Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article


Doctor of Philosophy


Applied Mathematics


Wild, Geoff


How will hosts and pathogens coevolve in response to multiple types of hosts? I study this question from three different perspectives. First, I model a scenario in which hosts are categorized as female or male. Hosts invest resources in maintaining their immune system at a cost to their reproductive success, while pathogens face a trade-off between transmission and duration of infection. Importantly, female hosts are also able to vertically transmit an infection to their newborn offspring. The main result is that as the rate of vertical transmission increases, female hosts will have a greater incentive to pay the cost to invest in their immune system, while the pathogen will evolve a lower rate of disease-induced mortality in female hosts relative to male hosts. Second, I study a model where hosts can change their type. Hosts are classified according to whether they engage or do not engage in prophylactic behaviours that reduce the transmission rate of an infectious disease and may freely start or stop these behaviours. I study the evolution of the degree to which the pathogen exploits its host’s resources. The main result is that, when hosts engage in prophylaxis, I expect pathogens to evolve a lower level of host exploitation than would otherwise be predicted in the absence of prophylactic behaviours. Finally, I consider the possibility of multiple pathogen strains in addition to multiple types of hosts. I develop a general theoretical framework to link ideas from evolutionary epidemiology to those from kin selection theory to study the evolution of coinfecting pathogen strains. The main result is that pathogens will evolve to balance both the direct and indirect benefits of increased transmission with the associated direct and indirect costs of decreased duration of infection within each type of host. The more genetically related is a pathogen strain to its coinfecting group, the more it will reduce its own disease-induced mortality rate for the benefit of the whole group. Overall, this work shows how standard results from evolutionary epidemiology change when considering the coevolution of hosts and pathogens in the presence of multiple types of hosts.

Summary for Lay Audience

Pathogens and their hosts evolve over time. Researchers build mathematical models to study this evolution and make predictions about the long-term behaviour of host-pathogen systems. A great deal of work has been done to understand the forces that shape the evolution of pathogens and the degree to which they harm their hosts. Other researchers have studied how hosts and pathogens evolve together, as changes in one group will affect the other group. They have shown that considering the evolution of both groups simultaneously allows us to make new and different predictions than if we consider only the evolution of one group. An area of interest which has received less attention is how hosts and pathogens evolve together when the host population is subdivided into different types. Host populations often have defining characteristics, such as sex or age, that can be used to distinguish subgroups within that population. Empirical evidence has shown that pathogens faced with these different types of hosts can evolve to behave differently in one type of host than in the other, and that this will, in turn, affect the evolution of the hosts themselves. This thesis addresses this area of research by building mathematical models and drawing predictions on how we expect hosts and pathogens to evolve when hosts are grouped into different types. I show that the evolution of hosts and pathogens together and the existence of different types of hosts are important features that can generate new evolutionary predictions, which can be used to help explain some of the trends observed in real host-pathogen systems.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License