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A Bayesian approach to study the risk variables for tuberculosis occurrence in domestic and wild ungulates in South Central Spain

dc.contributor.authorRodríguez Prieto, Víctor
dc.contributor.authorMartínez López, Beatriz
dc.contributor.authorBarasona García-Arévalo, José Ángel
dc.contributor.authorAcevedo, Pelayo
dc.contributor.authorRomero Martínez, Beatriz
dc.contributor.authorRodriguez Campos, Sabrina
dc.contributor.authorGortázar, Christian
dc.contributor.authorSánchez-Vizcaíno Rodríguez, José Manuel
dc.contributor.authorVicente, Joaquín
dc.date.accessioned2023-06-20T04:19:17Z
dc.date.available2023-06-20T04:19:17Z
dc.date.issued2012-08-30
dc.description.abstractBACKGROUND Bovine tuberculosis (bTB) is a chronic infectious disease mainly caused by Mycobacterium bovis. Although eradication is a priority for the European authorities, bTB remains active or even increasing in many countries, causing significant economic losses. The integral consideration of epidemiological factors is crucial to more cost-effectively allocate control measures. The aim of this study was to identify the nature and extent of the association between TB distribution and a list of potential risk factors regarding cattle, wild ungulates and environmental aspects in Ciudad Real, a Spanish province with one of the highest TB herd prevalences. RESULTS We used a Bayesian mixed effects multivariable logistic regression model to predict TB occurrence in either domestic or wild mammals per municipality in 2007 by using information from the previous year. The municipal TB distribution and endemicity was clustered in the western part of the region and clearly overlapped with the explanatory variables identified in the final model: (1) incident cattle farms, (2) number of years of veterinary inspection of big game hunting events, (3) prevalence in wild boar, (4) number of sampled cattle, (5) persistent bTB-infected cattle farms, (6) prevalence in red deer, (7) proportion of beef farms, and (8) farms devoted to bullfighting cattle. CONCLUSIONS The combination of these eight variables in the final model highlights the importance of the persistence of the infection in the hosts, surveillance efforts and some cattle management choices in the circulation of M. bovis in the region. The spatial distribution of these variables, together with particular Mediterranean features that favour the wildlife-livestock interface may explain the M. bovis persistence in this region. Sanitary authorities should allocate efforts towards specific areas and epidemiological situations where the wildlife-livestock interface seems to critically hamper the definitive bTB eradication success.
dc.description.facultyCentro de Vigilancia Sanitaria Veterinaria (VISAVET)
dc.description.refereedTRUE
dc.description.sponsorshipUnión Europea. FP7
dc.description.sponsorshipInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/39665
dc.identifier.doi10.1186/1746-6148-8-148
dc.identifier.issn1746-6148
dc.identifier.officialurlhttp://bmcvetres.biomedcentral.com/articles/10.1186/1746-6148-8-148
dc.identifier.urihttps://hdl.handle.net/20.500.14352/45165
dc.journal.titleBMC veterinary research
dc.language.isoeng
dc.page.initial148
dc.publisherBioMedCentral
dc.relation.projectIDTB-STEP (212414)
dc.relation.projectIDFAU2008-00004-C03
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.ucmVeterinaria
dc.subject.unesco3109 Ciencias Veterinarias
dc.titleA Bayesian approach to study the risk variables for tuberculosis occurrence in domestic and wild ungulates in South Central Spain
dc.typejournal article
dc.volume.number8
dspace.entity.typePublication
relation.isAuthorOfPublication7ac9cf6b-78dc-4407-85c8-17a3c3652015
relation.isAuthorOfPublication6b436065-5bf3-4a47-86c1-57e869d29a51
relation.isAuthorOfPublicationb078d9ce-ccce-49e2-a4e9-0ce85eca877e
relation.isAuthorOfPublication.latestForDiscovery6b436065-5bf3-4a47-86c1-57e869d29a51

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