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Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir.
Ribeiro, Rita; Matthiopoulos, Jason; Lindgren, Finn; Tello, Carlos; Zariquiey, Carlos M; Valderrama, William; Rocke, Tonie E; Streicker, Daniel G.
Afiliación
  • Ribeiro R; School of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, University Avenue, Graham Kerr Building, Glasgow G12 8QQ, UK.
  • Matthiopoulos J; School of Biodiversity, One Health and Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, University Avenue, Graham Kerr Building, Glasgow G12 8QQ, UK.
  • Lindgren F; School of Mathematics, University of Edinburgh, Edinburgh, UK.
  • Tello C; ILLARIY (Asociación para el Desarrollo y Conservación de los Recursos Naturales), Lima, Perú.
  • Zariquiey CM; Yunkawasi, Lima, Perú.
  • Valderrama W; ILLARIY (Asociación para el Desarrollo y Conservación de los Recursos Naturales), Lima, Perú.
  • Rocke TE; ILLARIY (Asociación para el Desarrollo y Conservación de los Recursos Naturales), Lima, Perú.
  • Streicker DG; Facultad de Medicina Veterinaria y Zootecnia, Universidad Peruana Cayetano Heredia, Lima, Perú.
Proc Biol Sci ; 290(2011): 20231739, 2023 Nov 29.
Article en En | MEDLINE | ID: mdl-37989240
Predicting the spatial occurrence of wildlife is a major challenge for ecology and management. In Latin America, limited knowledge of the number and locations of vampire bat roosts precludes informed allocation of measures intended to prevent rabies spillover to humans and livestock. We inferred the spatial distribution of vampire bat roosts while accounting for observation effort and environmental effects by fitting a log Gaussian Cox process model to the locations of 563 roosts in three regions of Peru. Our model explained 45% of the variance in the observed roost distribution and identified environmental drivers of roost establishment. When correcting for uneven observation effort, our model estimated a total of 2340 roosts, indicating that undetected roosts (76%) exceed known roosts (24%) by threefold. Predicted hotspots of undetected roosts in rabies-free areas revealed high-risk areas for future viral incursions. Using the predicted roost distribution to inform a spatial model of rabies spillover to livestock identified areas with disproportionate underreporting and indicated a higher rabies burden than previously recognized. We provide a transferrable approach to infer the distribution of a mostly unobserved bat reservoir that can inform strategies to prevent the re-emergence of an important zoonosis.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Rabia / Virus de la Rabia / Quirópteros Límite: Animals / Humans Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Rabia / Virus de la Rabia / Quirópteros Límite: Animals / Humans Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido