Spatial predictors of bovine tuberculosis infection and Brucella spp. exposure in pastoralist and agropastoralist livestock herds in the Ruaha ecosystem of Tanzania
While many studies investigate animal-related risk factors for disease, few have considered environmental or spatial risk factors in the dynamics of bovine tuberculosis (bTB) and brucellosis. In the Ruaha ecosystem of Tanzania, we investigated the role of household location as a predictor for infection with Mycobacterium bovis and exposure to Brucella in pastoralist and agropastoralist cattle herds in a typical African wildlife-livestock-human interface. ArcGIS was utilized to calculate Euclidian distances between households and the nearest river, village center, protected area, and other infected households, followed by multivariate logistic regression to assess the association between risk factors and herd-level bTB and Brucella outcomes. Global and local spatial clustering of bTB-infected and Brucella-exposed herds was explored using the Cuzick-Edward’s test and SaTScan spatial scan statistics. Households located farther from rivers and closer to village centers and herds belonging to agropastoralists were more likely to have bTB-positive cattle. Risk of Brucella exposure increased with proximity to protected areas. One spatial cluster of households with Brucella spp. seropositive cattle was identified. Spatial factors may be useful for assessing disease risk and for formulating intervention and control strategies for households that manage cattle in ecosystems characterized by seasonally limited resources and intense wildlife-livestock interfaces.
KeywordsBovine tuberculosis Brucellosis Cattle Spatial predictors Tanzania
This research was part of the Health for Animals and Livelihood Improvement (HALI) Project, a One Health project addressing zoonotic diseases in Tanzania, and was funded by the Global Livestock Collaborative Research Support Program by the Office of Agriculture, Bureau for Economic Growth, Agriculture and Trade, United States Agency for International Development under the terms of Grant No. PCE-G-00-98-00036-00. Special thanks go to Howard Kombe who assisted with household interviews and testing of cattle; to Jonas Fitwangile, Ali Kitime, and Kuleng’wa Ndaki Lukiko for laboratory assistance; and to Laurel Beckett, Esthe Geraghty, and Kate Thomas for their advice on statistical analysis and mapping.
Conflict of interest
The authors declare that they have no conflict of interest.
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