Joint Modelling of Recurrent Infections and Antibody Response by Bayesian Data Augmentation

A joint dynamic model for the interdependence between infection, immunity and risk of disease is presented. Recurrent latent infections are modelled as realizations from a renewal process and antibody dynamics as a diffusion with a decreasing drift modified by the stimulating effect of the random infections. The augmented submodels are estimated simultaneously in one large Markov chain Monte Carlo algorithm. As an example, we consider the risk of recurrent ear infections when having only partially observed information on bacterial carriage and antibody concentrations. Copyright 2003 Board of the Foundation of the Scandinavian Journal of Statistics..