Eco-evolutionary modelling of infectious disease and host resistance
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In this work we take an evolutionary invasion analysis approach to modelling evolution and use it to describe the selection pressures underlying epidemiological traits in natural host populations harboring endemic infections. Throughout this work a logistic form for host-birth rate allows for disease dependent population dynamics so that the detrimental e ects of infection can be modelled and we also consider the more neglected detrimental e ect whereby infection is linked to infertility. To begin with we give a theoretical introduction to the framework of adaptive dynamics and illustrate it through the established example of the evolution of parasite virulence. We then extend the results to account for condition dependent virulence which is an interaction between host condition (i.e. host stress) and virulence, that has recently generated much attention from empiricists. Many natural systems are seasonal, potentially leading to seasonal stress, and we show how to conduct a study for seasonal host populations and analyse its role in the evolution of density dependent virulence. We then turn our attention to the evolution of resistance beginning with a perspective on the relationship between investment in acquired immunity and the lifespan of hosts and parasites. In our penultimate chapter we derive explicit expressions for optimal investment in the various modes of resistance for a range of epidemiological scenarios. These expressions are then key to understanding our nal chapter where we elaborate further on the established theory by allowing for parasite diversity. The nal chapter highlights the central role played by speci city in the evolution of host defence. Since our approach throughout has been to build complexity onto a baseline model we conclude our discussion with a short section interpreting established results on the coevolution of virulence and resistance from the perspective of our results on the evolution of virulence and resistance.