Since 2000, the world has witnessed an unprecedented increase in development assistance for health. Millennium Development Goals (MDGs) 4 (reduce child mortality), 5 (improve maternal health), and 6 (combat HIV/AIDS, malaria, and other diseases) codified this focus. The United States has led the global response to the health-related MDGs by initiating several large bilateral global health assistance programs. These include the President’s Emergency Plan for AIDS Relief (PEPFAR)—a program that since 2003 has contributed $54 billion toward AIDS treatment, care, and prevention—and the President’s Malaria Initiative, which supports the Global Fund for AIDS, TB, and Malaria—an enterprise that has provided over $16 billion in funding to fight HIV/AIDS and $8 billion for malaria control since 2002. The impact of this funding has contributed to substantial health improvements: Since 2000, overall child mortality has declined by 50 percent, HIV/AIDS mortality has declined by 42 percent since 2004, while malaria mortality has dropped by more than 50 percent. And the World Health Organization recently announced that Millennium Development Goal 4, related to malaria mortality, had been achieved.
Less is known, however, about whether these health successes have translated into economic improvements, which is the ultimate goal of sustainable development. Indeed, new evidence from the fight against HIV/AIDS and malaria strongly suggests that there are positive economic effects associated with health investments. Reduced disease can improve economic outcomes through multiple channels: 1) greater labor productivity and school attendance from less absenteeism, 2) better cognition and school performance through less disease in utero and in early life, and 3) greater incentives for education and savings with lengthened life expectancy. However, there are challenges to accurately identifying these initiatives’ economic impact because many of them began at approximately the same time and were aimed at similar nations. Greater program transparency and data collection is therefore imperative for improving evidence-based policy and effective use of scarce development resources.
PEPFAR funding associated with an increase in employment in 10 sub-Saharan African countries
Recent research suggests that PEPFAR has indeed had a positive economic impact: Our recent paper, “PEPFAR funding associated with an increase in employment among males in ten sub-Saharan African countries,” compares employment trends in 10 countries that received PEPFAR funding against 11 that received little to no funding. PEPFAR support was associated with a 13 percent increase in employment among males in countries receiving aid compared to those that did not, though no effect was found for females. In addition, we found that increasing PEPFAR per capita funding by $100 was associated with a 9.1 percentage point average increase in employment among males. Combining our estimated increase in male employment with male population share by country, and assuming the average wage is equal to GDP per capita, we calculate that PEPFAR’s economic benefits are equal to approximately 50 percent of PEPFAR’s cost. Although our paper is the first to explore the employment impact of PEPFAR across most of sub-Saharan Africa, the results are necessarily incomplete because our data source (the Demographic and Health Surveys) collects limited economic information.
Malaria eradication campaign in Uganda associated with long-term improvement in educational and economic outcomes
Another new paper, “Malaria Eradication and Economic Outcomes in sub-Saharan Africa: Evidence from Uganda,” which investigated the long-term economic effects of an historical malaria eradication project in southwestern Uganda, found that eradication produced gains in educational attainment for males and females and increased the probability of wage work for males. To obtain these results, we compare outcomes in the eradication district against a weighted average of other districts in Uganda, chosen so that the characteristics of the comparison area closely resemble those of the treatment area before eradication. The campaign occurred between 1959-60 and was part of the WHO’s Global Malaria Eradication Program (GMEP), which intended to eliminate the disease worldwide using DDT spraying and distribution of anti-malarial medications. Previous studies explored the economic impact of GMEP eradication campaigns in peripheral areas, finding greater income for males in India, earnings gains in the U.S. and Latin America, and schooling improvements for girls in Paraguay and Sri Lanka. However, in addition to more intense transmission, the strain of malaria prevalent in these studies, Plasmodium vivax, causes long-lasting fever, but rarely death. Whereas the strain prevalent in much of sub-Saharan Africa and the area of southwestern Uganda investigated, Plasmodium falciparum, produces acute, severe fever and death at a substantially higher rate than P. vivax. Therefore, these results show that reducing malaria-related morbidity and mortality in sub-Saharan Africa can also improve human capital accumulation and provide economic benefits.
Even with this recent expansion in health investment, scholars have questioned the evidence on whether these initiatives at scale caused reductions in mortality, while limited data in the developing world impedes evaluation of economic impact. For example, while compiling a book of case studies on global health successes called Millions Saved, the Center for Global Development (CGD) was not able to identify a malaria control study that reduced mortality and fit its selection criteria of rigorous evidence. In a subsequent post, CDG did acknowledge additional papers that indicate malaria control benefits in Zambia and Kenya. However, this blog exchange highlights the difficulty in attributing causality to a set of interventions that most believe have produced very large mortality benefits. As noted above, identifying the specific impact of one program is made more difficult by their approximately concurrent introduction and the fact that some explicitly coordinate their activities: For example PMI is only active in nations with Global Fund operations. Another example is in our PEPFAR paper described above, which uses national variation in PEPFAR funding. We control for Global Fund HIV-related disbursement, but cannot completely eliminate the possibility that pre-existing trends in PEPFAR nations or economic growth drives the results we find. Data on PEPFAR’s activities and program intensity at the subnational level would improve our estimates of impact.
Improved data transparency for better evidence
Unlike any time before, we now have the financial and technical capacity to scale up existing health interventions to decisively close the global health equity gap. However, since the worldwide economic recession, rapid growth in development aid for health has stagnated. The examples discussed above fit into a growing body of literature that suggest global health efforts, largely thought to be humanitarian at first, can also help in the fight against global poverty. To allocate scarce aid funding effectively, the effect of these programs should compare program cost against the full health and economic effects.
Currently, our understanding of these effects is unfortunately incomplete due to data limitations. While greater transparency among the involved agencies would help close this evidence gap, progress is being made. For example, the WHO, World Bank, and USAID recently committed to improving data transparency and strengthening health information systems. Such investments will pay off by providing researchers and policymakers with timely and accurate information on the full impact of policies in aid-recipient countries. If subnational PEPFAR funding and timing data had been available in our evaluation mentioned above (as is increasingly the case), we could have more accurately pinpointed program impact. Better information on the malaria control activities of the Global Fund and PMI would also strengthen our ability to identify mortality and economic benefits. Moreover, one analysis characterizes as “trivially small” the cost of financing the gap in developing-country surveys to monitor program effects. Even with continued technological advances in global health, measurement to encourage broad deployment of the most cost-effective existing interventions represents our best prospect for continued improvements in human health and economic development.
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