Journal of Population Economics

, Volume 20, Issue 2, pp 383–422 | Cite as

Changes in HIV/AIDS knowledge and testing behavior in Africa: how much and for whom?

  • Peter GlickEmail author
  • David E. Sahn
Original Paper


Demographic and Health Survey data from nine African countries make it clear that HIV/AIDS prevention knowledge has been increasing. Still, in many cases, fewer than half of adult respondents can identify specific prevention behaviors. Knowledge is lowest in rural areas and among women. HIV testing generally remains rare but is highly variable across countries, likely reflecting differences in the supply of testing services. In most cases, schooling and wealth impacts on prevention knowledge have either been stable or have increased; hence, in the majority of contexts, initial disparities in knowledge by education and wealth levels have persisted or widened.


Africa AIDS Demographic and health surveys 

JEL Classification

I12 J13 O55 



We would like to acknowledge the helpful comments of two anonymous referees.


  1. Blanc AK (2000) The relationship between sexual behavior and level of education in developing countries. Report prepared for UNAIDSGoogle Scholar
  2. Becker G (1993) Human capital: a theoretical and empirical analysis with special reference to education, 3rd edn. The University of Chicago PressGoogle Scholar
  3. Carael M (1995) Sexual behavior and AIDS in the developing world. In: Cleland J, Ferry B (eds) London: Taylor and FrancisGoogle Scholar
  4. de Walque D (2004) How does the impact of an HIV/AIDS information campaign vary with educational attainment? Evidence from rural uganda. Policy Research Working Paper WPS3289. World BankGoogle Scholar
  5. Filmer D (1998) The socioeconomic correlates of sexual behavior: a summary of results from an analysis of DHS data. In: Ainsworth M, Fransen L, Over M (eds) Confronting AIDS: evidence from the developing world, selected background papers for the World Bank Policy Research Report, Confronting AIDS: public priorities in a global epidemicGoogle Scholar
  6. Fylkesnes K, Siziya SA (2004) A randomised trial on acceptability of voluntary HIV counselling and testing. Trop Med Int Health 9(5):566–572(7)CrossRefGoogle Scholar
  7. Gersovitz M (2001) The African HIV epidemic as seen through the Demographic and Health Surveys. Report for the CSAE Conference, Oxford University, 4/9-10/00Google Scholar
  8. Glick P (2005) Scaling up HIV voluntary counseling and testing in Africa: what can evaluation studies tell us about potential prevention impacts? Eval Rev 29(4):331–357CrossRefGoogle Scholar
  9. Glick P, Sahn DE (2005) Are Africans practicing safer sex: evidence from demographic and health surveys for eight countries. Cornell University. ( wp193)
  10. Glick P, Randriamamonjy J, Sahn D (2004) Determinants of HIV knowledge and behavior of women in Madagascar: an analysis using matched household and community data. Cornell University ( wp193)
  11. Gwatkin DR, Deveshwar-Bahl G (2001) Inequalities in knowledge of HIV/AIDS prevention: an overview of socio-economic and gender differentials in developing countries. World Bank. Study for the Population Services InternationalGoogle Scholar
  12. Konde-Lule JK (1995) The declining HIV Seroprevalence in Uganda: What evidence? Health Transition Rev 5 (supplement:27–33)Google Scholar
  13. Lanjouw P, Ravallion M (1999) Benefit incidence, public spending reforms, and the timing of program capture. The World Bank Economic Review 13:257–273Google Scholar
  14. Lawrence E (1991) Poverty and the rate of time preference: evidence from panel data. J Polit Econ 99(3):54–77, Macro International (2004) Demographic and Health Surveys. (
  15. Parkhurst JO (2002) The Ugandan success story? Evidence and claims of HIV-1 prevention. Lancet 360:78–80CrossRefGoogle Scholar
  16. Randriamamonjy J, Sahn D (2004) Determinants of HIV knowledge and behavior of women in Madagascar: an analysis using matched household and community data. Cornell University Food and Nutrition Policy Program Working Paper 168. Cornell University. ( wp168)
  17. Sahn DE, Stifel DC (2003) Exploring alternative measures of welfare in the absence of expenditure data. Rev Income Wealth 49(4):463–489CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Cornell UniversityIthacaUSA
  2. 2.Cornell UniversityIthacaUSA

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