In order to predict and control the spread of infectious diseases, it is important to understand the role of "superspreaders". These are hosts who transmit disease more often than most other infected individuals. To understand superspreaders this project will investigate how immunity to infections, host diet, and whether or not the host is infected with other parasites creates variation among individuals in susceptibility to pathogens and the ability to transmit infections. To do so, this project will develop mathematical frameworks of virus spread, to predict how food resources and infection with a parasite will first shape the risk that an individual will become infected, and then, will shape the spread of disease across populations and landscapes. These predictions will be tested using laboratory and field experiments with bank voles infected with Puumala hantavirus. The results of this project will shed new light on why some individuals become superspreaders and others do not. This has relevance to improving surveillance and management of this hantavirus, which regularly spills over from its vole reservoir host to infect humans, as well to other pathogens of concern to human and agricultural health. The project will also support the training of high school science teachers from across the United States, providing them with a hands-on research experience in Finland. This will equip them with activities and materials to use to teach high school students about the importance of emerging infectious diseases.
This research will examine the individual and synergistic effects of habitat quality and helminth coinfection on wild bank voles infected with the zoonotic pathogen, Puumala hantavirus. The project will develop novel mathematical theory to mechanistically link diet and coinfection with pathogen transmission to predict how bottom-up (diet-driven) and top-down (coinfection-driven) processes interact to drive the emergence of superspreaders, and how this individual-level variation scales up to influence pathogen transmission at the population- and landscape-level. These predictions will be tested using both laboratory vole infection experiments and powerful manipulative experiments involving supplemental feeding and de-worming treatments of wild vole populations in forests. By concurrently developing mathematical models and integrating them with empirical data, this project will quantify how habitat and coinfection influence (1) individual host competence for microparasite infection, (2) demographic and contact processes governing local transmission and (3) dispersal rates and landscape attributes that determine spatial spread of disease.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
