Mathematical Biology Seminar Jim Clark Duke University Friday Jan. 22, 2010 3:05pm in LCB 215 Inference in incidence, infection, and impact: Co-infection of multiple hosts by multiple pathogens Abstract: Host-specific mortality from natural enemies is one of the most widely tested mechanisms for explaining plant diversity. By disproportionate attack on specific hosts when they become abundant, pathogens might provide an advantage for rare species, thus promoting diversity. We hypothesized that this mechanism can operate not only if there are specific pathogens for each host, but also if co-infection by combinations of pathogens have host-specific effects. Testing this hypothesis requires methods to determine which of the many interactions have quantitative effects on host survival. We present a hierarchical framework for the case where there is detection information based on multiple sources (cultures, gene sequencing, and survival observations), and the inference problem includes not only parameters that describe environmental influences on pathogen incidence, infection, and host survival, but also on latent states themselves - pathogen incidence at a site and infection statuses of hosts. Due to the large size of the model space, we develop a reversible jump Markov chain Monte Carlo approach to select models, estimate posterior distributions, and predict environmental influences on host survival. We demonstrate with application to a data set involving fungal pathogens on tree hosts, where data include host survival and fungal detection using cultures and DNA sequencing. The approach allows us to filter hundreds to thousands of potential host-pathogen interactions down to those few combinations that affect host survival. We show that multi-host fungi have differential effects on survival depending on host identity and that multiple infections can impact survival even when single infections do not. The evidence for a rare species advantage has strong posterior support, despite the fact that infections by individual pathogens have small impact.