Keynote address to Thematic session of 49th UNAIDS Programme Coordinating Board, 10 December 2021
Thank you moderator, and also for the important work your team and UNAIDS does to strengthen data in the HIV response. It’s an honor to be asked by civil society and communities to join this important discussion on Human Rights Day.
I’d like to take this moment to reflect on the big picture. The hard truth is that funding for HIV is diminishing, and we urgently need data to make hard decisions. Who lives, who dies, increasingly depends on data.
But health data is not neutral: it is shaped by power and inequalities.
Who does the counting? Who gets counted? Who owns the data? The answers to these questions reflect deep historical disparities, among and within countries, that have shaped the HIV epidemic and the response. These disparities shape the data we have, and the data we lack. To get better data, we must address these inequalities.
Let me explain. In my research, I’ve seen that community-led HIV organizations often have rich data about clients — because they have their trust. But this richness is rarely reflected at national levels, where the data is plagued with gaps. And at global levels, we wind up working with mathematically modeled estimates.
These gaps in data are acute for key populations. The UNAIDS World AIDS Day report tells us that key populations and their partners account for 65% of new HIV infections. But key population size estimates may be off by 50% – many countries have no data at all. Why?
The answer, I argue, has to do with power: What Baral and Greenall call a data paradox. Politicians may deny key populations exist – they say, “there are no men who have sex with men in my country” or “there are no drug users, sex workers or transgender people”; so no research is done about their urgent health needs. The lack of data means services that could save their lives are not funded — and the lack of services reinforces the lack of data. It’s a vicious cycle of inequality in which absence of evidence is used as evidence of their absence.
We could end HIV. We’re not, and it’s in part because of uncounted people.
But in good-faith efforts to address this problem, we run into another form of power: historical inequalities between Global North and Global South. Some donor countries put pressure on implementers to produce data on key populations, improve coverage, or risk losing funding. And sometimes that pressure from outside does help people at the local level.
But other times, donor pressure can backfire. National health officials may be caught between a rock and a hard place: between the threat of losing funding on which they
depend, and the threat of backlash and violence if the true size of key populations becomes widely known.
Stuck between a rock and a hard place, what breaks? The data. Some health agencies do the size estimate, but never publish the data. Others appear to artificially reduce size estimates so they can report higher coverage, hoping donors will be impressed with their success, and keep the funds flowing.
Still others take that pressure from donors and pass it on to communities; at the moment of their greatest vulnerability, when they need health services, communities are asked to give up their locations, biometrics, real names, ID numbers, names of partners.
But this data can be volatile. In the wrong hands, data on women, key populations and people living with HIV can expose them to discrimination, arrest, hate crimes, intimate partner violence. These crimes are often not reported. Out of well-grounded fears, many will avoid health services and avoid being counted.
Colleagues, we are all – the whole global HIV response — stuck in this data paradox. Political power shapes the data we have and the data we lack. If we keep doing what we’ve always done, we’ll get the same results. How can we shift power and produce better data?
Instead of top-down pressure, let’s invest in data from the ground up through community-engaged research.
There are hundreds of studies of HIV using community-engaged research from all over the world: research co-designed with communities not just as data-gatherers, but thought partners. I’m principal investigator of one such qualitative study in Bangladesh, Colombia, Ghana, Kenya and Vietnam, with people living with HIV, social scientists and lawyers, collaborating to study the experience of young adults with digital health.
But let me finish with an anecdote from another study that illustrates the transformative potential of community-led research – from the Caribbean.
I first visited the Eastern Caribbean in 2017 and found key populations organizations in trouble. A major donor had pulled their funding to invest it in larger countries where they could reach bigger numbers. The Caribbean groups had to pack up their laptops and ship them back to the donor. They had never had national size estimates for key populations. Overnight, they lost their programmatic data, and they were demoralized. Their own data about their own community did not belong to them.
Then Caribbean Vulnerable Communities (CVC), a regional NGO, received funding from the Global Fund through the Organization of Eastern Caribbean States (OECS) to do community-led key population size estimates in six countries. As I observed the study over three years, I
saw a transformation: the community worked with social scientists to design rigorous, innovative methods to count key populations while protecting their security; gradually, community leaders became experts, gained new authority and new funding. Government officials, communities, NGOs and researchers all formed trust, while learning together, developing a shared sense of mission.
It’s a great study, with rich results. It won the Robert Carr Research Award. But sadly, it has never been published. The six countries involved should officially publish the data so we can all learn from it.
Seye Abimbola, a leading thinker in the movement to decolonize global health, calls this principle “moral proximity”: when people have a role in producing knowledge about themselves, he says, they see how their efforts help to promote the common good: They exercise agency, gain dignity and meaning from shaping their own destiny.
Through community-led research, we can create transformative change together, in partnership with those we’ve been failing to reach – the people who really count.
Abimbola S. The uses of knowledge in global health. BMJ Global Health 2021;6:e005802. doi:10.1136/bmjgh-2021-005802.
Baral S, Greenall M. The data paradox. Where there is no data [blog], 7 May 2013. https://wherethereisnodata.wordpress.com/2013/07/05/the-data-paradox/.
UNAIDS. Key populations atlas [database]. https://kpatlas.unaids.org/dashboard#/home.
UNAIDS. Unequal, unprepared, under threat: Why bold action against inequalities is needed to end AIDS, stop Covid-19 and prepare for future pandemics. Geneva, CH: UNAIDS. November 2021. https://www.unaids.org/en/resources/presscentre/pressreleaseandstatementarchive/2021/november/20211129_unequal-unprepared-under-threat.
Waters J, Budhwani H, Hasbun J, Hearld KR. Estimation of Key Population Size of Men Who Have Sex with Men (MSM), Transgender Women and Female Sex workers in the Eastern Caribbean. Final Report, June 31st, 2018. Unpublished.