Tick-borne diseases are an increasing global public health concern due to an expanding geographical range and increase in abundance of tick-borne infectious agents. A potential explanation for the rising impact of tick-borne diseases is an increase in tick abundance which may be linked to an increase in density of the hosts on which they feed. In this study, we develop a model framework to understand the link between host density, tick demography and tick-borne pathogen epidemiology. Our model links the development of specific tick stages to the specific hosts on which they feed.We show that host community composition and host density have an impact on tick population dynamics and that this has a consequent impact on host and tick epidemiological dynamics. A key result is that our model framework can exhibit variation in host infection prevalence for a fixed density of one host type due to changes in density of other host types that support different tick life stages. Our findings suggest that host community composition may play a crucial role in explaining the variation in prevalence of tick-borne infections in hosts observed in the field.

A more theoretical topic in that we explore the effect of different model frameworks, specifically the influence of latent and chronic infection, on the persistence of infection in a population. A suite of stochastic continuous-time Markov chain models are used to determine the mean time to pathogen extinction, with parameter sensitivity also undertaken to see impact of varying parameter values. This work has wide ranging impacts as each model can be applied to an assortment of infections seen globally.