Spatio-temporal distribution and persistence of Mycobacterium Bovis in a badger population

Studying the dynamics of pathogen transmission within wildlife populations presents an array of challenges. Where populations are socially structured, this can influence parasite transmission, impacting on the effectiveness of disease management strategies. In this thesis, I focus on a well-studied social mammal, the European badger (Meles meles) which is a key wildlife reservoir of a disease of economic importance; bovine TB (caused by infection with Mycobacterium bovis). The social structuring, characteristic of high density badger populations, is of well-established importance in the transmission of bovine TB and has resulted in unexpected management outcomes. However, little is known about the role of kin structure or host genotype on transmission dynamics. In this thesis, I combine traditional spatial epidemiology and ecological analysis of a well-studied badger population with more novel genetic and genomic approaches. Firstly, I investigate the role of kin structure within badger social groups in determining early life infection risk (Chapter 3). Using host genotype data, I demonstrate that cubs who are related to infected adults experience enhanced infection risks. I then explore the role of badger genotype on outcomes of M. bovis exposure and demonstrate that inbred badgers are more likely to show evidence of progressive infection (Chapter 4). Where the social structure of badgers is stable and unmanaged, this is predicted to result in a stable spatial distribution of M. bovis infection. Motivated by an observation of change in the spatial distribution of M. bovis infection in the study population, in the absence of management, I characterise the attrition of a spatially stable infection distribution (Chapter 5). To explore the drivers of this, I detect changes in the genetic population structure (Chapter 6) and present evidence that the population has experienced a period of demographic flux. Finally, I use a novel dataset generated by whole genome sequencing of M. bovis isolates and present evidence of spatial spread of M. bovis infection across the study population (Chapter 7). To conclude, I discuss how my findings demonstrate how genetic and genomic approaches can complement traditional wildlife epidemiology approaches, how they contribute to our understanding of heterogeneity in transmission dynamics and discuss their implications for wildlife disease management.