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Bovine tuberculosis (TB) poses a serious threat for agricultural industry inseveral countries, it involves potential interactions between wildlife andcattle and creates societal problems in terms of human-wildlife conflict. Thisstudy addresses connectedness network analysis, the spatial, and temporaldynamics of TB between cattle in farms and the European badger (Meles meles)using a large dataset generated by a calibrated agent based model. Resultsshowed that infected network connectedness was lower in badgers than in cattle.The contribution of an infected individual to the mean distance of diseasespread over time was considerably lower for badger than cattle; badgers mainlyspread the disease locally while cattle infected both locally and across longerdistances. The majority of badger-induced infections occurred when individualbadgers leave their home sett, and this was positively correlated with badgerpopulation growth rates. Point pattern analysis indicated aggregation in thespatial pattern of TB prevalence in badger setts across all scales. The spatialdistribution of farms that were not TB free was aggregated at different scalesthan the spatial distribution of infected badgers and became random at largerscales. The spatial cross correlation between infected badger setts andinfected farms revealed that generally infected setts and farms do not coexistexcept at few scales. Temporal autocorrelation detected a two year infectioncycle for badgers, while there was both within the year and longer cycles forinfected cattle. Temporal cross correlation indicated that infection cycles inbadgers and cattle are negatively correlated. The implications of these resultsfor understanding the dynamics of the disease are discussed.

A big-data spatial, temporal and network analysis of bovine tuberculosis between wildlife (badgers) and cattle