Backcalculation of HIV Infection Rates


Complete text of article in Statistical Science, 8, 82-119, 1993.


Backcalculation is an important method of reconstructing past rates of human immunodeficiency virus (HIV) infection and for estimating current prevalence of HIV infection and future incidence of acquired immunodeficiency syndrome (AIDS). This paper reviews the backcalculation techniques, focusing on the key assumptions of the method, including the necessary information regarding incubation, reporting delay, and models for the infection curve. A summary is given of the extent to which the appropriate external information is available and whether checks of the relevant assumptions are possible through use of data on AIDS incidence from surveillance systems. A likelihood approach to backcalculation is described and implemented in AIDS incidence data in the United States. New features of the approach include incorporation of seasonal variation in diagnosis rates, smooth nonparametric estimation of both the HIV infections curve and nonstationary aspects of the incubation period and reporting delay distributions, and an analysis of residuals from backcalculation fits. Unexplained lack of fit is examined and discussed. A fundamental concern is the appropriate acknowledgement of uncertainty associated with backcalculation estimates caused by misspecified assumptions and inaccurate external estimates of key components of the technique. Such uncertainly limits the usefulness of backcalculation and highlights the need for complementary approaches.


Disease Modeling | Statistical Methodology | Statistical Theory

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