Bovine tuberculosis in San Luis Potosi, Mexico: spatial analysis and risk factors
DOI:
https://doi.org/10.12834/VetIt.3405.23070.2Keywords:
Cattle, Spatial distribution, Geographic Information Systems, Bayesian, M. bovisAbstract
A better understanding of the bovine tuberculosis (bTB) spatial distribution and the factors associated with increased risk is required to implement more effective control measures in Mexico. A cross-sectional study based on bTB testing on >1,600 herds in two regions of San Luis Potosi state, Altiplano and Huasteca, during 2018-2021 was conducted for the identification of spatial clustering and of bTB risk factors using the spatial scan statistic test and multivariable logistic regression models. The proportion of herds with at least one reactor was 17.9% in Altiplano and 38.6% in Huasteca, with one high risk cluster (HRC) present in each region. Larger herds (>20 animals) and those included in the HRC were exposed to a significantly increased risk of having at least one reactor in both regions. Given bTB caudal fold test limitations, herd disease freedom median posterior probability was calculated in an empirical Bayesian framework, classifying herds as “likely free” (> 94%) or “inconclusive”, the cluster and regression analysis was repeated, finding similar outcomes. Results demonstrated that certain herds are exposed to higher risk depending on their size and location in both regions, suggesting similar patterns of transmission; these findings can be used to further investigate how the disease spreads in San Luis Potosi.
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Consejo Nacional de Ciencia y Tecnología
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Asociación Universitaria Iberoamericana de Postgrado
Grant numbers CUMex-AUIP 2022
