20 years of advances in global health data: Now there’s an app for that

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Bill Gates appreciates the importance of high-quality data to guide decisions. He was the keynote speaker at the 20th anniversary symposium of the Global Burden of Disease (GBD) study in Seattle recently. Gates was followed by Jim Kim, President of the World Bank. These two very heavy hitters – one, the richest man in the world, and one who runs the largest investment bank for developing nations – are huge fans of high-quality data that can be used to make decisions and guide investments in global health and development. I’m using the occasion of this anniversary to share more about the GBD study with our readers and to highlight the innovative use of data to improve global health.

Evidence in a post-truth world from Global Evidence Summit

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Recently I wrote a post about the Global Evidence Summit, which I attended in September. I commented that one thing I really liked about the conference is that it had some great plenary sessions. In this post, I highlight some of the key ideas that came from the fourth plenary of the conference, titled “Evidence in a Post-Truth World.”

The plenary started with Trish Greenhalgh, who is a Professor of Primary Care Health Sciences at the University of Oxford. Greenhalgh’s bio for the conference lists three areas her work covers, one of which is the complex links (philosophical and empirical) between research, policy and practice. Her speech focused on these philosophical links. She started with Aristotle’s On Rhetoric, in which he lays out three means of persuasion for an orator. The first is logos, which we can think of as evidence. The second is ethos, which we can think of as credibility, and the third is pathos, which we can think of as emotion. Greenhalgh suggested that the post-truth world is one where logos – evidence – is no longer a useful tool of persuasion, leaving us only with the other two.

What I learned about evidence networks at the Global Evidence Summit

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A couple of weeks ago, I was fortunate to attend the Global Evidence Summit (GES) in Cape Town, South Africa. GES was billed as being the first conference of its kind, jointly organized by the Cochrane Collaboration, the Campbell Collaboration, and several other groups to focus on evidence-based policy making across sectors. Those of us who attended the What Works Global Summit in London last September considered GES the second conference of its kind, and we were excited to reconnect with each other this year in Cape Town.

The conference brought together researchers and policy analysts in the fields of health, education, and international development to explore that long and often tortuous path between a single study and a policy or program that is evidence based. Sessions covered topics such as evidence mapping, systematic reviews, rapid reviews, standard and guideline setting, big data, and policy engagement. In this post, I report on what I learned about evidence networks in the first day’s plenary. For readers interested in learning more about the conference itself, I provide a quick review at the end of the post.

The science of beating HIV and AIDS

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The International AIDS Society (IAS) Conference on HIV Science (IAS 2017) in Paris last week brought together over 6,000 scientists, clinicians, public health practitioners and officials to review the state of the science intended to control and eventually end the HIV/AIDS epidemic. The central thrust of the global effort to control the epidemic is achieving the 90-90-90 targets set by the Joint United Nations Programme on HIV/AIDS (UNAIDS). These targets state that, by 2020, 90% of those living with HIV know their status, 90% of known HIV-positive individuals receive sustained antiretroviral therapy (ART), and 90% of individuals on ART have durable viral suppression. We know that HIV-infected persons with viral suppression, while not cured, do not transmit HIV infection – hence the focus on treatment, which is prevention.

While some countries have made encouraging progress, we are far short of the global 90-90-90 targets, and worse, there were 1.8 million new HIV infections in 2016. We need science to inform the way forward to reach the targets. In this post, I will report on some of the conference presentations around two major themes: 1) generating and applying evidence to optimize the use of current tools, and 2) developing new and improved methods for HIV prevention, care and treatment.

Don’t waste evidence on the youth! Recent data highlights education and employment trends

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A recent New York Times article describes a major contemporary challenge facing governments: the world has too many young people. A quarter of the world’s population is young (ages 10-24), and the majority live in developing countries. Policy makers are struggling with high levels of youth unemployment in every country, but a key challenge in developing countries has been a lack of data on education and employment characteristics. To fill this evidence gap, FHI 360’s Education Policy and Data Center (EPDC) recently added country-level Youth Education and Employment profiles to the resources available on our website. In this post, I describe the data and how they were collected, and I give some examples of how these data can be used to inform policy making and program design.

Photo credit: Garth Cripps/Blue Ventures; used with permission

Research on integrated development: These are a few of my favorite things

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You may have recently noticed an uptick in conversations within development circles on this underlying theme: A full realization of the new Sustainable Development Goals (SDGs) requires critical changes in what we do based on understanding the significant linkages between social, economic and environmental sectors. Intuitively, that seems fairly sensible. These linkages suggest that we should be using integrated approaches. But what do we know about the effectiveness of intentionally integrated approaches to development? In this post, I share a few of my very favorite examples of research that provide evidence on the effectiveness of integrated approaches.

Academia takes on global health

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The Consortium of Universities for Global Health (CUGH) held their 8th Annual Conference in Washington DC this week. More than 1,700 people from every corner of the globe gathered for three days to explore how the world’s academic institutions can best contribute to improving global health. This year’s meeting was particularly interesting given the contrast between current prospects for financial support for global health and the trajectory of support over the last 15 years. That contrast made several of the key topics discussed at CUGH even more salient to me.

How many scientific facts are there about science, technology, and innovation for development?

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There is a lot of excitement these days about science, technology, and innovation and the potential for these activities to contribute to economic and social development globally. The flurry of activity begs the question, how much of this excitement is supported by scientific facts? To help answer this question, the US Global Development Lab at USAID commissioned a project to create and populate a map of the evidence base for science, technology, innovation, and partnerships (STIP). As part of the project, scoping research was conducted to identify not just where there are evidence clusters and gaps, but also where the demand for new evidence by stakeholders is the greatest. In the recently published scoping paper, I and my co-authors analyze the data in the map together with the information from the stakeholders to recommend priorities for investment in new research on STIP. While there is good evidence out there, new research is necessary for strategies and programming to fully benefit from scientific facts. In this post, I briefly describe the research we conducted, summarize a few of the many findings, and list some of our recommendations.

Mining for development gold: Using survey data for program design

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As global health resources become more scarce and the prevalence of international crises increase, it is more important than ever that we design and target development programs to maximize our investments. The complexity of the applicable social, political and physical environments must be taken into consideration. Formative research can help us to understand these environments for program design, but formative research is often skipped due to budgetary, time or safety concerns that constrain the collection of new data. What many overlook is the vast untapped potential of existing household survey data that are rigorously collected, clean and freely available online around the world. By mining existing survey data, we can conduct the formative research necessary to maximize development impact.

Should PEPFAR be renamed the “President’s Epidemiologic Plan for AIDS Relief”?

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The effective use of data within PEPFAR has played a central role in getting us to the point where we can finally talk about controlling the HIV epidemic and creating an AIDS-free generation. PEPFAR’s transition from an emergency approach to one driven by real-time use of granular, site-level data to guide programmatic investments has contributed to achieving epidemic control. In view of this improved use of data, perhaps the “Emergency” in PEPFAR should now be changed to “Epidemiologic.”

Beyond research: Using science to transform women’s lives

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It was a warm spring day in 2011, and eight of my colleagues were helping me celebrate the realization of a long-awaited policy change in Uganda by sipping tepid champagne out of kid-sized paper cups. A colleague asked me, amazed, “How did you guys pull this off? What’s your secret to changing national policy?” I offered up some words about patience, doggedness, and committed team work. My somewhat glib response is still true, but since then I’ve thought a lot about what it takes to get a policy changed.