populations, have failed to end or even reduce the use of drugs. While HIV incidence has decreased globally, it is on the rise among people who inject drugs (UNAIDS 2019b). In the Philippines, there have been thousands of extrajudicial executions as part of a national crackdown. In other countries, harsh and long prison sentences are meted out to those who possess and use even small quantities of drugs. In countries with compulsory drug treatment, such as China, inmates may be detained for months or years; detainees are often sent to the 218

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facilities by police, without trial or access to defense attorneys (Amon et al. 2013; Jurgens 2012). There is a lack of HIV prevention, treatment, and care services, placing detainees at higher risk of the epidemic (WHO 2009a). Torture, sexual violence, and forced labor were widely documented in compulsory drug detention centers by Human Rights Watch researchers after I left the organization (Cohen and Amon 2008; HRW 2010, 2010a, and 2012). Youth are among those detained in these abusive conditions: in 2008 nearly one quarter of detainees in Cambodia’s centers were age eighteen or younger (HRW 2010). While the largest facilities are overcrowded and lack adequate medical care, professional staff, food, and clean water, the worst facilities are literally pig sties, in which detainees live with animals and their waste (HRW 2003). Torture is used both to punish infractions of the rules and to deter future drug use: chaining detainees in the sun for hours, isolation, beating, and sexual abuse have all been reported by the UN Special Rapporteur on Torture (General Assembly 2009). Compulsory drug detention centers have been recognized by UN agencies as a violation of international human rights law, and have been condemned by the UN Special Rapporteur on the Right to Health and the UN Special Rapporteur on Torture, as well as the International Narcotics Control Board (Human Rights Council 2009; INCB 2016; SR on the Right to Health 2012). In 2012, twelve UN agencies issued a joint statement calling for the closure of all compulsory drug detention centers (ILO et al. 2012). In 2019, the UN Special Rapporteur on Cambodia noted the death in custody at a detention center (Prey Speu) of an alleged drug user with a mental disability who was cremated prior to family notification and without investigation, and called again for an end to arbitrary detention and involuntary “internment and treatment without proper independent authorization and oversight” (Human Rights Council 2019). Amon et al., summarizing their research on drug detention centers in China, Cambodia, Viet Nam, and Lao PDR, reported: Every former detainee interviewed described physical violence as a common element of life inside drug detention centers. Beatings, whippings, and electric shocks were meted out by both center staff and by fellow detainees in supervisory and disciplinary roles. Individuals most often reported being beaten for violations of center rules, such as smoking cigarettes, gambling, playing cards, failing to work quickly enough, or failing to keep pace with forced exercises. . . . Former detainees also reported

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being beaten upon arrival at the detention center as a part of hazing – or for no discernible reason at all. . . . Former detainees in Viet Nam, Laos, and Cambodia also reported that detainees were tied up in the sun as punishment. Punishment and/or isolation cells were reported by individuals from each country. (Amon et al. 2013, 131)

Meanwhile, despite international criticism, the Chinese approach began to be adopted in Southeast Asia. While the Asia-Pacific transformed itself into a global manufacturing powerhouse, compulsory drug detention centers grew in parallel, taking those who dropped out of the formal economy and forcibly “reeducating” them as laborers. At least eleven countries in Southeast Asia and Latin America detain people who use drugs in compulsory drug detention centers (UNAIDS 2019b, 36). In 2014, a review of reported data from Cambodia, China, Lao PDR, Malaysia, the Philippines, Thailand, and Viet Nam estimated that 450,000 men, women, and children were detained in compulsory drug detention centers, the majority in China (Lunze et al. 2018). Some East and Southeast Asian countries have committed to transitioning to voluntary treatment facilities, but progress is slow (Kamarulazaman and McBrayer 2015). Proponents of compulsory drug detention, such as Chinese health official Wu Zunyou, have argued that this is the only way to treat drug dependence among “a certain proportion of opioid-dependent individuals [who] persistently refuse treatment” (Wu 2013). But studies have found that in fact both the fear of being detained in them, and detention itself worsen the health of detainees: relapse in Malaysia was more rapid among individuals released from compulsory facilities than those from voluntary facilities (Wegman et al. 2016). In Thailand, there was actually a positive correlation between compulsory drug detention and increased spending on drugs per day by those released. Studies have also found “a relationship between exposure to compulsory drug detention and the avoidance of healthcare,” because former detainees fear being detained again (Hayashi et al. 2015). And it is difficult to argue that public health is the main concern: while China scaled up its internal war on drugs, authorities largely looked the other way as alcohol consumption increased significantly in China, reaching “epidemic proportions” (Heng et al. 2015; Tang et al. 2013). Alcohol production has increased more than fifty-fold since 1952 (Cochrane et al. 2003). Why do these abusive facilities persist? In part, perhaps because they arose during the moment when China was transition from socialism to 220

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capitalism at what was otherwise a chaotic time. They may have contributed legitimacy to an authoritarian state for those within the country who were concerned about increasing rates of crime and drug use. The role of the state as a strict disciplinarian, enforcing its own moral code, was to “reeducate” those on the margins of society and turn them into cogs in the larger productive manufacturing system. Foucault’s argument is that prisons played this kind of legitimizing role in the industrial revolution in Europe: with the rise of factories, European prisons became a parallel type of moral factory, “reeducating” malcontents into productive laborers. European prisons in the industrial revolution era were a form of punishment “that act[ed] in depth on the heart, the thoughts, the will, the inclinations” (Foucault 1995, 16). Manual labor was moral re-education in the European industrial revolution, because many people believed that “idleness was the general cause of most crimes. . . . Hence the idea of a house that would in a sense provide a universal pedagogy of work for those who had proven to be resistant to it” (Foucault 1995, 201). Foucault wrote that this moral discipline derived from bodily discipline, such as intense, militarized rote labor: reminiscent of troops of female detainees I had seen marching together in Changpo, army-style, shouting slogans such as “Drugs are bad! I am bad!” Beyrer wrote that drug detention centers in Asia reminded him of “the accounts of mental patients from 18th or 19th century Europe – with shackles, chains, and beatings masquerading as treatment, gross overcrowding, the ever-present stench of human waste” (Beyrer 2010, 5). In China, similarly, the use of forced labor to morally “reeducate” wrongdoers dated from late Qing and early Republican-era criminal justice reforms, and was expanded in 1955 under Mao to “morally reeducate” political dissidents and others viewed as outside the socialist value system, including street people, sex workers, juvenile delinquents, and political and religious dissidents (Fu 2005). Forms of moral “reeducation” like these aim to enhance the authority of the ruling regime. In recent years, China has incrementally changed its policy. As Table 9.1 shows, the numbers of those detained in these facilities has slowly reduced. A 2011 regulation made voluntary rehabilitation an option. In 2013, officials announced plans to abolish Re-education through Labor, though many of the abusive practices persisted (Amnesty International 2013). By 2018, there were two million registered users of drugs and 279,000 visits to compulsory drug detention centers, a significant decrease from a high of 319,000 detained in 2015 (Ma 2019). 221

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TABLE 9.1 China’s reported drug users, drug detention, and community treatment, 2013–18

20137 20145, 6 20154 20163 20172 20181

Registered users of drugs

Visits to drug detention

Visits to community treatment and/ or rehabilitation*

2,475,000 2,955,000 2,345,000 2,505,000 2,553,000 2,044,000

242,000 264,000 340,000 357,000 321,000 279,000

184,000 242,000 319,000 304,000 260,000 242,000

Sources: 1. Ma 2019; 2. Liu 2018; 3. Zhang 2017; 4. Lu 2016; 5. Yang 2015; 6. Xiao 2015; 7. Huang 2014. Emile Dirks provided assistance in compiling and interpreting these sources. * Estimated in some cases by combining reported numbers for community treatment and rehabilitation.

The head of China’s Drug Addiction Administration Bureau admitted in a television interview in 2017 that despite its commitments to doing so, the national system was slow to transform “from a re-education through labor function to a drug rehabilitation function” (Zhao 2017). The proposed layoff of hundreds of state employees if centers were closed poses risks to state-run economies, and there are entrenched financial interests which profit from free labor (Kamarulzaman and MacBrayer 2015; International Labor Rights Forum 2014). Thus, while China has received some international praise for increasing support for harm reduction services, it is important to remember that hundreds of thousands of people who use drugs are still detained in abusive compulsory drug detention centers – possibly the largest number of people who use drugs in administrative detention anywhere, though without more data from countries employing this approach, it is difficult to say this for certain (see Table 9.1). Moreover, the shift to reduce numbers in detention reflects a trend toward more precise forms of targeted policing, using new technology such as biometrics, that surveil drug users and others in daily life: in effect, an expansion of the panopticon beyond the walls of the detention facility. 222

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Emile Dirks, founder of the China Drug Crime and Detention Database, said in an email on July 19, 2019, that community-based treatment is integrated into more sophisticated systems of surveillance and “stability maintenance” that “keep users of drugs out of drug detention, while still allowing the police to monitor and control them as a population.” China, he argues, developed an extensive system of surveillance of targeted population groups that combined “profiling, extensive personal and biometric data collection, and location-based tracking,” extending even to police software that combines facial recognition with two-dimensional maps of apartment complexes to “associate particular key individuals – whether petitioners, foreigners, users of drugs, “cult” members, or the mentally ill – with specific apartment units” (Dirks 2019). He argues that this approach, piloted with people who use drugs, has since been refined in Xinjiang to control Muslims in the region and is now being expanded more widely. Chinese authorities use facial recognition software and artificial intelligence to racially profile and track Uyghur Muslims as part of an expansive system of detention and surveillance (Mozur 2019). THE HUMAN RIGHTS KPI

The abuses in compulsory drug detention centers proved difficult to document and expose internationally. As researchers continued to attempt to gather accurate data about these closed facilities, they contributed to a wider debate about the ethics of engaging inside the facilities, including by the Global Fund. A decade after that initial visit, I found myself in the position of being tasked with developing policies and monitoring mechanisms for services funded inside compulsory drug detention centers. In the decade after that brief visit to Changpo, as touched on above, Human Rights Watch, Open Society Foundations and UN Special Rapporteurs amassed a body of evidence of torture and forced labor inside the facilities. They and regional and global networks of people who use drugs used this evidence to advocate with global health agencies. One significant result of this was that the Global Fund began to incorporate human rights into its mandate. In 2010, Human Rights Watch and other civil society activists wrote to Michel Kazatchine, then the Fund’s executive director, to share information about abuses and to call on the Global Fund to withdraw 223

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support for health programs in the facilities. Kazatchine responded with public statements and letters affirming that the centers violated human rights standards. However, he asserted that he believed the Fund had an obligation to provide health services to those detained in them: Depriving detainees from accessing life-saving treatments and the means to protect themselves from HIV and other preventable conditions is inhuman. Until these centers are closed, the Global Fund will not exclude funding effective, evidence-based HIV prevention and AIDS treatment in the centers if detainees are otherwise unable to access these services. (quoted in Garmaise 2011)

Human Rights Watch argued, however, that testimony from detainees stated that guards had withheld treatment as a form of punishment, and they argued that financing health services was in effect a financial subsidy and a legitimation of forced labor. They publicly called donors to task for financing HIV services in these facilities. After a decade of advocacy on this and other issues, in 2012, advocates were ultimately successful in getting a human rights objective into the Global Fund’s corporate strategy: a commitment to ensure that the Fund “does not finance programs that infringe human rights,” language influenced by advocates who were concerned about the financing for services inside compulsory drug detention centers (The Global Fund 2011). As the incoming senior human rights advisor, I was tasked with determining how the Fund’s objective on human rights should be operationalized, a process described in earlier articles (Davis 2014, 2015). But how would this work be measured? We needed an indicator, a KPI on human rights to report on to the Board: one number to capture the complexity of human rights, HIV, tuberculosis, and malaria in more than 130 countries. Debates ranged among the Secretariat and the Board over various options, most of which relied on indices, data, or factors that were beyond the direct control of the Fund, and that did not relate closely to the human rights issues relevant to HIV, TB, and malaria. Some suggested that the challenges in setting a KPI meant that the Fund should not engage at all in the area of human rights because it was “too hard to measure.” So we focused in more closely on the Fund’s core business: on the programs it funds itself, and on an objective in the strategy to “ensure the Fund does not invest in programs that infringe human rights.” We 224

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drafted a KPI that would compare the percentage of human rights complaints in Global Fund–financed programs that had been previously identified through risk tools, with the number resolved using Secretariat processes. This was more of a lever than a sign. In order to report on this KPI to the Board, internal work would need to be done first. There would need to be a clear internal definition of what constituted a human rights complaint that the Fund had to address, how that complaint would be registered and tracked, and how it would be resolved. The definition would need to be integrated into risk assessment tools, so that Secretariat staff managing funding to a country discussed that potential human rights risk with the grant recipient, and made plans to address it. It was a KPI designed to spur needed institutional conversations and change, in line with the Board strategy. As a first step, a meeting of human rights experts convened to advise the Fund recommended that the Fund pass a policy clarifying its position on funding in compulsory drug detention centers. Intensive consultation with UN agencies, civil society, and representatives of people who use drugs followed. There were numerous challenges: 1. Where were the compulsory drug detention centers, and what was known about them? The only real data that existed at that time was reports produced by human rights organizations. In 2015 no UN agency was regularly visiting or capturing data on compulsory drug detention centers. (As discussed below, UNAIDS and UNODC later committed to regular data-gathering from countries where these facilities were located.) It was difficult even to say for sure how many facilities there were or how many people were detained in them. 2. How should international aid agencies engage to address humanitarian needs in closed contexts where there were systematic human rights abuses? What kinds of conditionality should or should not be attached? The 2012 joint UN statement on compulsory drug detention centers had called for health services to be provided, “pending closure of the centers,” but did not specify what conditions, if any, international funders should put on their funding (ILO et al. 2012). The UN Special Representative John Ruggie had drafted a set of human rights principles for businesses investing in countries where there were widespread rights violations, but it was difficult to apply these principles to the work of a health aid agency. No human rights standards for aid agencies existed.

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3. Who spoke for the people who use drugs – especially for those who had been, or were currently, detained in the centers? A growing number of countries in Asia had community-based organizations and networks that could represent people who use drugs, but in Asia the regional network was going through changes and had not recently met. While several respected organizations and individuals stepped forward to share with the Global Fund what Asian drug users had told them, their reports were contradictory: some said people who used drugs wanted HIV services to be funded inside the centers, and others said they wanted donors out. Consulting directly with national organizations of people who use drugs inside the authoritarian countries in question might expose those individuals to pressure from authorities who wanted funding to continue. 4. How would the Fund monitor inside the centers to ensure that services were reaching those who needed it?

While debates continued, this was a specific problem we had already contended with (and written about publicly) in managing an HIV grant in Viet Nam. In early 2013, shortly after I started work at the Global Fund, Viet Nam submitted an HIV funding request that included funding for HIV testing and treatment in compulsory drug detention centers. Recognizing the concerns about abuses in the centers, the Global Fund negotiated conditions with Viet Nam on the $85 million HIV grant. These stated that the Vietnamese government would work with the Global Fund to identify an international, independent non-governmental organization to monitor conditions in all drug treatment centers where the Global Fund supports interventions. . . . This additional safeguard will help to ensure that the services provided in the centers through Global Fund resources are provided on a voluntary basis, and that medical treatment is provided in accordance with international human rights standards. As of 1 January 1, 2014, all Global Fund support for services in these centers will be conditional on this monitoring. (Global Fund 2013b)

Human Rights Watch cautiously praised this as progress. But it turned out to be difficult to find an agency willing and capacitated to do the monitoring: an agency technically equipped and experienced in monitoring both human rights violations and health programs in closed settings that would be both independent, and acceptable to all parties (Garmaise 2013). We soon reached an impasse. In mid-2014, senior managers at the Fund made the difficult decision to stop funding services inside 226

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Vietnamese compulsory drug detention centers (Garmaise 2014). Even some who had formerly argued to stay in no longer believed the funding could be monitored appropriately. Instead, the funding was shifted to facilities based outside the centers to which detainees could be brought, and which could be visited and monitored. It was a compromise that made no one happy, but at least the services would be verifiably delivered to those who needed them. Reviewing this experience and the input of various UN agencies and human rights experts in July 2014, the standing committee appointed to lead this work on the Board passed a policy that restated the Fund’s “commitment to the closure of compulsory treatment programs and to avoid financing or supporting programs that infringe human rights.” Based on this, the decision states that the Global Fund shall not, as a general principle, finance any activities in or related to compulsory treatment programs or facilities where: a. Individuals are detained without due process, such as legal representation and judicial review; b. Medicines and treatment regimens are not scientifically sound or approved; or c. There is torture or cruel, inhuman or degrading treatment, as understood under international law. (The Global Fund 2014c)

The policy left room for funding medically sound services in cases where “sufficient measures can be implemented and maintained to oversee and verify the conditions and utilization of such financing.” In September 2015, UNAIDS, UNODC, and UNESCAP convened a consultation with nine East and Southeast Asian governments on compulsory drug detention centers. The participating governments “agreed to transition to voluntary community-based services including treatment, through implementing a roadmap” (UNAIDS 2015a). The roadmap included three “pillars of action”: establishing national task teams to develop transition plans, reviewing existing policies, and building the capacity of health sectors to provide community-based services as an alternative to compulsory treatment. However, the roadmap includes no specific time commitment. In its 2017–22 strategy, the Global Fund kept its objective to protecting and promoting human rights. To implement the objective, my 227

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successor, Ralf Jürgens, worked with UN partners to identify seven key programs to reduce human rights–related barriers to HIV, TB, and malaria services for inclusion in Global Fund financing (The Global Fund 2019). His Breaking Down Barriers initiative provides intensive support and additional funds to twenty countries in order to encourage them to scale up these programs. In the intervening years since the Global Fund decision not to fund in programs that use compulsory treatment, the world’s attention to compulsory drug detention centers has largely dissipated. With the end of their funding for the issue, Human Rights Watch no longer followed it, and aside from periodic press statements, there were no new reports. The Global Fund migrated to a new website, and the statement that it would not fund in compulsory treatment facilities vanished along the way. Advocacy in Malaysia generated hopeful signs of progress toward reform of compulsory drug detention centers, and there were indications that other countries were gradually losing faith in the compulsory approach, after thousands of former detainees continued to relapse. But overall, “it doesn’t seem like anything changed” since the commitment, said Judy Chang of the International Network of People who Use Drugs (INPUD), when I met with her on a visit to Geneva in May 2019. Bikas Gurung, Program and Communication Coordinator of the now revamped and revived Asia-Pacific Network of People who Use Drugs (ANPUD), agreed when we spoke by phone a few weeks afterward: “The process has halted, and there is no sign of completely transitioning out from compulsory detention.” He also noted the rise of new forms of private rehabilitation facilities that were linked to police and just as abusive as the public facilities. A UN official familiar with the work said that UN agencies had plans to circulate a questionnaire to gather data from governments in the near future, but that focus had shifted from pushing for compliance with the 2015 commitment to transition out of compulsory treatment, and was now rolling out tools in order to support work in partnership with countries on developing alternatives to compulsory treatment. At around the time that the Global Fund issued its decision on not investing in the centers, some other UN agencies had also developed internal agreements that they would no longer engage with the centers, according to the UN official. I asked the official whether the Global Fund policy had been helpful in pushing for change. The official felt frankly that it was 228

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complex: that the international community had placed restrictions on engagement in the hopes that doing so would push governments to change their policies on forced treatment, but that this approach had failed to have the hoped-for effect. They described frustration at being unable to engage with staff of the centers as a result of this decision, saying: “If we don’t train staff to understand that compulsory treatment is not OK, that there are evidence-based alternatives, then how do they understand that compulsory treatment is wrong? It’s not just high-level officials, it’s also people working inside the centers that need to know that information.” The official said they had heard of detainees accessing drugs inside the centers, and relapsing after release, because treatment is non-existent and the risks of overdose are high. In the end, the official said, Sometimes I don’t understand what that policy of not engaging or directly supporting these centers to improve the health services does. I see why from a human rights and philosophical, moral point of view. But in a practical sense, I don’t see that that has been effective. We are failing the people we are trying to help by not engaging.

I asked Bikas Gurung, who is a delegate on the Board, if he felt the Global Fund policy on not investing had made a difference in encouraging reforms in the region. He said he didn’t believe it had, but that his community still stood behind the policy. As for donors or UN agencies who would argue that funding in the facilities enables them to press governments for reform, he said, “It’s useless, actually. Even if the money that is allocated for HIV services gets to people inside detention, it’s just masking a tragedy. The government is going to use [the money] any way they want. . . . [It’s] just a waste of resources, and a way of endorsing also.” Judy Chang said, “INPUD’s position is the same. No one [in our network] thinks donors should continue funding compulsory drug detention centers.” THE LIMITS OF MONITORING

The compulsory drug detention center, with its own systems of surveillance and discipline, is a panopticon within the larger, growing panopticon of Chinese society. By engaging in different forms of monitoring, human rights organizations and development organizations attempt to 229

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engage in their own forms of surveillance and discipline; but in a closed system, these systems meet their limits. Sometimes, what they encounter is a Potemkin effect: a sunny display intended to deflect accountability and hide grimmer realities. Randeria (2003) similarly notes the sophisticated manipulation of optics by states that manage surveillance by international organizations. Wolfe (2010), who as a funder of research into compulsory drug detention centers has contributed to documentation of the abuses in them, warns of the “very real ethical and programmatic conundrum” faced by funders and program implementers in these settings: If people are starving in a concentration camp, do you go in and serve them food? How about medicines for those with HIV? If you do decide to go in, how do you talk and think about it to ensure that you’re not just working to perpetuate a system that is illegal, immoral, and in fact only impedes the public health goals you are supposed to be supporting? . . . [Y]ou want to avoid what philosopher Avishai Margolit calls the “rotten compromise” – working to reach common understanding with a system so fundamentally organized around humiliation or degradation that a collaboration is ethically unworkable. (Wolfe 2010)

In writing about the risks connected to the “rotten compromise” in a concentration camp, Wolfe indirectly invoked the specter of Terezin, a Nazi concentration camp visited by officials from the ICRC in 1944. (I had first learned about this from my mother, Ruth Davis. While she and my grandparents had escaped from Czechoslovakia to England in 1939, many relatives had been sent to Terezin and had not survived. As a Czech Jewish historian, she had worked for years to gather oral histories of others who had survived the camps.) To prepare for the ICRC visit to Terezin, the Nazis went to great lengths to create a “model Jewish town”: More deportations to Auschwitz were carried out in order to reduce the overcrowding in the ghetto. Fake stores, a coffee house, bank, school, kindergartens and the like were opened and flower gardens were planted throughout the ghetto. The commission arrived in the ghetto on June 23, 1944. Their meetings with prisoners were meticulously planned beforehand. After the visit the Nazis produced a propaganda film about the new life of the Jews under the auspices of the Third Reich. After finishing filming, most of the actors in the film, including almost all of the

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independent leadership and most of the children in the ghetto, were sent to the gas chambers of Auschwitz-Birkenau. (Yad Vashem, no date)

The ICRC has since expressed regret for this and other mistakes made in dealing with the Nazis and the genocide (ICRC 2014). This incident, among others, demonstrated to international organizations how the very act of monitoring abusive contexts can, in some cases, be manipulated by abusers to legitimize their power. Since then, the field of human rights monitoring has evolved and professionalized significantly; international experts have developed concrete and practical approaches to monitoring and assisting detainees, noting that regular transparent and independent monitoring is “one of the best safeguards against torture and ill-treatment” (Association for the Prevention of Torture 2004, 15). But in China, Viet Nam, and other countries, organizations that try to monitor such facilities or speak for prisoners are in turn monitored and restricted; a sweeping crackdown in China has significantly closed civic space. While a prison or detention center can enforce punishments on those it sees breaking the rules, and an authoritarian state can as well, the threat of human rights monitoring does not always have the hopedfor disciplinary effect, especially as those monitored become more adept at creating Potemkin villages, and managing optics. In fact, Foucault’s own theoretical work was informed by his personal experience as a cofounder of group that worked with prisoners to monitor abuses in detention (Hoffman 2012; Welch 2011). In writing about Foucault’s efforts to support monitoring by prisoners, Welch calls this counterveillance, “turning the prison inside out” to expose abuses (Welch 2011). If Discipline and Punish contained good insights, Foucault said afterward, they came from his experience with this group (Hoffman 2012, 23). However, he found to his despair that real improvements in prison conditions were hard to achieve. In 2002, HRW’s approach to counterveillance was to document violations, expose them in reports, and use the reports and resulting media coverage to advocate for an end to the violations. This was what colleagues called “shining a light” on abuses, “naming and shaming” abusers. A veteran researcher assigned to train me in 2002, seeing how difficult it was to gather evidence in China, and hearing from former detainees about the abusive conditions, remembered how the researcher

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had once talked their way into prisons in another country, and suggested I try to do the same. When interviewing Chinese victims of rights violations, I had taken a number of steps to inform them of potential risks, protect their anonymity, and mitigate the risks, in consultation with research and legal experts at HRW’s headquarters. Going into a drug detention center was another story. The facility was open to the public. I booked a visitor’s tour but did not disclose that I worked for HRW, as I believed doing so would lead to retaliation against Chinese colleagues. Meeting the expat photographer through a mutual friend in Kunming, I asked if he wanted to come along to take photos for HRW, and he readily agreed. I also wanted him along in case it turned out that I could talk my way into Changpo, but not out again. From 2007 to 2011, Human Rights Watch went on to conduct further investigations of abuses in compulsory drug detention centers in China, Cambodia, Viet Nam, and the Lao People’s Democratic Republic, as did other agencies such as Open Society Foundations (2011). In an article discussing the ethical issues with this work, Amon and colleagues argued that the work was not research in the biomedical sense, and that because Chinese ethical review committees are not independent, seeking approval of research into human rights abuses would lead to risks for both research participants and researchers (Amon et al. 2012). In publishing this work, the authors explained: The research approach, and ethical and human participant protections associated with the research, were reviewed and approved prior to conducting the research by legal, programmatic, and policy staff at Human Rights Watch. We did not seek ethical approval from Chinese authorities as we felt that this would have endangered, not protected, the safety of the participants. (Cohen and Amon 2008)

This contributed to a larger debate about the ethics of using these facilities as medical research sites. Pearshouse and Amon argued: Research in drug detention centres that does not reflect upon the conditions in the centre or the legal status of detainees does tangible harm to detainees: it disguises recognition of these centres as settings of gross human rights abuses, and may be used by governments to claim these centres as legitimate institutions. (Pearshouse and Amon 2012) 232

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Yet counterveillance of this kind, or reversing the optics, is not necessarily synonymous with inverting power relations. While some Foucault scholars (Joyce 2002) have noted that neoliberalism and mass media produce multiple vectors of surveillance, a “synopticon” or “omniopticon” with people increasingly watching each other, Caluya cautions that the panopticon is not only a question of gaze: “Although Foucault writes and speaks incessantly about visibility and the gaze, this should not be taken as an analysis of the gaze, but an analysis of power through the use of the gaze. In short, the gaze is only important here insofar as it is a concrete mechanism through which power is exercised” (2010, 625). Any form of monitoring can create Potemkins: showplaces aimed at hiding grim truths. Obviously, it is not only the possibility of being watched that compels detainees in the panopticon to obey; it is the fear of being punished if they are caught breaking the rules. Human rights researchers who “name and shame” have no such power over abusive officials. If the officials who are caught violating human rights standards don’t feel ashamed, like the warden showing off Changpo, then the influence of monitoring is minimal. Li quotes Foucault as saying that power is a relation of “reciprocal incitation and struggle” involving a range of actors (2007, 276). In global governance, including in relationships between donors, states, and civil society, monitoring and counterveillance have become tools of power and negotiation, generating varying forms of knowledge that are used to assert competing political influence. Human rights organizations and aid agencies monitor and threaten states with exposure. This moral regime relies on visibility to discipline behavior, as well as on elaborate systems of indicators, monitoring and reporting data. Deconstruction can be powerful; advocacy, monitoring, accountability, and community engagement can be powerful. Key populations, human rights groups, and their allies have used these and other tools to advance human rights norms, incrementally, where they can. But these approaches have limits, and they will not work everywhere. It has taken years to process the different forms of violence and invisibility during that visit to Changpo in 2002. Seventeen years later, my memories are fragments: a blue sky, an unnameable look in the eyes of the detainees, the warden’s mirthless laugh, the sound of the camera shutter clicking, and the reflecting pools of all that water on the ground. 233

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In September 2019, the UN High-Level Meeting on Universal Health Coverage (UHC) met at the United Nations in New York City to pass new ambitious global goals, to encourage countries to “move together to build a healthier world” (New 2019). Once again, the sweeping health commitments were “pretty fuzzy,” said critics; while the political declaration approved by the General Assembly articulated the steps needed to reach Universal Health Coverage, “the direct policy and financial commitments needed to meaningfully address those components are lacking”; as needed resources for global health are locked in the “golden straitjacket” of a chaotic free-market economy (Blaser and Bales 2019; Lancet Global Health 2019). And worse, there were no indicators at all this time: Rico Gustav and GNP+ warned that the lack of any clear accountability framework would result in “minimum progress and maximum self-congratulatory celebrations” by states (Gustav 2019). By day two of the and wan pieties from heads of state in the General Assembly, Jamila Headley, managing director of HealthGap, had had enough. Headley, a longtime AIDS activist and PhD in public health, posted a call on Facebook for a protest, saying she was tired of “the hollow promises and the absence of concrete new funding commitments or ambitious health service delivery targets” (Headley 2019). To friends, she commented that she had just landed in New York after six weeks of travel for HealthGap in South Africa, where she had witnessed firsthand “the reality of struggling health care systems, health worker shortages, stock outs of essential medicines and other gross injustices”; she felt it was time to march and “fight for health justice for all” (Headley 2019a). 234

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That afternoon, staff and volunteers with HealthGap, Partners in Health, PIH Engage, and Student Global AIDS Campaign staged their UN walkout, taking to the streets to chant “Healthcare is a human right!” But the videos, which Headley posted online later, showed that the vocal protest was a small one. Granted, it had been a spontaneous protest, so it was not surprising to have only a few dozen AIDS activists marching. But when you thought about it, Universal Health Coverage should have broad appeal and urgency. Why were there not thousands of people in the streets in front of the UN? Where were the TB activists, who had recently begun mobilizing their own organizations, and had started to identify key populations vulnerable to TB? The malaria activists? The organizations working on noncommunicable diseases such as cancer and diabetes, or the groups fighting for health rights for women, who had seen language about their rights negotiated out of the political declaration? Indigenous peoples, persons with disabilities? For that matter, the streets of New York are filled with thousands of people who lack health coverage, many of them living with HIV. Health had been a hotly debated issue in the Democratic Party election debates just days earlier. Where was everyone? The protest highlighted the larger global problem of lack of resources for health, and it also showed the old paradigm of AIDS activism at a turning point. There are some lessons to take away from the experience of the global HIV response, and one of those is that resources follow strong, community-led transnational advocacy. As global health agencies and donors shift their focus away from single-disease responses and toward the broader umbrella of universal health coverage, the advocacy movement that has achieved so much in building and operating under the old framework is now beginning to wrestle with finding new ways to reach out to, speak to, partner with, and mobilize broader and more diverse constituencies. They will need to start a snowball effect, in which contacts mobilize other contacts and bring them into the network. Where to begin this renewal? This movement will need data, gathered from the ground up. BIG PLANS AND ARTIFICIAL SCARCITY: THE DRIVE FOR DATA

This book has argued that the Fast-Track approach used ambitious goals developed with models that were too simple to capture the complexity of the context that drives HIV transmission. When what Easterly (2006) 235

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called “Big Plans” encountered limited resources, the pressure created by this artificial scarcity was shifted down to aid agencies, which have been forced to make absurd decisions in order to deliver on those promised goals, based on cost-effectiveness: choosing between the cost of saving a life in rural Kenya versus the cost of saving a life in Venezuela or Russia. In the absence of a clear, human rights and ethics-based approach, they fell back on the model of the market. Simplified versions of private-sector tools were made to fit the purpose: investment cases, business strategies, key performance indicators, and mapping and tracking individuals down to the site level. The approach was rational, but the absence of nuanced economic data to assess fiscal space, and the lack of data on key populations meant that those who had historically been losers would sometimes continue to lose. The Fast-Track approach did achieve important things: thanks to a massive collective global effort, AIDS-related deaths did sharply decline. Lives really were saved, especially in high-prevalence countries. But the world is not on track to reaching the end of AIDS, and because they were de-prioritized and invisibilized, criminalized key populations in middle-income countries are now facing rising infections. This is in part because adding in human rights language as decoration on top of data-driven systems of prioritization, without integrating rights principles throughout the tools and systems, leaves human rights considerations an afterthought and favors commoditization of health financing over structural change. To create a strategy requires making difficult decisions: choosing to make some things visible and others not. The uncounted, the phenomena and people that are epistemologically excluded, discursively help to construct the priorities, just as negative space in a picture helps to shape the things that are depicted. The people who hide to avoid arrest, violence, and stigma are among those often left uncounted, their population sizes and their needs underestimated in ways that feed the denial that they exist at all. Absence of evidence is taken as evidence of absence, creating a vicious cycle of invisibility, concentric circles that swallow up rhetorical promises that “no one will be left behind.” Strategies use abstractions, such as objectives and indicators, to coordinate and focus efforts toward clear outcomes. Signs like the indicators discussed here are inherently partial abstractions. But as Butler (1993) argues, something must be excluded from economies of discursive intelligibility in order for political economies to function as self-sustaining systems. To select an indicator means to exclude and 236

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render something, someone uncounted. To displace the top-down power dynamics that shape priorities requires a ground-up approach that empowers communities to gather their own data through participatory action approaches, enabling them to inform national and global targets based on local realities, and to have a say in decisions that shape their lives. This book has argued that while numbers may be presented as neutral and fixed systems of representation, they are embedded in histories of expression that are constantly being remade, and they offer numerous entry points for productive contest. As Bakhtin says, “I live in a world of others’ words” (1981, 143). Discourse involves multiple voices, he wrote, incorporating ideas and references beyond those of the speaker; changes in context can give those forms of signification diverse and multiple meanings that the speaker cannot control. When civil society and community representatives are in the conversation, it becomes dialogic, incorporating multiple epistemologies and forms of evidence. Brown, drawing on Balibar, says that equality is “imposed by the revolt of the excluded” in a process that has no end; the demos is made up of “those unqualified to rule, ‘the uncounted,’” who come forward to claim their place at the table (Brown 2015, 19). Having people living with HIV, sex workers, transgender people, men who have sex with men, and people who use drugs sitting at the decision-making table next to health ministers and other leading figures does not overturn power inequalities, but it destabilizes them slightly, in ways that may lead to better decisions. Quantification makes indicators and the phenomena they represent visible as “epistemic objects,” for instance through data visualization, but these do not have to be totalizing. By bringing diverse voices into the room, the meanings of those objects can be contested and revised (Didier 2007; Bartl, Papilloud, and Terracher-Lipinski 2019). The act of presenting data to a group can open a debate about what is and is not captured by that data, potentially enabling someone in the room to bring the excluded politics, the “elephant in the room,” back into the conversation. (In fact, in a 2015 meeting of the UNAIDS Programme Coordinating Board, the NGO Delegation actually brought in small stuffed elephants and put one on the table of each board representative, to represent the “elephant in the room” they felt was not being discussed at that meeting: lack of funding for community-led responses to HIV.) The problem then becomes who is in the room and how power is managed and distributed with in it. Are there individuals present who 237

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Figure 10.1 Civil society “elephant in the room,” UNAIDS Programme Coordinating Board, 2015. Credit: Malu S. Marin

legitimately represent the communities whose lives will be affected by their decisions? Are those representatives empowered to ask difficult questions? How are messy realities that are difficult to quantify either excluded from, or factored into, decision-making tools? How are values of cost-effectiveness calculated and weighted against other values, such as the right to health for historically discriminated against populations? And where there is no official data due to official denialism, can other forms of evidence be introduced, or a reverse burden of proof? These are problems that the HIV sector has wrestled with, creating numerous paradigms of community engagement that should be considered for other areas of global health governance as well. Kerlin Charles, executive director of GrenCHAP in Grenada, said that she would encourage other community-based organizations that might be offered the opportunity to do their own key population size estimates to seize that opportunity “and run with it.” She also said: I would encourage them to do a lot of mobilization prior to the start of the population size estimate, to go out there and really mobilize the

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community, so they would answer those questions. If we had had more time, we would have had more persons. I would also say to use persons from the community [as indigenous field workers], that’s how you get persons to come out.

She remembered how, toward the end of the study, key populations had begun to turn up in larger numbers each day: “The snowballing was amazing,” she marveled. Repeatedly in the course of writing this book, I saw community organizations that had rich troves of excellent data; national health officials operating with data filled with gaps; and at the global level, targets set based on modeled estimates. In one town, for example, I met with an NGO that said they routinely “bump up against” health officials at the national level, because their NGO exceeded national targets. When asked why they were able to achieve that, they said, “We’re reaching the people who are hard to reach,” including mobile sex workers, men who have sex with men, and transgender people who move frequently to different parts of the country to seek income-generating opportunities wherever the tourist trade is peaking: “We use a relationship model” built on trust. One manager pulled out her cell phone to demonstrate that she had real names and numbers of her clients; they gave them to her because they wanted certificates from vocational training courses using their legal names. “Our clients are not targets,” she said. As the world shifts toward UHC, there will be a need for new forms of mobilization to demand resources and accountability for public promises. As UHC will need better data, I suggest drawing on the example of the CVC study to expand and try other forms of community mobilization that incorporate data-gathering through participatory action research, bringing together diverse grassroots constituencies to document and understand local needs, and to establish trust with networks they need to serve. Because of the problems created by criminalization, communities at risk of HIV have hard-won experience in doing this kind of work among stigmatized populations, experience that could be used with other populations as part of broader mobilization to gather community-led data in global health – for instance, with migrants and refugees (many of whom are also key populations, or living with HIV) who are vulnerable to numerous health risks, frequently de-prioritized by national health programs, and who need to understand and exercise their rights to have a say in what counts and what gets counted. 239

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Individuals at risk of every kind of health issue have a right to be educated and empowered to make decisions; as Hummel and colleagues argue, individuals cease to be data sovereigns if they are unable to articulate or enforce claims to power and/or if they are unaware of the flow of their personal information, the nature of the data that is being generated about their lives, who can access it, the ways in which it is processed, and the mechanisms in which such processing feeds back into their decision making. In the worst case, potentially autonomous and reflective subjects are degraded to mere objects of data flows. (Hummel et al. 2018)

But grassroots mobilization in data-gathering has the potential to both change that dynamic and to generate richer data, using that data to hold other agencies accountable as well. Ambassador Birx said, when we spoke, “Data is only valuable if lets you see down to the individual that you’re serving. . . . I like data because it allows me to see through my own misperceptions, down to the reality of what people are facing on the ground, and the decisions that they have to make.” Richer data can reveal hidden realities that international organizations may need; at the same time, individuals can also use that same data to make institutions visible: their strengths and gaps, their rationales, assumptions, and pressures, what the institution thinks counts, what it may sometimes miss. For example, we can use data to show that while China has officially ended re-education through labor and committed to moving toward a system of voluntary community-based drug treatment, the numbers of those in detention centers remain in the hundreds of thousands. We can use government-reported data to show that governments reporting unprecedented success in HIV testing coverage of men who have sex with men may be basing this report on implausible size estimates. And we can use data to demand accountability from national and international organizations that provide health services for mitigating the risks related to their own data-gathering, and demand transparency about how that data is gathered and processed, where it is stored, and how, or whether, it will be used. * As of 2019, the CVC size estimation study had not been published yet. “There was some pushback,” said John Waters when we spoke in July. 240

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“Pressure from countries on the Organization of Eastern Caribbean States.” The data showing the sizes of populations of sex workers, men who have sex with men, and transgender people was perhaps too explosive for publication in some countries – as was the data showing other difficult realities, such as gender-based violence and child abuse. Those who had done the research were frustrated that lack of published data was undermining the fight for prioritization; as Dr. Martin put it in our last interview, “Publishing it would enable conversations that need to take place” to get resources allocated to HIV prevention programs in Grenada. Meanwhile, time was moving on: before long, the region would need to start the whole process of data-gathering again. UNAIDS says size estimates are only valid for three years. Nonetheless, the size estimates did make it into the regional funding request to the Global Fund. In 2018 the OECS Regional Coordinating Mechanism submitted a request for a continuation of the Global Fund HIV/TB Elimination grant QRBC-1037 for an additional three years (Organization of Eastern Caribbean States [OECS] Regional Coordinating Mechanism [RCM] 2019), for an amount of $3.5 million, of which more than $2 million was allocated to HIV and $1.5 million to TB. The key population size estimate numbers were presented as incomplete drafts yet to be finalized, and were appended in an annex as drafts (OECS RCM 2019, 4). I spoke with John about the funding request. He said that there had been long negotiations to produce it, and that one of the things that we felt was critical was setting up regular outreach programs with key populations groups, making sure those are actually getting to new subgroups identified in the study. That was a big piece. Because [the OECS] had had so many problems reporting to the Global Fund on the indicators on key populations under the old grant, it made it an easier sell.

The funding request does note problems with “poor reporting on services for key populations due to the non-disclosure of status, poor linkages and access to services due to stigma and discrimination” and proposes to address this by integrating civil society organizations into provision of services and use of rapid tests (OECS RCM 2019, 11–13). Some interventions to strengthen a central community role were included: using the indigenous field workers from the population size estimates to improve linkages to testing and care for men who have sex 241

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with men and sex workers; improving access to justice for people living with HIV, MSM, sex workers, and transgender people; documenting good practices in civil society-led service delivery to build capacity among other civil society groups; training key population groups in HIV and STI testing; strengthening data collection for key populations; establishing a code of conduct for health care workers; and more (OECS RCM 2018, 14). The collaborative committees formed in each country with civil society and health ministries would be continued, to ensure collaboration in outreach (OECS RCM 2018, 17). However, getting funding set aside for work to address gender-based violence against sex workers and men who have sex with men had been a tougher sell, John said: “It was a stark reminder that, wow, these issues remain very challenging in the Caribbean.” While he was pleased that many of the interventions he had recommended were included in the funding request, that was no guarantee that the funds would actually be spent on those programs. While the small island economy exception in the Eligibility Policy had protected eligibility for the Eastern Caribbean, the Global Fund’s 2019–22 grant allocation was nearly one-third less than the previous allocation had been (OECS RCM 2018, 19). In previous Global Fund grants, he recalled, there had been numerous cuts during implementation. As governments began to feel the pressure to scale up testing and treatment to reach 90-90-90, funds had been taken away from other interventions and funneled into procurement of commodities. This time, the pressures would be even greater. Was Grenada’s government able to fill the gaps, if needed? The national budget did not seem to offer much flexibility. Out of estimated expenditures in 2018 of ED$778.4 million, just EC$5.7 million went to health, most of this from external aid (Government of Grenada 2019, viii). The recurrent expenditures for the Ministry of Health were just EC$73 million, while the cost of public debt was EC$371 million. With this heavy burden of debt, like many other countries in the Caribbean, the Grenadian government had limited fiscal space for health. John was not counting on the Caribbean states being able to fill civil society funding gaps. He was already experimenting with various side projects in tourism and agriculture for young key populations: “Personally, one of the reasons why finding ways to generate income has been a big thing for me, is because I don’t see the transition thing happening well. [Donors] expect governments to fund NGOs to do outreach and provide services, but I just don’t see that happening.” 242

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While we were analyzing the budgets, I noticed that Grenada’s national budget included an allocation to rebuild the crumbling Ministry of Health, which was certainly needed; the country’s national buildings have been decimated repeatedly by hurricanes, and the health ministry has been just one on a long list of repairs and reconstruction. But I was surprised to see that the funder for Grenada’s Ministry of Health building, with a grant of EC$27 million (about US$9.9 million), was the Bolivarian Republic of Venezuela (Government of Grenada 2019, x). The reasons for the promised aid are not stated in the budget; perhaps they are linked with the Venezuelan government’s ongoing efforts to shore up support from its neighbors against the threat of a potential US invasion. Meanwhile, Venezuela’s health needs grew more desperately urgent. While the Global Fund approved a $5 million donation to Venezuela in 2018, months later, most of the treatment had not yet reached those who needed it. In May 2019 the Venezuelan network of people living with HIV and other civil society organizations issued a public statement disputing a UN report that treatment had been provided to fifty thousand people inside the country. Calling this “incoherent with reality,” they reported that only 3,659 people living with HIV had received the treatment donated by the Global Fund, while much of the medicines sat in warehouses (RVG+ and the Coalition of NGOs of the Interior of the Country [COVIP] 2019). News reports stated this was because the Venezuelan government lacked trucks to distribute the medicines; and then some whistleblowers were detained by authorities (Lavers 2019, 2019a). With refugees fleeing to other countries, the national government finally permitted the Red Cross to provide some humanitarian aid. By 2019, Venezuela’s rapidly resurgent malaria epidemic finally made the country officially eligible under the Global Fund Eligibility Policy (Garmaise 2019; Kurmanaev and Herrero 2019). While the hardworking officials at Grenada’s health ministry certainly needed a new building, given their own urgent needs, Venezuelan health rights advocates also have the right to know that particular data point, and about the funds promised across the Caribbean Sea. * This book began with a search for answers about data, but it turned out to be about human beings: how they communicate or fail to listen; their moments of courage in the face of suffering by others; their pig-headed 243

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blind spots and fierce advocacy; their bodies and how those intrude on all the best-designed models; about power, autonomy, and trust. My last interview with Kerlin and Mr. B of GrenCHAP touched on these issues. We met at a cafe by the marina in St. George’s Bay, on a sunny, clear day in January 2019. The pristine blue and white yachts bobbed in the water as soca wailed from minivans veering down the main road nearby. It was just a quick chat; they could not stay for long. GrenCHAP had a busy week ahead, between meetings, grant reports, an anniversary dinner party, an art show. Over the three years of this study, the organization, now a leader in the national HIV response, had grown rapidly. Kerlin said that GrenCHAP was now a certified HIV rapid testing site, thanks to their partnership with Dr. Martin: “On World AIDS Day, we had only two persons on site [doing testing], but we had 104 men come in to get tested. They were below 25 [years old], all these young men, and it was the first time they got tested; and this was because they were getting the results right there and then.” She said she was trying to get these men, and others they had interviewed in the CVC study, into GrenCHAP programs: “We’re not seeing all of them, but we’re seeing a large number of them; we have increased the amount of persons we reach. We’re seeing new faces, engaging in movie nights. It’s good that we did a population size estimate and have a safe space for persons to engage.” I attended GrenCHAP’s staff appreciation dinner, a candlelit buffet in the office where the walls were lined with good wishes written on Post-It notes. I met new staff and young volunteer outreach workers who were energetic and fierce: one nineteen-year-old woman, a new GrenCHAP volunteer, sat down across from me at dinner and told me peremptorily to use this book to “let the world know that lesbians exist.” Another program officer shared his excitement that GrenCHAP had been selected by USAID for core support and capacity-building; he was looking forward to getting the financial training he needed to subgrant to other, smaller start-up groups in Grenada. When Kerlin and Mr. B reviewed all this progress at the marina, they had just learned that a grant application for a six-month project had been funded with US$10,000 they had written the proposal using data from the CVC study. In our conversation, Ambassador Birx worried about the long-term sustainability of civil society organizations, given the withdrawal of many European donors: “If anything worries me in the epidemic, it’s [that]. We really do need a long-term solution around

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the community voices related to HIV/AIDS. Until we find a cure, it’s not like HIV is going away.” Compared with the kinds of numbers the Global Fund and PEPFAR worked with daily, a grant of ten thousand was tiny. But signs can change their meanings in different contexts, and ten thousand meant something different in St. George’s than it did in Geneva. To GrenCHAP, it was a game-changer. “I hope we get more opportunities where we can use the data, get the funding, and really touch the lives that we need to get to,” Mr. B said. To fund a group like GrenCHAP should not be an expensive proposition for global health agencies and governments: it really comes down to what you prioritize, a problem of political will. I congratulated Kerlin and Mr. B on the grant. I had had doubts about whether I should publish the size estimates and other data in Chapter 8: would it cause difficulties? I had written to a few Grenadian contacts to ask their views. Some replied and said that publishing the data would open up some conversations that they were ready to have. One wrote back, reflectively, that it could help “elucidate the need to give everyone in Grenada their right to human dignity.” Sitting by the marina, I asked whether the size estimates, if they were ever published, would lead to changes for men who have sex with men in Grenada. Mr. B, who usually has an upbeat outlook, took a moment to reflect. His reply was not overly ambitious or optimistic. He said, “It is possible. My personal belief is that our generation needs to lay the groundwork and put it out there, so that younger persons coming up now become a little more accepting. When they get to our stage, change might be achieved. The fight continues.”

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REFLECTION QUESTIONS

These are suggested reflection questions for participants in health governance meetings about indicators, models, and data used to make decisions. INDICATORS AND TARGETS

• Were these indicators selected through a process that was democratic, transparent, and included elected representatives of my government and of my community? • What is the indicator aiming to measure and why? • Are these indicators signs that aim to communicate something to a public audience? • Are these indicators levers that apply pressure to create a change in behavior or policies? If so, is that change being adequately supported and funded? • Is the indicator going to produce the kind of data we need to make informed decisions? • Does the indicator require data that is disaggregated by age and gender? If not, why not? • Do the indicators relate to an index which rank-orders things as better or worse that cannot reasonably be rank-ordered, because they are different from one another? • If the indicator is a coverage (or percentage) indicator, does the baseline estimate of the population exist, and is that baseline plausible? • What do these indicators leave out, and why? • Does the data to report against this indicator exist? If not, where will it come from? 246

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• What are the consequences if the targets are not met? • Are the targets realistic for our context? Are they too ambitious, the right level of ambition, or not ambitious enough? • Do the targets require laws or practices to change in order to be achievable? If so, is this work being funded and supported? MODELS

• What are the assumptions behind the models? • Are the models being used to predict a future scenario? If so, what is the story they tell? Is it a story that serves some specific political or economic interest? • Are there difficult realities that the model is failing to address? If so, how could they be factored in the model? • Is anyone excluded from the model who should be reflected in it? DATA

• How was this data gathered? • Who gathered the data? Was there community involvement in the research design, implementation and data analysis? If not, why not? • Who funded the data-gathering, and why? • Was the data gathered using protocols that clearly respect the rights, and identify and manage any risks, for vulnerable communities? • Who owns the data? • Is the absence of evidence of some difficult and hard-to-acknowledge reality or population being used as evidence that those facts or people do not exist? • Is it possible to use other forms of evidence, such as reports from civil society? • Is it possible to use a reverse burden of proof, as ICRC does for conflict-related sexual violence (i.e., assume that the problem or group exists and program accordingly, unless someone can produce evidence to the contrary)?

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ACKNOWLEDGMENTS

Many individuals and organizations generously shared their time and support. I am especially grateful to all those who agreed to be interviewed. A heartfelt thank you to John Waters and Caribbean Vulnerable Communities; Dr. Francis Martin and the Grenada Ministry of Health; Henna Budhwani and Ria Hearld; GrenCHAP and the Grenada Planned Parenthood Foundation; to many individuals, named and anonymous; and to all the research team that allowed me to join some of their journey. In Kenya, I am indebted to Allan Maleche, Tabitha Saoyo Griffith, and the inspiring team at KELIN; to Patricia Asero and Maurine Murenga, and the members of the Key Populations Consortium: asante sana. In Geneva, Peter Sands took time out from his vacation to share insights into business and global health tools. Peter Ghys at UNAIDS, and Rachel Baggaley and Andy Seale at WHO, also made time to speak during busy work weeks. Ambassador Deborah Birx was gracious and thoughtful in our interview, and I continue to appreciate her forthright rights-based advocacy at global health meetings. Keith Sabin patiently explained how UNAIDS works with countries to gather and attempt to verify data. Rico Gustav was a reliable source of wisdom. Numberless colleagues at the Global Fund, PEPFAR and other bilateral and UN agencies spoke off the record to share their expertise. Several experts read an early draft of some or all of the book and shared thoughtful edits, including Joe Amon, Melissa Ditmore, Nigel Mathlin, Mike Podmore, Keith Sabin, and Ryan Whitacre. Emile Dirks and the China Drug, Crime and Detention Database helped to find and think through data from Chinese sources. I am grateful to three anonymous reviewers for Cambridge University Press, as well as reviewers of articles submitted to the Journal of the International AIDS Society and Global Health Governance. Conversations with those above and the following were helpful at key moments, though they bear no responsibility for the results: Eliot Albers, George Ayala, James Bair, Stefan Baral, Scott Catey, Judy Chang, 248

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Alberto Colorado, Joanne Csete, Hazel Da Breo, Heather Doyle, Chris Dolan, Kene Esom, William C. Goedel, Misha Golichenko, Carolyn Gomes, Nicole Gorman, Matt Greenall, Jonathan Gunthorp, Jamila Headley, Rebecca Henderson, Julian Hows, Alexandrina Iovita, Hristijan Jankuloski, Matt Kavanagh, Michel Kazatchkine, Andrew Kennedy, Stephen Leonelli, Lynette Mabote, Sally Engle Merry, Suerie Moon, Berry Didier Nibogora, Vinh-Kim Nguyen, Sara Paparini, PaulGilbert, David Ruiz, Jorge Saavedra, Miriam Sabin, Anya Sarang, Meg Satterthwaite, Shen Tingting, Annie Sparrow, Laurel Sprague, Dereck Springer, Rebekah Thomas, Mary Ann Torres, Melania Trejo Mendes, Yesim Tozan, Sridhar Venkatapuram, Inga Winkler, and Elijah Zarwan. I also learned from the teams at African Men for Sexual Health and Rights (AMSHeR), Asia Catalyst, Avenir Health, and the Robert Carr Fund for Civil Society Networks. Three academic centers gave me a desk as a visiting scholar: the Center for Human Rights and Global Justice at New York University from 2015–18; and at the Graduate Institute, both the Anthropology and Sociology Department and the Global Health Centre in 2019. Thank you to Emmanuelle and Robin Lyon and to L’Essieu du Batut for ongoing support, including a writing residency. I also benefited from feedback at the American Anthropological Association, the Association for Social Anthropology, the Critical Legal Conference, the Governing by Numbers workshop at Martin-Luther-Universität, Halle-Wittenberg, the Democratizing Data meeting at NYU, and the Global Health Centre at the Graduate Institute. At Cambridge, I am grateful to my editor Jackie Grant; to series editors Mark Fathi Massoud and Rachel E. Stern; and to Laura Blake and the team who helped to copyedit, design, market and publish the book. My global family provided intellectual and actual nourishment. Helen Sunderland and Rod Hancox provided a home away from home in London; Sam Davis and Yael Falicov did the same in Oakland. My parents taught me to value social justice and good writing. Thank you to Dan Hancox for writerly advice; and to Allan, Mike, Colleen Daniels, Jan Brown, Karyn Kaplan, and Loretta Wong for listening and encouragement. One spark for this book came from Andrew Hunter, whom I first met while working in China. Andrew was an Australian sex worker openly living with HIV, devoted to his partner Dale, and a voracious reader and thinker. As head of the Asia-Pacific Network of Sex Workers and a member of the Communities Delegation to the Global Fund Board, 249

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he was a steadfast source of support, often via sarcastic and hilarious text messages. Just one of his many obsessions was coercive data-gathering by states about sex workers. “If you don’t protect the human rights of sex workers,” he used to say, “every other dollar you invest in HIV prevention is wasted.” After a long year of fighting for those rights, his heart gave out in December 2013. He was forty-seven. While the HIV movement has lost many leaders, collectively they are a force to reckon with. Thank you to the activist community online and in person for sharing fears and frustrations, as well as moments of hope, laughter, and measurable progress.

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295

INDEX

“end of AIDS,” 7–9, 10, 20, 65, 83, 130, 143, 192 and drive for data, 195 and mathematical models, 115–31 90-90-90 targets, viii, 8–10 and human rights goals, 131 and masking of failures, 50 and pressure to test, 173, 196 changing list of countries, 10 PEPFAR focus countries, 16 role of community groups, 45 ACT-Up, 21, 48 Adams, Vincanne, 24, 39, 100 African Charter on Human and People’s Rights, 110 AIDS AIDS-related deaths, declines in, 130, 236 AIDS-related deaths, increases in, 143 AIDS-related deaths, predictions of, 103 AIDS Healthcare Foundation, 3, 153 AIDS Law Project, 176, 193, 194 Algeria, HIV response, 49, 147 Amon, Joe, 47, 62, 219, 220, 232, 248 anti-politics machine, 43, 127–28 artificial intelligence, 54, 57, 223 Asero, Patricia, 175, 177–79, 193, 194, 197, 248 photograph of, 178 Asia Catalyst, 40, 146, 249 assisted partner notification services (aPNS), viii, 173–97 definition of, 174 PEPFAR position, 184, 188, 195 WHO guidelines on, 188–91 audit culture, 4, 217 Baggaley, Rachel, 191–92, 197, 248 Bakhtin, M.M., 237 Belarus, HIV response, 107, 109 biometrics, 45, 46 definition, 54 resistance in Kenya, 51–61 use by Chinese state, 222

296

Birx, Amb. Deborah, 16, 36, 59, 61, 83, 85, 179, 240, 244, 248 and PEPFAR drive for data, 181–84 bio, 180–81 Botswana, 10, 35, 158 Brazil, 47, 110 Brown, Wendy, 99, 101, 113, 237 Budhwani, Henna, 75, 77, 78, 81, 132, 134, 135, 136, 138, 248 Butler, Judith, 39, 236 Caribbean HIV/AIDS Alliance (CHAA), 78, 82–83 Caribbean Vulnerable Communities (CVC), 42, 50, 63, 67, 68, 73, 74, 77, 79, 80, 89, 131, 132, 198, 199, 202, 205, 206, 210–14 Figure, research timeline, 200 Center for Disease Control, 55, 60, 184 Chang, Judy, 228, 229 Charles, Bennet, 83, 84 Charles, Kerlin, 87, 88, 89, 90, 135, 136, 210, 238–39, 244 China and civil society, 40, 146, 231 and compulsory drug detention centers, 215–17, 218–23 and human rights, 215–17, 218–23 and human rights research methods, 231–32 and the Global Fund, 146, 154 coded messages, 46, 80, 86, 202 colonialism, 3, 87, 206 compulsory drug detention centers, 215–33 cost-effectiveness, 14, 19, 31, 83, 93, 115, 119, 130, 141, 142, 165, 171, 238 and aid to small countries, 160 and critical enablers, 125, 131 and ethics, 170, 236 and gender, 124–25 and human rights, 94–114 Country Coordinating Mechanism (CCM), 28–28, 213 criminalization, 105, 116, 129 and aid eligibility, 160 and indirect discrimination, 101

INDEX

and the data paradox, 46–50 ignored in models, 123, 124, 128, 130 of key populations, 18, 19, 60, 66, 106, 239 of key populations in Caribbean, 72 of key populations in Kenya, 53, 56 Da Breo, Hazel, 208, 210, 249 data paradox, 47, 90, 105, 127, 160, 165, 185 gender-based violence, 196 decriminalization definition, 19 Derrida, Jacques, 127 development continuum, 163, 164 Dias, Lorna, 57, 60 Dirks, Emile, 222, 223, 248 discrimination, 53, 105, 112, 116, 151, 164, 241 addressed in human rights standards, 111 against key populations, 18, 47, 56, 72, 88, 147 and Grenada law reform, 87 and testing strategies, 197 by health care providers, 80, 116, 127 indirect forms, 101 omitted in cost-effectiveness analysis, 106 omitted in models, 122–23 UNAIDS targets, 8, 113 disease burden, 2, 147 and aid eligibility, 159, 160, 163, 164, 166, 171 Dombos, Tamás, 49 Dybul, Mark, 98, 162, 180 Eastern Europe and Central Asia (EECA), 14, 66, 109, 168, 172 rise in HIV, 143 emic vs. etic categories, 208–9 epistemological exclusion, 94, 115, 236 epistemology, 39, 237 and trust, 168 Eswatini, 109 HIV response, 10, 183 investment case, 107 Fast-Track approach, viii, 8, 10 and “lives saved,” 23 and decline in deaths, 236 and Global Fund indicators, 31 and models, 115, 120 and Plato’s “noble lie,” 20, 116 and prioritization, 14, 19 estimated cost, 11 weak consideration of human rights, 113 Females exchanging sex (FES). See sex workers Ferguson, James, 43, 128 Foucault, Michel, 217, 221, 231, 233

gender-based violence, 196, 241, 242 and reverse burden of proof, 196 data challenges, 25–26 debate over definition, 136 in Kenya, 53, 177 PEPFAR programs, 174 underreporting, 186–88 Ghys, Peter, 14, 127, 128, 129, 130, 248 Global Commission on HIV and the Law, 47 global health finance, 11 Global Network of People Living with HIV (GNP+), 2, 22 Global Network of Sex Work Projects (NSWP), 61, 62, 207 global scale-up, 9, 11, 22, 23, 97, 115, 116, 119, 120, 121, 122, 123, 129, 184 GOALS software, 101 analysis of, 104–5 and gender, 124–25 Golichenko, Mikhail, 169, 249 Greater Involvement of People living with HIV (GIPA), 21 Grenada, 42 and donor transition, 65–68, 71, 82–85, 86, 171 Constitutional referendum, 87 health budget, 67, 242, 243 history, 70–71, 79, 206, 208 HIV response, 137, 214 social conservatism, 79–80, 87, 90, 91, 204–5, 241, 245 Study findings, 211–12, 214 US invasion, 68, 71 Grenada Planned Parenthood Association, 79, 81, 137, 205, 210, 211, 248 GrenCHAP, 87–90, 135, 210, 211, 238, 244 Griffith, Tabitha Saoyo, 194–95, 197, 248 Gross national income per capita (GNIpc), ix, 157 and aid eligibility, 4–5, 158–59, 163–64, 167–68 World Bank thresholds, 158 Gurung, Bikas, 228, 229 Gustav, Rico, 22, 38, 66, 147, 150, 151, 165, 166, 168, 172, 234 photo, 141 harm reduction, 19, 57, 109, 146 and donor transition, 142 and increase in HIV, 147 deprioritized in investment cases, 109 in China, 222 in Russia, 153, 161, 169–70 low global coverage, 143 omitted from models of scale-up, 124 Hasbún, Julia, 75, 90, 133, 134, 135, 136, 202, 204

297

INDEX

health systems strengthening, 36–37 Hearld, Ria, 132, 248 HIV disease burden definition, 5 eradication vs. elimination, 9 global prevalence, 9 infection rates, 18–19 treatment access, 1, 3, 8, 9 human rights, 116, 161, 162, 169, 213 aid accountability, 215 and anthropology, 39 and biometrics, 61 and cost-effectiveness, 94–114 and death penalty, 47 and gender within UN, 52, 57 and prioritization, 110–13 impact on HIV, 47, 116, 127, 128, 164, 179 in Kenya’s constitution, 174, 193 omitted from models, 115, 122–23, 129, 131 right to health, 110–11 UN mechanisms, 170 Human Rights Watch, 5, 40, 127 and China, 154, 215, 218 and compulsory drug detention centers, 219, 223, 224, 228 and research ethics, 232 and Venezuela, 5 Hungary, HIV response, 48, 49 Hunter, Andrew, 249 identity, social construction of, 209 IDU. See people who inject drugs (PWID) incest. See gender-based violence indicators, ix critiques, 24, 100 Global AIDS Monitoring, 10, 128 key performance indicators, ix LGBTI inclusion, 129 sites of contest, 1, 4, 140–69 tools of global governance, 2 tools of governance, 84 indigenous field workers, 41, 202, 213, 239, 241 indigenous peoples, 6, 42, 63 Indonesia HIV response, 47 infectious disease models, 9, 115–31 International AIDS Conference, 52, 63, 143, 146 International Committee of the Red Cross (ICRC), 186, 196, 230, 231 International Covenant on Economic, Social and Cultural Rights, 110, 112, 169 International Gay, Lesbian, Bisexual and Transgender Association (ILGA), 48, 49, 72

298

International Guidelines on HIV and Human Rights, 21, 110 International HIV/AIDS Alliance (Frontline AIDS), 82 International Network of People who Use Drugs (INPUD), 228, 229 intimate partner violence. See gender-based violence investment cases institutional, 23, 30–31, 114 national, 94, 96, 107–10 Jamaica, HIV response, 72, 85 Jerven, Morton, 158 Joint UN Programme on HIV and AIDS (UNAIDS), 6, 8, 42, 50, 108, 150, 163, 197, 225, 227, 248 and biometrics, 56, 59 and data on HIV, 72, 143, 160, 171, 183 and modeling, 120, 130 civil society in governance of, 175, 237 critique of Global Fund prevention approach, 123 data on HIV, 23, 33, 48, 49 executive director resignation, 10, 26, 52 financing estimates, 11, 109, 130 guidance on size estimates, 32, 241 guidelines on key populations, 16 guidelines on size estimates, 73 human rights costing tool, 125 indicators, 10 Lancet Commission, 16 Programme Coordinating Board, 41, 237 social enablers, 125, 128 Spectrum, 102 Strategic Investment Framework, 97 target-setting, 8, 11, 14, 36, 50, 115, 125, 128, 129 Kamau, Grace, 59 Kavanagh, Matt, 11, 61, 249 Kazatchkine, Michel, 155, 156, 161 KELIN (Kenya Legal & Ethical Issues Network on HIV & AIDS), ix, 42, 51–52, 54–56, 58, 176, 193–95, 248 Kenworthy, Nora, 36, 99, 115 Kenya, 62, 110, 177 biometrics, 54, 58 HIV response, 35, 53, 112, 116, 129, 172, 173, 178, 179 human rights, 52, 126, 129, 174 Key Populations Consortium, 53, 54–56 litigation on right to health, 175, 192 National AIDS and STI Control Program (NASCOP), 55–57, 59–60 PEPFAR allocation, 182 rates of intimate partner violence, 185, 187

INDEX

studies of assisted partner notification services, 188–90 key populations and the data paradox, 45 definition, 5, 16 indigenous peoples excluded, 6 rates of new infections, 23 service coverage KPI for Global Fund, 32–33 Kyrgyzstan, 46 Latour, Bruno, 41 Leon, Phil, 137, 202, 203 malaria, 153, 224, 235, 243 Maleche, Allan, 51–52, 116, 139, 140, 150, 173, 175, 176, 193, 194, 195, 248 and donor transition, 172 photo, 141 mapping, politics of, 69–70, 76, 208 Martin, Francis, 67, 68, 91, 92, 93, 135, 137, 204, 210, 213, 241, 244, 248 Mathlin, Nigel, 87–90, 248 men who have sex with men, 6 implausibly low size estimates, 48–50 middle-income countries and aid eligibility, 157–62 and donor transition, 24, 65, 81–83, 142, 146, 147, 152 and HIV response, 20, 22–23, 71, 119, 143, 153 and income inequality, 5 donor transition, 14 World Bank definition, 4 monitoring human rights, 231 in detention, 215–33 Murenga, Maurine, 116, 175, 248 photo, 141 neoliberalism, 99–101, 112 definition, 99 Nigeria aid allocation, 182, 183 census, 159 HIV response, 35, 102, 124, 158 Njane, Peter, 51, 57, 60, 112 OneHealth software, 104, 106, 125 opioid substitution therapy (OST), 19, 109, 124, 143 Optima software, 101, 102–4, 107, 109 Organization of Eastern Caribbean States (OECS), ix, 69, 73, 76, 201, 241, 242 Organization of Economic Cooperation and Development (OECD), ix, 12, 166

Development Assistance Committee (DAC) list, 160, 161, 165 Otieno, Jackson, 53, 57 Pan-Caribbean Partnership against HIV and AIDS (PANCAP), 71, 83 panopticon, 218, 222, 229 definition, 217 participatory action research, 75, 202, 239 definition, 74 Paul-Gilbert, 61, 105, 207, 249 people who inject drugs (PWID), 19, 147, 215–33 people who use drugs, 18, 19, 21, 53, 56, 150 Phillip, Nicole Laurine, 70, 206 Podmore, Mike, 23, 150, 151, 152, 153, 154, 162, 166, 167, 168, 171, 172, 248 photo, 141 population size estimates, 32, 33, 35 and community-led data, 62 and denialism, 46 and subpopulations, 88 in Caribbean, 64, 72 methods, 73–74 Potemkin effect, 50, 216, 230, 231, 233 prisoners, 18, 42, 105, 231 Resilient and Sustainable Systems for Health. See Health System Strengthening Robert Carr Fund for Civil Society Networks, 12, 249 Romania aid eligibility, 148, 161 HIV response, 146 rule of rescue, 170 Russian Federation aid eligibility, 152–53 HIV response, 143–46 Saavedra, Jorge, 153, 158, 159, 249 Sabin, Keith, 33, 128, 248 Saint Lucia, 41, 48, 73 Sands, Peter, 23, 29, 60, 86, 248 Sarang, Anya, 169, 170, 171, 249 Scott, James C., 47, 69, 208 Service Availability and Readiness Assessment (SARA) index, 37 sex workers, viii, ix, 5, 18, 21, 138, 194, 212 and agency in research, 62–63 and biometrics, 57 and cost-effectiveness analysis, 102, 104 and decriminalization, 19 and labor rights, 207 in Belarus, 109 in Caribbean, 64, 73, 134, 138, 211, 214, 241, 242 in China, 221

299

INDEX

sex workers (cont.) in Eswatini, 108 in global health governance, 237 in Grenada, 78, 79, 87, 90, 203, 204, 205–7 in Jamaica, 239 in Kenya, 53, 55, 56, 62 in Marshall Islands, 49 in models, 118, 124 in Myanmar, 45 male, 105–6, 107, 108, 134, 211 policing, 124, 126 Sidibé, Michel, 10 slavery, 70, 208 Soca music, 206 social media #MeToo, 26 and HIV activism, 2, 151, 174, 175, 176, 234 and key populations, 134 South Africa, 63, 110, 126, 158, 234 HIV and gender-based violence, 185, 191 HIV response, 14, 17, 35, 84, 120, 182, 183 policing in, 124 Springer, Dereck, 71–72, 83, 85, 249 Strategic Investment Framework, 96–97, 125 Sudan HIV response, 35, 107–9 Sustainable Development Goals (SDGs), 7, 19, 25, 46, 130 Sylvester-Gill, Jeannine, 79, 81, 205, 210, 213 Tanzania, 208 HIV and gender-based violence, 185 HIV response, 35 human rights, 57 Test and Treat, 118–22 The Global Fund to Fight AIDS, TB and Malaria allocation methodology, 149 Board, 2, 4, 28, 33, 36, 41, 86, 100, 140–72, 224, 225 Board, civil society on, 3, 6–7, 22, 23, 32, 38, 52, 116, 140–72, 175, 229, 237, 249 Board, constituencies, 28 Board, donors on, 33, 98, 140–72, 180 Board, Implementer Group of, 71 Board, policy on compulsory treatment, 227 business model, 28 Eligibility Policy, 1–3, 4–7, 140–72 NGO Rule, 152–53, 161–62, 169–70, 171 no data provision, 6, 160, 165 Equitable Access Initiative, 162–65 establishment of, 1–2 Framework Document, 154–55 Human Rights Reference Group, 95–96 key performance indicator on human rights, 223–29

300

key performance indicators (KPIs), 26–38, 168 Sustainability, Transition and Co-financing (STC) Policy, 148 Technical Review Panel (TRP), 155, 156 transactional sex, 74, 79, 122, 133, 138, 205 transgender people, x, 5, 18, 19, 32, 112 and gaps in data, 33, 53 and violence, 25, 186 criminalization, 47 in Caribbean, 73, 134, 205, 212 in Eswatini, 107 in global health governance, 237 in Kenya, 53, 239 in Southeast Asia, 103 in Sudan, 108 omitted from models, 105 on Board of the Global Fund, 175 Treatment as Prevention, 123 tuberculosis, 18, 42, 52, 76, 102, 119 human rights, 176, 224 in Caribbean, 73 Uganda, 25, 37 and denialism, 47 HIV and gender-based violence, 185 HIV response, 35, 177, 182, 183 UNAIDS, 5–6 United Nations Development Programme (UNDP), 42, 109, 163 United Nations General Assembly, 7, 11, 25, 31, 47, 110, 111, 179, 216, 219, 234 United Nations Office of Drug Control (UNODC), 42, 225, 227 United Nations Special Rapporteur on Cambodia, 219 United Nations Special Rapporteur on Extreme Poverty and Human Rights, 111 United Nations Special Rapporteur on the Right to the Highest Attainable Standard of Physical and Mental Health, 219 United Nations Special Rapporteur on Torture and Other Cruel, Inhuman or Degrading Treatment or Punishment, 216, 219 United States, 65 Congress, 12 development assistance, 12, 72, 81, 180 internal inequality, 111 political volatility and development assistance, 12 role in China, 217 role in the Global Fund, 33 role in Venezuela, 243

INDEX

United States President’s Emergency Plan for AIDS Relief (PEPFAR), ix, 42, 59, 115, 245, 248 and biometrics, 61 and Country Operational Plans (COPs), 51, 183–84 and key population size estimates, 51 and lives saved, 30 and prioritization, 180–85 and the drive for data, 60, 179, 195 budget constraints, 14, 153 DREAMS initiative, 174, 181, 196 in Caribbean, 82 Universal Declaration of Human Rights (UDHR), 110 Universal Health Coverage (UHC), 36, 234, 235 Venezuela appeal to the Global Fund, 1–3, 4–7, 153, 160, 243 development assistance to Grenada, 243 health catastrophe, 5–7 Viet Nam, 231 compulsory drug detention centers, 219, 220, 226 drug policy, 218 HIV response, 35

136, 138, 199, 201, 205, 207, 209, 210, 211, 212, 240, 241, 242, 248 Wolfe, Daniel, 230 World Bank, 99, 171 country income classifications, 4, 71, 157, 158, 165 HIV financing, 81, 98, 102, 106, 107, 108, 109, 159 role in the Global Fund, 2, 155, 157, 163 World Food Programme, partnership with Palantir, 57 World Health Organization (WHO), 42, 72, 97, 163, 248 and lives saved, 114 aPNS and intimate partner violence, 188–93, 195, 196, 197 civil society role in, 175 data on intimate partner violence, 188 guidance on size estimates, 32, 73 guidelines on gender-based violence, 187 guidelines on HIV, 119, 181 guidelines on key populations, 6, 19 guidelines on testing, 174, 184 health systems strengthening, 37 in Kenya, 55 investment case, 114 position on decriminalization, 19 role in global health governance, 16

Waters, John, 50, 63–64, 67, 68, 73, 74, 75, 76, 77, 80, 81, 87–90, 132, 133, 134, 135,

Zambia HIV response, 35, 182, 183

301

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