Lessons learned in the conduct, validation, and interpretation of national population based HIV surveys

AIDS. 2005 May;19 Suppl 2:S9-S17. doi: 10.1097/01.aids.0000172872.88347.f3.


In the past few years several countries have conducted national population-based HIV surveys. Survey methods, levels of participation bias from absence or refusal and lessons learned conducting such surveys are compared in four national population surveys: Mali, Kenya, Peru and Zambia. In Mali, Zambia, and Kenya, HIV testing of adult women and men was included in the national-level demographic and health surveys carried out regularly in these countries, whereas in Peru the national HIV survey targeted young people in 24 cities with populations over 50 000.The household response rate was above 90% in all countries, but some individuals were absent for interviews. HIV testing rates were between 70 and 79% of those eligible, with higher test rates for women. Three critical questions in this type of survey need to be answered: who did the surveys miss; how much it matters that they were missed; and what can be done to increase the participation of respondents so the coverage rates are adequate. The level of representativeness of the populations tested was adequate in each survey to provide a reliable national estimate of HIV prevalence that complements other methods of HIV surveillance. Different lessons were learned from each survey. These population-based HIV seroprevalence surveys demonstrate that reliable and useful results can be obtained, although they require careful planning and increased financial and human resource investment to maximize responses at the household and individual level, which are key elements to validate survey results.This review was initiated through an international meeting on 'New strategies for HIV/AIDS Surveillance in Resource-constrained Countries' held in Addis Ababa on 26-30 January 2004 to share and develop recommendations to guide future surveys.

Publication types

  • Review

MeSH terms

  • Africa / epidemiology
  • Data Interpretation, Statistical
  • Female
  • HIV Infections / epidemiology*
  • Health Surveys*
  • Humans
  • Latin America / epidemiology
  • Male
  • Prevalence
  • Reproducibility of Results