Data from: The effects of the avoidance of infectious hosts on infection risk in an insect-pathogen interaction

In many animal host-pathogen interactions, uninfected hosts either avoid or are attracted to infected conspecifics, but understanding how such behaviors affect infection risk is difficult. In experiments, behaviors are often eliminated entirely, which allows demonstration that a behavior affects risk but makes it impossible to quantify effects of individual behaviors. In models, host behaviors have been studied using ordinary differential equations, which can be easily analyzed but cannot be used to relate individual behaviors to risk. For many insect baculoviruses, however, quantifying effects of behavior on risk is straightforward because transmission occurs when host larvae accidentally consume virus-contaminated foliage. Moreover, increases in computing power have made it possible to fit complex models to data. We therefore used experiments to quantify the behavior of gypsy moth larvae feeding on oak leaves contaminated with virus-infected cadavers, and we tested for effects of cadaver-avoidance behavior by fitting stochastic simulation models to our data. The models that best explain the data include cadaver avoidance, and comparison of models that do and do not include cadaver avoidance shows that this behavior substantially reduces infection risk. Our work demonstrates that host behaviors that affect exposure risk play a key role in baculovirus transmission and adds to the growing consensus that host behavior can strongly alter pathogen transmission rates.