abstract

• 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%25 in Altiplano and 38.6%25 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 94%25) or

authors

• Ballesteros Rodea Gilberto
• Hernández Arteaga Luisa Eugenia del Socorro
• Álvarez Fuentes Gregorio

publication date

• 2024-01-01

funding provided via

• Ministerio de Ciencia, Innovación y Universidades, MCIU; Universidad Complutense de Madrid, UCM; Ministerio de Ciencia e Innovación, MCIN; Consortium of Mexican Universities; Consejo Nacional de Ciencia y Tecnología, Paraguay, CONACYT; Asociación Universitaria Iberoamericana de Postgrado, AUIP; Ibero-American Postgraduate University Association; University of Central Missouri, UCM, (RTI2018-096010-B-C22); University of Central Missouri, UCM  Grant

published in

• Veterinaria Italiana  Journal

keywords

• Bayesian; Cattle; Geographic Information System; M. bovis; Spatial distribution Article; bovine tuberculosis; caudal fold test; cluster analysis; cross-sectional study; diagnostic test; disease transmission; geographic distribution; geographic information system; histopathology; logistic regression analysis; Mycobacterium bovis; nonhuman; prevalence; receiver operating characteristic; regionalization; risk factor; San Luis Potosi (state); sensitivity and specificity; spatial analysis; whole genome sequencing

Digital Object Identifier (DOI)

• 10.12834/VetIt.3405.23070.2

PubMed ID

start page

end page

volume

• 60

issue

• 4 Special Issue