Leah R. Johnson, Virginia Tech

Abstract

Traits of individuals, such as individual susceptibility to infection or behavior that determines contact rates, ultimately drive the observed dynamics of infections in populations. However, these traits are not often included explicitly into the traditional SIR-type models for infection transmission. In this talk I will focus on vector-borne infections generally, and on dengue specifically. I show a trait-based approach that allows data taken on individual vectors to be incorporated into a transmission model at the population level without explicitly modeling individuals. Further, we allow vector traits to depend on an environmental driver, specifically temperature. Most disease vectors are small arthropods, their life history process are very sensitive to temperature. We use a Bayesian approach to quantify how traits of the Aedes species mosquitoes depend on temperature. The thermal responses of these traits are incorporated into a dynamical model for the spread of dengue which is, summarized by a summary of the system based on the basic reproductive number R0. We also quantify the uncertainty of the traits and propagate this into uncertainty in R0. We validate this model using observed case data, and then explore predictions for global suitability for transmission both now and in the face of climate change.