JSM 2004 - Toronto

Abstract #300504

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Activity Number: 87
Type: Contributed
Date/Time: Monday, August 9, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract - #300504
Title: Bayesian Hierarchical Models for Estimating Vaccine Efficacy on Susceptibility and Infectiousness
Author(s): Xiaohong M. Davis*+ and Michael J. Haber and Lance A. Waller
Companies: Centers for Disease Control and Prevention and Emory University and Emory University
Address: 4770 Buford Hwy. NE, Atlanta, GA, 30341,
Keywords: vaccine efficacy ; vaccine efficacy for susceptibility ; vaccine efficacy for infectiousness ; Bayesian hierarchical models ; household random effect
Abstract:

Likelihood methods have been used to estimate vaccine efficacy on susceptibility (VES) and on infectiousness (VEI) from household data assuming fixed transmission probabilities and vaccine effects. In real disease epidemic, the transmission probabilities and vaccine effects may not be the same across households, communities or even individuals. We propose Bayesian hierarchical models for estimating VES and VEI using final size (outbreak) data from a household study. Our method allows for both between- and within-household heterogeneities in transmission probabilities due to random effects at both household and individual level. We performed extensive Markov chain Monte Carlo (MCMC) simulations to evaluate the performance of the estimators of VES and VEI for different models and vaccination designs.

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