Statistical Analysis of HIV Infectivity Based on Partner Studies
The full text of this version of the working paper is not currently available online.
Published in Biometrics (December, 1990), 46, pp. 1133-1150.
Abstract:
Partner studies produce data on the infection status of partners of individuals known or assumed to be infected with the human immunodeficiency virus (HIV) after a known or estimated number of contacts. Previous studies have assumed a constant probability of transmission (infectivity) of the virus at each contact. Recently, interest has focused on the possibility of heterogeneity of infectivity across partnerships. This paper develops parametric and nonparametric procedures based on partner data in order to examine the risk of infection after a given number of contacts. Graphical methods and inference techniques are presented that allow the investigator to evaluate the constant infectivity model and consider the impact of heterogeneity of infectivity, error in measurement of the number of contacts, and regression effects of other covariates. The majority of the methods can be computationally implemented easily with use of software to fit generalized linear models. The concepts and techniques are closely related to ideas from discrete survival analysis. A data set on heterosexual transmisison is used to illustrate the methods.
Subject Area:
Disease Modeling, Statistical Models, Survival Analysis
Suggested Citation:
Nicholas P. Jewell and Stephen C. Shiboski, "Statistical Analysis of HIV Infectivity Based on Partner Studies" (April 1989). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 1.
http://www.bepress.com/ucbbiostat/paper1