000112521 001__ 112521
000112521 005__ 20230914083433.0
000112521 0247_ $$2doi$$a10.1080/20008686.2022.2025647
000112521 0248_ $$2sideral$$a128117
000112521 037__ $$aART-2022-128117
000112521 041__ $$aeng
000112521 100__ $$0(orcid)0000-0001-7483-046X$$aEstrada-Peña, A.$$uUniversidad de Zaragoza
000112521 245__ $$aIs composition of vertebrates an indicator of the prevalence of tick-borne pathogens?
000112521 260__ $$c2022
000112521 5060_ $$aAccess copy available to the general public$$fUnrestricted
000112521 5203_ $$aCommunities of vertebrates tend to appear together under similar ranges of environmental features. This study explores whether an explicit combination of vertebrates and their contact rates with a tick vector might constitute an indicator of the prevalence of a pathogen in the quest for ticks at the western Palearctic scale. We asked how ‘indicator’ communities could be ‘markers’ of the actual infection rates of the tick in the field of two species of Borrelia (a bacterium transmitted by the tick Ixodes ricinus). We approached an unsupervised classification of the territory to obtain clusters on the grounds of abundance of each vertebrate and contact rates with the tick. Statistical models based on Neural Networks, Random Forest, Gradient Boosting, and AdaBoost were detect the best correlation between communities’ composition and the prevalence of Borrelia afzelii and Borrelia gariniii in questing ticks. Both Gradient Boosting and AdaBoost produced the best results, predicting tick infection rates from the indicator communities. A ranking algorithm demonstrated that the prevalence of these bacteria in the tick is correlated with indicator communities of vertebrates on sites selected as a proof-of-concept. We acknowledge that our findings are supported by statistical outcomes, but they provide consistency for a framework that should be deeper explored at the large scale. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
000112521 536__ $$9info:eu-repo/grantAgreement/ES/DGA/A16-20R
000112521 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttp://creativecommons.org/licenses/by-nc/3.0/es/
000112521 592__ $$a0.707$$b2022
000112521 593__ $$aEnvironmental Science (miscellaneous)$$c2022$$dQ2
000112521 593__ $$aEpidemiology$$c2022$$dQ3
000112521 594__ $$a9.6$$b2022
000112521 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000112521 700__ $$aFernández-Ruiz, N.$$uUniversidad de Zaragoza
000112521 7102_ $$11009$$2773$$aUniversidad de Zaragoza$$bDpto. Patología Animal$$cÁrea Sanidad Animal
000112521 773__ $$g12, 1 (2022), 202564 [17 pp]$$tInfection Ecology and Epidemiology$$x2000-8686
000112521 8564_ $$s12413445$$uhttps://zaguan.unizar.es/record/112521/files/texto_completo.pdf$$yVersión publicada
000112521 8564_ $$s998363$$uhttps://zaguan.unizar.es/record/112521/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000112521 909CO $$ooai:zaguan.unizar.es:112521$$particulos$$pdriver
000112521 951__ $$a2023-09-13-12:14:44
000112521 980__ $$aARTICLE