Predicting disease dynamics and human infection risk from wildlife requires a strong understanding of the traits of hosts and parasites. However, hosts and parasites are not uniform entities that exist in constant environments. Instead, organisms can vary dramatically and the environment is heterogeneous across space and time. Here we develop a framework that integrates the intrinsic traits of hosts and parasites (e.g., body size and underlying physiology) with the influence of external factors (e.g., resource availability) to mechanistically predict infection dynamics for individual hosts. Specifically, we built a model based on Dynamic Energy Budget (DEB) theory with a parasite that (1) consumes host resources, (2) interferes with the host’s allocation to somatic and reproductive processes, and (3) produces and releases infectious propagules. We then parameterized the model with a life table experiment using the major human parasite Schistosoma mansoni and its intermediate snail host, Biomphalaria glabrata across a 24-fold gradient of resource density (Experiment 1). We then validated the model by simulating infection dynamics for individual hosts experiencing different levels of intraspecific competition and comparing these predictions to the results of another life table experiment that manipulated the density of conspecifics competing with a focal host (Experiment 2).
Results/Conclusions
In experiment 1, resource availability profoundly affected all host and parasite traits. For example, reproduction for uninfected hosts increased ~5000-fold. Similarly, production of human-infectious cercariae by snails increased ~60-fold across the resource gradient. The DEB model explained an enormous amount of the variation in life history and infection dynamics across the resource gradient. The parameterized model predicted a strong negative effect of conspecific density on host growth and reproduction as well as parasite production. Experiment 2 confirmed these predictions, highlighting the influence of resource competition among hosts for the expression of critical epidemiological traits. Ultimately, a bioenergetics perspective that successfully explains individual infection dynamics could more deeply integrate consumer-resource and infectious disease ecology, enhance predictions for epidemiological dynamics and human risk in heterogeneous environments, and identify novel control strategies for infectious disease in natural populations.