Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.762583
Title: Mathematical models of stress and epidemiology
Author: Booton, Ross D.
ISNI:       0000 0004 7657 4481
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2018
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
This thesis is concerned with using mathematical models to investigate the impacts of stress and epidemiology on ecological frameworks. First we focus on the effects of stress on honey bee colony decline. We establish a mathematical model to describe the regulatory processes governing the hive and general stressors impacting the colony. We analyse this model in order to understand how these regulatory processes counteract stressors and find that increasing a density-dependent Allee stressor effect can cause sudden and unexpected dynamical changes in behaviour. Our second study examines honey bee hive infection with multiple routes of transmission. We study a mathematical model of infection with multiple transmission routes in order to understand how these routes can impact the spread of disease within a colony. We use published data taken from the literature and examine the respective contributions to total disease burden by each route. We demonstrate the presence of a synergistic interaction between both infection pathways compared to each infection route acting alone. Our third study examines the interaction between two interacting stressors. Toxicant stress can have both immunosuppressive and lethal direct effects on non-target organisms. We study a model which describes the within-host processes of cellular health, infection and immunity and analyse this model under the effects of increasing toxicant stress. We show that sublethal toxicant stress can promote within-host infection and that this infection is maximised by an intermediate level of toxicant, rather than linearly increasing as the toxicant load is increased. We expand upon this within-host framework to include population level processes. We do this since infection not only spreads within the host organism but also spreads between those individuals within a population. We formulate a nested model to describe the within-host processes and the between-host epidemiological dynamics under stress to understand how toxicants impact the spread of population-level disease. We show that infection outbreak at the population level is determined by the interaction with stress and that the epidemic is maximised by an intermediate level of toxicant. Finally we summarise the findings of this thesis and discuss potential future avenues for research.
Supervisor: Childs, Dylan Z. ; Marshall, James A. R. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.762583  DOI: Not available
Share: