Abstract #300761

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JSM 2003 Abstract #300761
Activity Number: 53
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 4:00 PM to 5:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #300761
Title: Estimating Heterogeneous Transmission with Multiple Infectives Using MCMC Methods
Author(s): Haitao Chu*+ and Marie-Pierre Preziosi and M. Elizabeth Halloran
Companies: Johns Hopkins University and Emory University and Emory University
Address: Bloomberg School of Public Health Dept. of Epidemiology, Baltimore, MD, 21205,
Keywords: transmission probability ; adaptive rejection metropolis sampling ; multiple infectives ; Markov chain Monte Carlo methods ; vaccine efficacy ; Gibbs sampling
Abstract:

We develop a general procedure for estimating the transmission probability, adjusting for covariates when susceptibles are exposed to several infectives concurrently and taking correlation within transmission units into account.The procedure is motivated by a study estimating efficacy of pertussis vaccination based on the secondary attack rate in a rural sub-Saharan community and illustrated with simulations. The procedure is also appropriate to estimate the pairwise transmission probability in transmission studies of live vaccine virus in a collection of transmission units, such as daycare centers or retirement centers. Previously, analyses either excluded transmission units with multiple infectives or ignored co-infectives. Excluding transmission units with multiple infectives is statistically less efficient, and ignoring co-infectives can lead to biased estimation. Modeling is carried out by regressing the latent pairwise transmission probability from each infective to a susceptible on covariates and specifying a transmission linkage function linking the latent pairwise transmission probability to the overall transmission probability. Parameters are estimated using MCMC methods.

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