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dc.contributor.authorEscobar, Luis E.
dc.contributor.authorPeterson, A. Townsend
dc.contributor.authorPapeş, Monica
dc.contributor.authorFavi, Myriam
dc.contributor.authorYung, Verónica
dc.contributor.authorRestif, Olivier
dc.contributor.authorQiao, Huijie
dc.contributor.authorMedina-Vogel, Gonzalo
dc.date.accessioned2016-02-05T16:01:27Z
dc.date.available2016-02-05T16:01:27Z
dc.date.issued2015-09-04
dc.identifier.citationEscobar, Luis E., A. Townsend Peterson, Monica Papeş, Myriam Favi, Veronica Yung, Olivier Restif, Huijie Qiao, and Gonzalo Medina-Vogel. "Ecological Approaches in Veterinary Epidemiology: Mapping the Risk of Bat-borne Rabies Using Vegetation Indices and Night-time Light Satellite Imagery." Vet Res Veterinary Research 46.1 (2015): n. pag. http://dx.doi.org/10.1186/s13567-015-0235-7.en_US
dc.identifier.urihttp://hdl.handle.net/1808/19895
dc.description.abstractRabies remains a disease of significant public health concern. In the Americas, bats are an important source of rabies for pets, livestock, and humans. For effective rabies control and prevention, identifying potential areas for disease occurrence is critical to guide future research, inform public health policies, and design interventions. To anticipate zoonotic infectious diseases distribution at coarse scale, veterinary epidemiology needs to advance via exploring current geographic ecology tools and data using a biological approach. We analyzed bat-borne rabies reports in Chile from 2002 to 2012 to establish associations between rabies occurrence and environmental factors to generate an ecological niche model (ENM). The main rabies reservoir in Chile is the bat species Tadarida brasiliensis; we mapped 726 occurrences of rabies virus variant AgV4 in this bat species and integrated them with contemporary Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The correct prediction of areas with rabies in bats and the reliable anticipation of human rabies in our study illustrate the usefulness of ENM for mapping rabies and other zoonotic pathogens. Additionally, we highlight critical issues with selection of environmental variables, methods for model validation, and consideration of sampling bias. Indeed, models with weak or incorrect validation approaches should be interpreted with caution. In conclusion, ecological niche modeling applications for mapping disease risk at coarse geographic scales have a promising future, especially with refinement and enrichment of models with additional information, such as night-time light data, which increased substantially the model’s ability to anticipate human rabies.en_US
dc.publisherBioMed Centralen_US
dc.rightsOpen AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleEcological approaches in veterinary epidemiology: mapping the risk of bat-borne rabies using vegetation indices and night-time light satellite imageryen_US
dc.typeArticle
kusw.kuauthorTownsend Peterson, A.
kusw.kudepartmentEcology & Evolutionary Biologyen_US
dc.identifier.doi10.1186/s13567-015-0235-7
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Except where otherwise noted, this item's license is described as: Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.