IDEAS home Printed from https://ideas.repec.org/a/plo/pgph00/0002467.html
   My bibliography  Save this article

Assessing the impact of the president’s emergency plan for AIDS relief on all-cause mortality

Author

Listed:
  • Gary Gaumer
  • Yiqun Luan
  • Dhwani Hariharan
  • William Crown
  • Jennifer Kates
  • Monica Jordan
  • Clare L Hurley
  • Allyala Nandakumar

Abstract

This study estimated the impacts of PEPFAR on all-cause mortality (ACM) rates (deaths per 1,000 population) across PEPFAR recipient countries from 2004–2018. As PEPFAR moves into its 3rd decade, this study supplements the existing literature on PEPFAR ‘s overall effectiveness in saving lives by focusing impact estimates on the important subgroups of countries that received different intensities of aid, and provides estimates of impact for different phases of this 15-year period study. The study uses a country-level panel data set of 157 low- and middle-income countries (LMICs) from 1990–2018, including 90 PEPFAR recipient countries receiving bilateral aid from the U.S. government, employing difference-in-differences (DID) econometric models with several model specifications, including models with differing baseline covariates, and models with yearly covariates including other donor spending and domestic health spending. Using five different model specifications, a 10–21% decline in ACM rates from 2004 to 2018 is attributed to PEPFAR presence in the group of 90 recipient countries. Declines are somewhat larger (15–25%) in those countries that are subject to PEPFAR’s country operational planning (COP) process, and where PEPFAR per capita aid amounts are largest (17–27%). Across the 90 recipient countries we study, the average impact across models is estimated to be a 7.6% reduction in ACM in the first 5-year period (2004–2008), somewhat smaller in the second 5-year period (5.5%) and in the third 5-year period (4.7%). In COP countries the impacts show decreases in ACM of 7.4% in the first period attributed to PEPFAR, 7.7% reductions in the second, and 6.6% reductions in the third. PEPFAR presence is correlated with large declines in the ACM rate, and the overall life-saving results persisted over time. The effects of PEFAR on ACM have been large, suggesting the possibility of spillover life-saving impacts of PEPFAR programming beyond HIV disease alone.

Suggested Citation

  • Gary Gaumer & Yiqun Luan & Dhwani Hariharan & William Crown & Jennifer Kates & Monica Jordan & Clare L Hurley & Allyala Nandakumar, 2024. "Assessing the impact of the president’s emergency plan for AIDS relief on all-cause mortality," PLOS Global Public Health, Public Library of Science, vol. 4(1), pages 1-14, January.
  • Handle: RePEc:plo:pgph00:0002467
    DOI: 10.1371/journal.pgph.0002467
    as

    Download full text from publisher

    File URL: https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0002467
    Download Restriction: no

    File URL: https://journals.plos.org/globalpublichealth/article/file?id=10.1371/journal.pgph.0002467&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pgph.0002467?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guido W. Imbens, 2022. "Causality in Econometrics: Choice vs Chance," Econometrica, Econometric Society, vol. 90(6), pages 2541-2566, November.
    2. Christoph Breunig & Patrick Burauel, 2021. "Testability of Reverse Causality Without Exogenous Variation," Papers 2107.05936, arXiv.org, revised Apr 2024.
    3. Bingbo Gao & Jianyu Yang & Ziyue Chen & George Sugihara & Manchun Li & Alfred Stein & Mei-Po Kwan & Jinfeng Wang, 2023. "Causal inference from cross-sectional earth system data with geographical convergent cross mapping," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Loftus, Joshua R., 2024. "Position: the causal revolution needs scientific pragmatism," LSE Research Online Documents on Economics 125578, London School of Economics and Political Science, LSE Library.
    5. Peter Hull & Michal Kolesár & Christopher Walters, 2022. "Labor by design: contributions of David Card, Joshua Angrist, and Guido Imbens," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(3), pages 603-645, July.
    6. Vikram Dayal & Anand Murugesan, 2020. "Demystifying causal inference: ingredients of a recipe," IEG Working Papers 393, Institute of Economic Growth.
    7. Barnor, Kodjo & Caton, James & Miljkovic, Dragan, 2023. "The role of funding on research and science: The impact of glyphosate herbicides on health and the environment," Journal of Policy Modeling, Elsevier, vol. 45(1), pages 103-120.
    8. Shishir Shakya & Nabamita Dutta, 2024. "How Individualism Influences Female Financial Inclusion through Education: Evidence from Historical Prevalence of Infectious Diseases," Working Papers 24-03, Department of Economics, Appalachian State University.
    9. Kulkarni, Nirupama & Malmendier, Ulrike, 2022. "Homeownership segregation," Journal of Monetary Economics, Elsevier, vol. 129(C), pages 123-149.
    10. Neil Christy & Amanda Ellen Kowalski, 2024. "Counting Defiers in Health Care: A Design-Based Model of an Experiment Can Reveal Evidence Against Monotonicity," Papers 2412.16352, arXiv.org, revised Mar 2025.
    11. Martin Huber, 2024. "An introduction to causal discovery," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-16, December.
    12. Chen, Lifeng & Wang, Kaifeng, 2022. "The spatial spillover effect of low-carbon city pilot scheme on green efficiency in China's cities: Evidence from a quasi-natural experiment," Energy Economics, Elsevier, vol. 110(C).
    13. Philipp Baumann & Enzo Rossi & Michael Schomaker, 2022. "Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Machine learning in central banking, volume 57, Bank for International Settlements.
    14. Öberg, Stefan, 2021. "Treatment for natural experiments: How to improve causal estimates using conceptual definitions and substantive interpretations," SocArXiv pkyue, Center for Open Science.
    15. Dragan Miljkovic & Cole Goetz, 2023. "Futures markets and price stabilisation: An analysis of soybeans markets in North America," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(1), pages 104-117, January.
    16. Su, Zhi & Liu, Peng & Fang, Tong, 2022. "Uncertainty matters in US financial information spillovers: Evidence from a directed acyclic graph approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 229-242.
    17. Markku Maula & Wouter Stam, 2020. "Enhancing Rigor in Quantitative Entrepreneurship Research," Entrepreneurship Theory and Practice, , vol. 44(6), pages 1059-1090, November.
    18. Florian F Gunsilius, 2025. "A primer on optimal transport for causal inference with observational data," Papers 2503.07811, arXiv.org, revised Mar 2025.
    19. Barrera, Emiliano Lopez & Miljkovic, Dragan, 2022. "The link between the two epidemics provides an opportunity to remedy obesity while dealing with Covid-19," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 280-297.
    20. Emmet Hall-Hoffarth, 2022. "Causal Discovery of Macroeconomic State-Space Models," Papers 2204.02374, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pgph00:0002467. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: globalpubhealth (email available below). General contact details of provider: https://journals.plos.org/globalpublichealth .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.