Estimates of rabies risk from vampire bats to livestock in Colombia.
Andrea T Medina-Rodríguez1
Andrés F Osejo-Varona2
Jaime Unriza-Vargas3
Diego Soler-Tovar4
Zulma Rojas-Sereno5
Luis E Escobar6
Paige Van de Vuurst7
Affiliations7 institutions
Instituto Colombiano Agropecuario (ICA), Subgerencia de Protección Animal, Dirección Técnica de Vigilancia Epidemiológica, Bogotá, Colombia.
Instituto Colombiano Agropecuario (ICA), Subgerencia de Protección Animal, Dirección Técnica de Sanidad Animal, Bogotá, Colombia.
Unidad de Planificación Agropecuaria (UPRA), Grupo Análisis de Información, Oficina TIC, Bogotá, Colombia.
Universidad La Salle, Facultad de Ciencias Agropecuarias, Grupo Epidemiología y Salud Pública, Bogotá, Colombia.
Universidad Andres Bello, Facultad Ciencias de la Vida, Doctorado en Medicina de la Conservación, Santiago, Chile.
Virginia Tech, Department of Fish and Wildlife Conservation, Center for Emerging Zoonotic and Arthropod-borne Pathogens, Kellogg Center for Philosophy, Politics, and Economics, Blacksburg, Virginia, USA.
Virginia Tech Graduate School, Translational Biology, Medicine and Health Program, Virginia Tech, Blacksburg, Virginia, USA and Department of Geography and Environment, Columbian College of Arts and Sciences, The George Washington University, Washington, District of Columbia, USA.
The goal of this study is to share with the community a spatial model of vampire-bat rabies (VBR) spillover risk developed with the government of Colombia to better inform current anti-rabies vaccination efforts. This model was designed to determine likely areas where vaccination should be prioritized across Colombia. This spatial analysis designed by the Instituto Colombiano Agropecuario (ICA) sought to develop a predictive data-driven model, with information obtained from passive surveillance. Predictive identification of VBR hotspots of transmission risk within Colombia was made by incorporating VBR epidemiological data with environmental and landscape variables. This study identified clustered patterns of the current geographic risk of VBR in Colombia, which were used to inform a national effort for rabies vaccination. Areas of VBR spillover risk were associated with distance to forested area, climate, and high cattle density in the Caribbean and Andean regions. At least 87% of Colombia could be identified as "at risk" to VBR spillover based on environmental conditions. That is, the majority of the country has conditions similar to sites were VBR spillover to livestock has occurred in the past. The model identified 88 municipalities as being at high risk for VBR spillover (spillover risk ≥0.70). More years of vaccination data are needed for an accurate evaluation of the rabies vaccination program in cattle in Colombia. This study provides a refined VBR transmission-risk map, which reveals key geographic to be prioritized for vaccination and govertment effort for VBR control.
Distributionmodelsprophylaxisrabies virusriskspillover (Sources: UNESCO, DECS, and MeSH)
Structured evidence records
Evidence records
2 total
Spillover Event1 records
Spillover EventExtraction confidence 0.95
Key finding
Rabies virus spillover from vampire bats to livestock has been documented in Colombia, with identified geographic areas showing high risk for such transmission.
Areas of VBR spillover risk were associated with distance to forested area, climate, and high cattle density in the Caribbean and Andean regions. That is, the majority of the country has conditions similar to sites where VBR spillover to livestock has occurred in the past.
Rabies virus surveillance data from vampire bats and livestock in Colombia were used to identify high-risk areas for spillover and to inform vaccination strategies.
This spatial analysis designed by the Instituto Colombiano Agropecuario (ICA) sought to develop a predictive data-driven model, with information obtained from passive surveillance. Predictive identification of VBR hotspots of transmission risk within Colombia was made by incorporating VBR epidemiological data with environmental and landscape variables.
Method
passive surveillance; spatial modeling
Geographic raw
Colombia
Country inferred
Colombia
Citation context
References
35 references
Reference network
Force-directed citation graph. OmniVira-indexed references are prioritized and recursively expanded up to three steps.
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