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dc.contributor.authorMcDonald, Jennifer Leslie
dc.date.accessioned2014-08-08T08:25:30Z
dc.date.issued2014-05-09
dc.description.abstractThe topic of badgers in the UK is often a contentious one, dividing opinions and sparking political debate. On one hand, badgers represent an important part of the British ecosystem but on the other a wildlife reservoir of disease implicated in the transmission of bovine tuberculosis (TB) to livestock in the UK. This has prompted strong interest in their population dynamics and epidemiology. Using data from a long-term study of a naturally infected badger population in Woodchester Park, Gloucestershire, this thesis explores a range of capture-mark-recapture (CMR) models to further understand disease and demographic processes. The first section examines long term population dynamics, simultaneously estimating demographic rates alongside their drivers using integrated population models (IPMs). The findings provide new insight into badger demography, highlighting density-dependent mechanisms, vulnerabilities to changing climate and disease prevalence and subsequently how multi-factorial analyses are required to explain fluctuating badger populations. The following sections use multistate models to answer pertinent questions regarding individual disease dynamics, revealing rates of TB infection, progression and disease-induced mortality. A key finding was sex-differences in disease response, with males more susceptible to TB infection. After applying a survival trajectory analysis we suggest sex differences are due to male immune defence deficiencies. A comparative analysis demonstrated similarities between epidemiological processes at Woodchester Park to an unconnected population of badgers from a vaccine study, supporting its continued use as a model population. The final study in this thesis constructs an IPM to estimate disease and population dynamics and in doing so uncovers disease-state recruitment allocation rates, demographic and population estimates of badgers in varying health-states and predicts future dynamics. This model aims to encapsulate the more commonly held notion of populations as dynamic entities with numerous co-occurring processes, opening up avenues for future analyses within both the badger-TB system and possible extensions to other wildlife reservoir populations.en_GB
dc.description.sponsorshipNERCen_GB
dc.identifier.citationGraham, J., Smith, G. C., Delahay, R. J., Bailey, T., McDonald, R. A., & Hodgson, D. (2013). Multi-state modelling reveals sex-dependent transmission, progression and severity of tuberculosis in wild badgers. Epidemiology and infection, 141(07), 1429-1436.en_GB
dc.identifier.citationMcDonald, J. L., Smith, G. C., McDonald, R. A., Delahay, R. J., & Hodgson, D. (2014). Mortality trajectory analysis reveals the drivers of sex-specific epidemiology in natural wildlife–disease interactions. Proceedings of the Royal Society B: Biological Sciences, 281(1790), 20140526.en_GB
dc.identifier.urihttp://hdl.handle.net/10871/15336
dc.language.isoenen_GB
dc.publisherUniversity of Exeteren_GB
dc.rights.embargoreasonI am currently trying to develop chapters for publication and would rather the thesis not be made open access until this time.en_GB
dc.subjectBovine tuberculosisen_GB
dc.subjectEuropean badgeren_GB
dc.subjectstate-dependent modellingen_GB
dc.subjectsurvivalen_GB
dc.subjectwildlife diseaseen_GB
dc.subjectSex-differencesen_GB
dc.subjectdiseaseen_GB
dc.subjectBayesianen_GB
dc.subjectsurvival analysisen_GB
dc.subjectCapture-mark-recaptureen_GB
dc.titleDisease and Demography in the Woodchester Park Badger Populationen_GB
dc.typeThesis or dissertationen_GB
dc.contributor.advisorHodgson, Dave
dc.publisher.departmentBiosciencesen_GB
dc.type.degreetitlePhD in Biological Sciencesen_GB
dc.type.qualificationlevelDoctoralen_GB
dc.type.qualificationnamePhDen_GB


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