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Details of Award

NERC Reference : NE/M010260/1

Integrated modelling of demography, transmission and epidemiology of bovine tuberculosis in badgers

Training Grant Award

Lead Supervisor:
Professor DJ Hodgson, University of Exeter, Biosciences
Science Area:
Terrestrial
Overall Classification:
Terrestrial
ENRIs:
Biodiversity
Environmental Risks and Hazards
Natural Resource Management
Science Topics:
Statistics & Appl. Probability
Medical science & disease
Demography (General)
Population Ecology
Abstract:
Wild badgers are an important reservoir of bovine tuberculosis in the United Kingdom. This wildlife-disease interaction is of massive economic importance to the UK livestock industry, yet we still lack the ecological and epidemiological tools to better understand how to manage it. We propose a modelling project that uses 30 years of information on badger and tuberculosis population dynamics, collected by the National Wildlife Management Centre. We aim to create a working model of badger demography and TB prevalence that can actually predict future dynamics, and predict the impacts of relevant management strategies, for example targetted badger culls or vaccination campaigns. Even when badgers and TB are mointored intensively, there remains a great deal of uncertainty in our understanding: the diagnostic tests used to identify TB infections vary in their sensitivity (their ability to detect infection) and specificity (their ability to distinguish TB infection from other diseases); badgers may avoid capture; badgers move among social groups, can roam widely, and may mate with distant individuals. All of this uncertainty is best handled using new modelling techniques called Bayesian Integrated Population Models. We have already created a framework for these models, using the Woodchester Park badger dataset. We now aim to: (1) Model uncertainty in the sensitivity and specificity of the diagnostic tests used during the 30 year time series; (2) Integrate this uncertainty into a full model of badger demography (age- and sex-specific survival and reproduction; disease transmission and disease-induced mortality; disease prevalence), and test this model's ability to predict system dynamics over the last decade. (3) When we have a useful predictive model, we aim to test the efficacy of various management scenarios, including culling and vaccination regimes. Overall, this project represents the first attempt to properly consider uncertainty in models of badgers and TB, and will yield the best evidence base for optimal control of bovine tuberculosis in the wildlife reservoir. The PhD student will work in collaboration between the Centre for Ecology and Conservation and the College of Engineering, Mathematics and Physics at the University of Exeter, and the National Wildlife Management Centre, a section of DEFRA's Animal Health and Veterinary Laboratory Association.
Period of Award:
1 Oct 2015 - 30 Sep 2021
Value:
£85,122
Authorised funds only
NERC Reference:
NE/M010260/1
Grant Stage:
Completed
Scheme:
DTG - directed
Grant Status:
Closed
Programme:
Industrial CASE

This training grant award has a total value of £85,122  

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FDAB - Financial Details (Award breakdown by headings)

Total - FeesTotal - RTSGTotal - Student Stipend
£16,584£11,000£57,536

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