Estimating the size of populations at high risk for HIV using respondent-driven sampling data.

ABSTRACT: The study of hard-to-reach populations presents significant challenges. Typically, a sampling frame is not available, and population members are difficult to identify or recruit from broader sampling frames. This is especially true of populations at high risk for HIV/AIDS. Respondent-driven sampling (RDS) is often used in such settings with the primary goal of estimating the prevalence of infection. In such populations, the number of people at risk for infection and the number of people infected are of fundamental importance. This article presents a case-study of the estimation of the size of the hard-to-reach population based on data collected through RDS. We study two populations of female sex workers and men-who-have-sex-with-men in El Salvador. The approach is Bayesian and we consider

SUBMITTER: Handcock MS 

PROVIDER: S-EPMC4418439 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature