COS 229-4 - Theoretical and empirical impacts of short-term thermal variability on endemic infection prevalence of an environmentally-transmitted disease

Abstract: Climate change has profound effects on infectious disease dynamics, yet the impacts of increased short-term temperature fluctuations on disease spread remain poorly understood. Using replicated experimental epidemics in a Daphnia-microparasite system, the goal of our study was to empirically test the theoretical prediction that temperature variability should suppress endemic infection prevalence at the pathogen’s thermal optimum. This theoretical prediction arises from two distinct models. The first modelling approach numerically estimates endemic infection prevalence using hierarchical simulations of a standard disease transmission model where parameters for host and parasite traits are functions of temperature based on the Metabolic Theory of Ecology. The second approach calculates endemic prevalence by averaging a nonlinear thermal response curve for endemic prevalence over a stochastic thermal distribution. To test these theoretical frameworks, we held replicated Daphnia populations in constant and variable thermal treatments. Populations in the variable treatment each received a unique sequence of daily temperature changes. All populations were initially susceptible and the disease was introduced over the course of the experiment at a low rate. Every third day, Daphnia hosts were sampled from each population and their infection status (presence of infection, infection burden) was determined under a microscope. Repeating this sampling process across all replicate populations for 228 days allowed us to estimate endemic infection prevalence as the proportion of infected hosts during the endemic phase of the epidemic in constant and thermally variable environments.

In contrast to theoretical predictions, our experimental study revealed that short-term thermal variability had a positive, rather than negative, effect on endemic infection prevalence. Additionally, this discrepancy between theoretical predictions and experimental results could not be resolved by accounting for host and parasite acclimation responses to changing temperatures in the hierarchical disease transmission model. The empirical data indicate that a decrease in the among-host variance of infection burden is associated with the positive effect of temperature variability on endemic infection prevalence. This implies that temperature variability may be operating through mechanisms that scale from within- to among-host transmission dynamics. In conclusion, this study suggests that predictive frameworks aimed at modelling the effects of short-term thermal variability on epidemiological and ecological dynamics may require a multi-scale approach that explicitly models the interdependence of biological processes across scales.