DISSERTATION RESEARCH: Epidemiology meets symbiosis: modeling symbiont spread through multi-host communities

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Most new infectious diseases in humans are zoonotic, which means the pathogens that cause these diseases originate in wild and domestic animals and then spread to humans. Many pathogens that infect livestock and wildlife species are also found in other species. Mathematical models that describe pathogen transmission within single wildlife host species (e.g., rabies transmission within bat populations) and between different host species (e.g., rabies transmission between bats and skunks) are critical tools for understanding and predicting disease outbreaks in humans, livestock, and wildlife. In addition to being used to understand the spread of pathogens among hosts, these same models can be used to understand the spread of beneficial symbionts (small organisms such as bacteria that live in much larger hosts) that help rather than harm the host. However, the fundamental assumptions that underlie these mathematical models are rarely tested, because observing animal contact rates and spread of disease in nature is difficult. This research will use a system of hosts and their symbionts to test assumptions on which the existing models are built, and will quantify how well those models can predict disease transmission in wildlife populations. The results of this research will ultimately lead to mathematical models that are better at predicting symbiont transmission. Wildlife population densities often vary across space and time. Classic epidemiological models use one of two mechanistic transmission functions to describe the relationship between host density and pathogen transmission rates. The first assumes that animal contact rates and thus transmission rates increase linearly with host density (density-dependent transmission), and the second assumes that animal contact rates and transmission rates are not affected by host density (frequency-dependent transmission). However, nonlinear relationships that fall somewhere between those extremes may be more appropriate in many host-symbiont systems. Using an experimentally tractable multi-host system - symbiotic annelid worms living on freshwater snails - this research will: (1) empirically quantify the relationship between host density and both intra- and inter-specific host contact rates, and (2) use the resulting model to make and test predictions regarding symbiont transmission dynamics in single and multi-host host communities at broad spatial and temporal scales in natural systems. Critical evaluation of fundamental model assumptions and the resulting model predictions will lead to better predictive models of symbiont transmission.