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dc.contributor.authorNaranjo Lucena, Amalia
dc.contributor.authorMunita Corbalán, María Pía
dc.contributor.authorMartínez-Ibeas, Ana María
dc.contributor.authorMcGrath, Guy
dc.contributor.authorSayers, Riona
dc.contributor.authorMulcahy, Grace
dc.contributor.authorZintl, Annetta
dc.date.accessioned2023-06-26T15:25:04Z
dc.date.available2023-06-26T15:25:04Z
dc.date.issued2018-05-07
dc.identifier.citationNaranjo Lucena, A., Munita Corbalán, M. P., Martínez-Ibeas, A. M., McGrath, G., Sayers, R., Mulcahy, G., & Zintl, A. (2018). Validation of a spatial liver fluke model under field conditions in Ireland. Geospatial Health, 13(1). https://doi.org/10.4081/gh.2018.641en_US
dc.identifier.urihttp://hdl.handle.net/11019/2950
dc.descriptionpeer-revieweden_US
dc.description.abstractFasciola hepatica is the causative agent of fasciolosis, a global disease of a wide range of mammals, particularly sheep and cattle. Liver fluke infection causes annual losses estimated at around €2.5 billion to livestock and food industries worldwide. Various models have been developed to define risk factors and predict exposure to this liver fluke in ruminants in European countries, most of them based exclusively on data from dairy herds. The aim of this study was to validate a published theoretical baseline risk map of liver fluke exposure and cluster maps in Ireland, by including further explanatory variables and additional herd types that are spatially more widespread. Three approaches were employed: i) comparison of predicted and actual exposure; ii) comparison of cluster distribution of hotspots and coldspots; and iii) development of a new model to compare predicted spatial distribution and risk factors. Based on new survey data, the published baseline predictive map was found to have a sensitivity of 94.7%, a specificity of 5%, a positive predictive value of 60% and a negative predictive value of 38.2%. In agreement with the original model, our validation highlighted temperature and rainfall among the main risk factors. In addition, we identified vegetation indices as important risk factors. Both the previously published and our new model predict that exposure to Fasciola is higher in the western parts of Ireland. However, foci of high probability do not match completely, nor do the location of clusters of hotspots and coldspots.en_US
dc.language.isoenen_US
dc.publisherPAGEPress Publicationsen_US
dc.relation.ispartofseriesGeospatial Health;Vol 13
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectFasciolosisen_US
dc.subjectHotspot analysisen_US
dc.subjectIrelanden_US
dc.subjectSpatial modellingen_US
dc.subjectValidationen_US
dc.titleValidation of a spatial liver fluke model under field conditions in Irelanden_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.4081/gh.2018.641
dc.contributor.sponsorEuropean Union Horizon 2020 programmeen_US
dc.source.volume13
dc.source.issue1
refterms.dateFOA2023-06-26T15:25:06Z
dc.source.journaltitleGeospatial Health


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