Modelling multisera data: The estimation of new joint and conditional epidemiological parameters

Abstract

Testing humans for infectious diseases is often done by assessing the presence or absence of disease-specific antibodies in serum samples. For feasibility and economical reasons, these sera are often tested for more than one antigen. Studying diseases with similar transmission routes can govern new insights for disease dynamics. We use flexible marginal and conditional models to model multisera data on the Varicella-Zoster virus and the Parvo B19-virus in Belgium. Next form the derivation of the age-dependent marginal force of infection (FOI), we introduce new epidemiological parameters: the age-dependent joint and conditional FOI. These parameters allow us to study the association among the occurrence and acquisition of both infections. Furthermore, we show how to test for association and whether the infection-specific age-dependent FOI curves are proportional and consequently whether separable mixing in the population holds. Copyright (C) 2007 John Wiley & Sons, Ltd.