Abstract

The prevalence of human immunodeficiency virus (HIV) infection can be estimated by two distinct methods. One method, back-calculation, is a complex statistical procedure that estimates the HIV epidemic curve. The second method is based on data from population-based surveys, which provide estimates of the proportion of persons infected with HIV within subgroups, and on the known or estimated population totals for these subgroups. Estimates from these methods are subject to substantial uncertainty and bias, both of which are difficult to quantify. We review recent use of these procedures to estimate HIV prevalence in the United States of America. We also summarize new data on the uncertainty and the bias in these estimates. Reliable estimates of HIV prevalence can be made only by synthesizing estimates from several procedures and by a comprehensive evaluation of relevant data. Future estimates of HIV prevalence will require modifications of these methods or the development of new methods.

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