The Demographic and Health Surveys project (MEASURE DHS) has been conducting surveys in Africa, Asia, Latin America, and Eastern Europe since 1984. DHS has earned a worldwide reputation for collecting and disseminating accurate, nationally representative data on fertility, family planning, maternal and child health, child survival, malaria, nutrition and HIV/AIDS. DHS household surveys typically interview a nationally representative sample of over 10,000 women and men age 15-49. In recent years, blood tests have been added to the verbal interview to test for various health conditions, including anemia, and more recently, malaria and HIV. MEASURE DHS is implemented by Macro International, Inc based in Calverton, Maryland, and is funded by the United States Agency for International Development (USAID) and the President's Emergency Plan for AIDS Relief (PEPFAR). Individual surveys also receive funding from national governments, as well as multilateral and bilateral donors.

This report summarizes the HIV prevalence estimates provided in MEASURE Demographic and Helath Surveys. The MEASURE DHS project is implemented by ICF Macro, and ICF International Company, and funded by the United States Agency for International Development (USAID).

The overall effect of non response biases on national HIV estimates tends to be small and remains inferior to sample variations. If adjustments need to be interpreted with caution due to the limited information available to predict the prevalence of non tested people, we can conclude that national population-based surveys can provide quality and representative national HIV prevalence estimates.

The DHS Program has supported the conduct of numerous large-scale HIV seroprevalence surveys. Some of these surveys used a testing strategy based on enzyme-immunoassays (EIA) and recent concerns were raised that this algorithm could have led to overestimation of HIV prevalence. The present report investigated the impact of potential misclassification of samples on HIV prevalence estimates for 23 surveys conducted from 2010-2014. Along with visual inspection of laboratory results, we examined how accounting for potential misclassification of HIV status through Bayesian latent class models affected prevalence estimates. Two types of Bayesian models were specified: one that only uses the individual dichotomous test results and a continuous model that makes use of the quantitative information of the EIA (i.e., their signal-to-cutoff values). Overall, we found that adjusted prevalence estimates roughly matched the surveys’ original results, with overlapping uncertainty intervals, suggesting that misclassification of HIV status should not affect prevalence estimates in most surveys. Our analyses did, however, suggest that two surveys may be problematic; the Uganda AIDS Indicator Survey 2011 and the Zambia Demographic and Health Survey 2013-14, where prevalence could have been overestimated - the magnitude of which remains difficult to ascertain. Interpreting results from the Uganda survey is made difficult by the lack of internal quality control and potential violation of the multivariate normality assumption of the continuous Bayesian latent class model. In conclusion, despite limitations of our latent class models, our analyses suggest that prevalence estimates from most reviewed surveys are not overwhelmingly affected by sample misclassification.

Sub-national estimates of HIV prevalence can inform the design of policy responses to the HIV epidemic. Such responses also benefit from a better understanding of the correlates of HIV status, including the association between HIV and geographical characteristics of localities. In recent years, several countries in Africa have implemented household surveys (such as Demographic and Health Surveys) that include HIV testing of the adult population, providing estimates of HIV prevalence rates at the sub-national level. These surveys are known to suffer from non-response bias, but are nonetheless thought to represent a marked improvement over alternatives such as sentinel surveys. At present, however, most countries are not in a position to regularly field such household surveys. This paper proposes a new approach to the estimation of HIV prevalence for relatively small geographic areas in settings where national population-based surveys of prevalence are not available. The proposed approach aims to overcome some of the difficulties with prevailing methods of deriving HIV prevalence estimates (at both national and sub-national levels) directly from sentinel surveys. The paper also outlines some of the limitations of the proposed approach.