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Title: Epidemiological dynamics of Mycobacterium bovis and population suppression in badgers (Meles meles)
Author: Beckley, Nicholas
ISNI:       0000 0004 6420 9196
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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Bovine TB in cattle is a major economic problem in the UK, costing the government approximately £100m a year. Badgers are a wildlife host of the infection that causes bovine TB, and there is strong evidence that they transmit the infection to cattle. Understanding the ecology and epidemiology of infected badger populations is therefore crucial for implementing disease management strategies relating to badgers. Genetic and phenotypic data of badgers captured during a large-scale field trial of repeated, widespread badger culls were used to assess the importance of parental roles on the impacts of badger culling. Further ecological and epidemiological dynamics were investigated through developing a stochastic simulation model of an infected badger population. An estimated 72.8% of badgers were captured during initial culls of the trial, and an estimated 57.8% during follow-up culls, based on badger parentage assignments. Further analyses of these parentage assignments revealed evidence of a genetic predisposition in infection susceptibility from parents to cubs, but no evidence of a significant infection transmission route from mothers to their young, dependent cubs. There was also no evidence that badger welfare was compromised during the trial through not capturing dependent cubs of culled mothers. Analysis of a simulation model found that moderate levels of disease-induced mortality in an infected badger population could significantly reduce the size of badger social groups with a higher prevalence of infection. The impact of these findings relating to potential disease management strategies is discussed, together with suggested directions for future research.
Supervisor: Donnelly, Christl Sponsor: Natural Environment Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral