Mosquito-borne diseases cause substantial mortality and morbidity worldwide. These impacts are widely predicted to increase as temperatures warm, since mosquito biology and disease ecology are strongly linked to temperature. However, direct evidence linking environmental change to changes in mosquito-borne disease is rare, and the ecological mechanisms that may underpin such changes are poorly understood. Environmental drivers, can have non-linear, opposing impacts on the demographic rates of different mosquito life cycle stages and on disease transmission processes. As such, model frameworks that explicitly incorporate the effects of temperature are required to predict seasonal mosquito abundance and the intensity and persistence of disease transmission under environmental fluctuations. Chapter 2 develops a variable-delay delay differential equation (DDE) model to estimate seasonal abundance of each life stage of the West Nile virus (WNV) vector mosquito species, Cx. pipiens, given temperature and photoperiod conditions experienced. The model highlights that the timing and intensity of warm periods can be more influential in shaping abundance patterns than average temperatures. Chapter 3 presents an extensive body of fieldwork, which led to a high temporal resolution seasonal abundance dataset of each life stage of Cx. pipiens. Chapter 4 challenges assumptions of the DDE model from Chapter 2 in light of the seasonal abundance data collected in Chapter 3. The importance of using appropriate, high temporal resolution input temperature datasets is displayed. Chapter 5 extends the DDE model from Chapter 4 to explicitly model WNV transmission cycles between vectors and avian hosts. The disease model predicts that the current climate in the South of England is too cold to facilitate WNV outbreaks. However, given projected warming in the UK in coming decades it is predicted that WNV infection rates in mosquitoes will be consistent with the lower range of values observed during WNV outbreaks 2080 if virus introduction coincides with warm periods. The risk of these outbreaks is predicted to increase sharply with increases in human greenhouse gas emissions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:726674 |
| Date | January 2017 |
| Creators | Ewing, David |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/8450/ |
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