Identifying clusters of Mycobacterium bovis infection in cattle by applying spatial analysis methods to bovine tuberculosis surveillance data in the higher incidence areas of England

Spatio-temporal analyses are used in epidemiological studies to detect disease risk. In this paper, we assessed the level of heterogeneity of bovine tuberculosis (bTB) in cattle in higher incidence areas of England where the disease is considered endemic. The spatial distribution of bTB between 2013 and 2022 was analysed using herd incidence and breakdown data. Some areas improved over time, consistent with a decrease in disease burden. Incidence rates (per 100 herd-years at risk) remained unchanged in parts despite enhanced control measures being implemented, including increased herd testing frequency, and licensed badger culling over much of the High Risk Area (HRA). Applying Getis Ord Gi* and Local Moran’s I identified significant positive clusters, outliers, hotspots and coldspots, with the number decreasing over time. Spatial scan statistics using SaTScan identified clusters of bTB infection with the highest number in 2015-2016 (n=16), decreasing to four in 2021-2022. There was little overlap between all methods. Where bTB clusters remain, this suggests that some transmission routes are not being fully managed, such as local reservoirs of infection in cattle and wildlife, and movement of infected cattle. Areas identified as having the highest infection burden would benefit from further epidemiological investigation. Using these spatial analysis methods collectively can help to identify areas of England which have sustained consistently high incidence rates over time. These results provide insight into the level of heterogeneity occurring in the higher incidence areas of England, which can help with the selection of specific areas for targeted interventions to control bTB.