Resumen

ZARZA, Heliot; MARTINEZ-MEYER, Enrique; SUZAN, Gerardo  y  CEBALLOS, Gerardo. Geographic distribution of Desmodus rotundus in Mexico under current and future climate change scenarios: Implications for bovine paralytic rabies infection. Veterinaria México OA [online]. 2017, vol.4, n.3, pp.10-25. ISSN 2448-6760.  https://doi.org/10.21753/vmoa.4.3.390.

Climate change may modify the spatial distribution of reservoirs hosting emerging and reemerging zoonotic pathogens, and forecasting these changes is essential for developing prevention and adaptation strategies. The most important reservoir of bovine paralytic rabies in tropical countries, is the vampire bat (Desmodus rotundus). In Mexico, the cattle industry loses more than $2.6 million US dollar, annually to this infectious disease. Therefore, we predicted the change in the distribution of D. rotundus due to future climate change scenarios, and examined the likely effect that the change in its distribution will have on paralytic rabies infections in Mexico. We used the correlative maximum entropy based model algorithm to predict the potential distribution of D. rotundus. Consistent with the literature, our results showed that temperature was the variable most highly associated with the current distribution of vampire bats. The highest concentration of bovine rabies was in Central and Southeastern Mexico, regions that also have high cattle population densities. Furthermore, our climatic envelope models predicted that by 2050-2070, D. rotundus will lose 20 % of its current distribution while the northern and central regions of Mexico will become suitable habitats for D. rotundus. Together, our study provides an advanced notice of the likely change in spatial patterns of D. rotundus and bovine paralytic rabies, and presents an important tool for strengthening the National Epidemiological Surveillance System and Monitoring programmes, useful for establishing holistic, long-term strategies to control this disease in Mexico.

Palabras llave : vampire bat; rabies; maximum entropy model; livestock; climate change.

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