A Markov model for measuring vaccine efficacy for both susceptibility to infection and reduction in infectiousness for prophylactic HIV vaccines

We use a discrete-time non-homogeneous Markov chain to model data from augm ented human immunodeficiency virus (HIV) vaccine trials. For this design, t he study population consists of primary participants some of whom have stea dy sexual partners who are also enrolled to augment the trial. The state sp ace consists of the infection status of primary participants without steady partners and the infection status of both persons in the steady partnershi ps. The transition probabilities are functions of the two parameters: vacci ne efficacy for susceptibility (VEs) and infectiousness (VEI). We use likel ihood methods to estimate VEs and VEI from time-to-event data. We then use stochastic simulations to explore the bias and precision of the estimators under various plausible conditions for HIV vaccine trials. We show that bot h the VEs and VEI are estimable with reasonable precision for the condition s that may exist for planned HIV vaccine trials. We show that exams conduct ed every six months will likely provide sufficient information to estimate the VE parameters accurately, and that there is little gain in precision fo r more frequent exams. Finally, we show that joint estimation of the VEs an d VEI will likely be feasible in a currently planned HIV vaccine trial amon g injecting drug users in Bangkok, Thailand, if one augments the informatio n about the primary participants in the trial with information about their steady sexual partners. Copyright (C) 1999 John Wiley & Sons Ltd.