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 huanglongbing (HLB or citrus greening) specifically. I show a trait-based approach that allows data taken on individual vectors to be incorporated into a transmission model. Further, I 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. I show how traits can be used to mechanistically connect external forcing to dynamics and to summaries of transmission intensity, including the basic reproductive number R0.
Results/Conclusions
I use a Bayesian approach to quantify how four traits of the Asian citrus psyllid (the vector that spreads Candidatus Liberibacter asiaticus, the bacterium that causes HLB) depend on temperature. The thermal response of these four traits are incorporated into a dynamical model for the spread of HLB. I also quantify the uncertainty of the traits into R0 and examine how the uncertainty in the values of the traits propagate through the system. I discuss next steps in incorporating correlation between traits and level individual variation into transmission models.