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Estimating HIV Prevalence and Incidence in Africa from Mortality Data

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  • Oster Emily

    (The University of Chicago Booth School of Business)

Abstract

An estimated 33 million people are infected with the HIV virus, with 67% of them in Sub-Saharan Africa. Despite this, knowledge about HIV prevalence in Africa is limited and imperfect. Although population-based testing in recent years has provided reliable information about current prevalence in the general population, we have little reliable data on prevalence in early years of the epidemic. This paper suggests a new methodology for estimating HIV prevalence and incidence using inference from mortality data. This methodology can be used to generate prevalence estimates from early in the epidemic. This information is valuable for understanding how the epidemic has evolved over time and is also likely to be helpful in analyses that explore how policy affects the epidemic or how HIV affects other country-level outcomes.

Suggested Citation

  • Oster Emily, 2010. "Estimating HIV Prevalence and Incidence in Africa from Mortality Data," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-46, September.
    • Handle: RePEc:bpj:bejeap:v:10:y:2010:i:1:n:80
    DOI: 10.2202/1935-1682.2602
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    References listed on IDEAS

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    1. Emmanuela Gakidou & Gary King, 2006. "Death by survey: Estimating adult mortality without selection bias from sibling survival data," Demography, Springer;Population Association of America (PAA), vol. 43(3), pages 569-585, August.
    2. Ian Timæus & Momodou Jasseh, 2004. "Adult mortality in sub-Saharan Africa: Evidence from demographic and health surveys," Demography, Springer;Population Association of America (PAA), vol. 41(4), pages 757-772, November.
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    Cited by:

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    2. Oster, Emily, 2012. "HIV and sexual behavior change: Why not Africa?," Journal of Health Economics, Elsevier, vol. 31(1), pages 35-49.
    3. Kudo, Yuya, 2014. "Religion and polygamy : evidence from the livingstonia mission in Malawi," IDE Discussion Papers 477, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    4. Belgi Turan, 2020. "Life expectancy and economic development: Evidence from microdata," Review of Development Economics, Wiley Blackwell, vol. 24(3), pages 949-972, August.
    5. Anne Case & Christina Paxson, 2011. "The Impact of the AIDS Pandemic on Health Services in Africa: Evidence from Demographic and Health Surveys," Demography, Springer;Population Association of America (PAA), vol. 48(2), pages 675-697, May.
    6. Omar Mahmoud, Toman & Thiele, Rainer, 2013. "Does Prime-Age Mortality Reduce Per-Capita Household Income? Evidence from Rural Zambia," World Development, Elsevier, vol. 45(C), pages 51-62.
    7. Dick Durevall & Annika Lindskog, 2016. "Adult Mortality, AIDS, and Fertility in Rural Malawi," The Developing Economies, Institute of Developing Economies, vol. 54(3), pages 215-242, September.
    8. TENIKUE Michel & TEQUAME Miron, 2018. "Economic and Health Impacts of the 2011 Post-Electoral Crisis in Côte d’Ivoire: Evidence from Microdata," LISER Working Paper Series 2018-03, Luxembourg Institute of Socio-Economic Research (LISER).

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    Keywords

    HIV; Africa; mortality inference;
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