Outbreaks of infectious disease affect host populations, ecological communities, the structure and function of natural and managed ecosystems, and global public health. Anticipating and controlling outbreaks requires a strong understanding of the individual-level traits of hosts and parasites. However, classic management strategies and models often assume that the traits of hosts and parasites are fixed, which implies that reductions in the densities of infected hosts or vectors should consistently reduce parasite transmission. Using a case study of human schistosomes and their intermediate host snails, I will illustrate how important individual-level traits are driven by underlying physiology (bioenergetics) and environmental conditions (resource availability, variability, and competition) by building bioenergetic models of infection and parameterizing them with a series of experiments that vary resource supply and competition at the individual and population levels.
Results/Conclusions
Resource supply rates, periodic starvation, and competition drive dynamic responses in individual-level infection dynamics. Specifically, low resource supply, long starvation periods, and intense competition all reduced the virulence and productivity of schistosome infections, consistent with predictions from the bioenergetics models. Once scaled up to the population level via individual-based modeling (IBM), these dynamic trait changes yield three important consequences: (1) they sever the relationship between infected host density and transmission potential, (2) they facilitate brief periods of extreme human exposure risk during phases of snail population growth, and (3) they highlight conditions under which snail reduction can backfire, elevating human risk of exposure to schistosomes. Experimental epidemics with snail populations yielded strong evidence for the first two IBM predictions. Field evaluations of these predictions could improve human schistosomiasis control strategies. Ultimately, an energetic perspective on host-parasite interactions could greatly improve prediction and control of infectious disease in a variety of systems.