Statistical Analysis of the Time Dependence of HIV Infectivity Based on Partner Study Data


Published in Journal of the American Statistical Association (1991), 87, pp. 360-372.


Statistical analyses of data form studies of Human Immunodeficiency Virus (HIV) transmission in partners of infected individuals often focus on estimation of the per contact probability of virus transmission, or infectivity. Of particular interest is evaluating whether the infectivity changes during the course of a partnership and in identifying factors that influence the infectiousness of the initially infected partner (called the index case) and the susceptibility of the uninfected partner. Estimation and inference are complicated by limitations in partner study data, which may include unknown time of infection for either or both partners, inaccurate or incomplete information on the number and frequency of contacts and uncertain disease status of the index case. Jewell and Shiboski (1990a) developed statistical methods for partner studies in which data is retrospectively ascertained using techniques that rely on knowledge of the numbers of contacts for each partnership. The infectivity was treated as a function of the number of contacts but was assumed not to depend on the length of time of exposure. Here we consider various generalizations of these ideas. In particular, discussion is focused on analysis of data where the (chronological) time of exposure is observed in addition to or rather than the number of contacts and using models that allow variation in the infectivity according to time since infection of the index case. Where possible, methods are illustrated on data sets on heterosexual transmission.


Disease Modeling | Medical Specialties | Statistical Models | Survival Analysis

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