An Environmental Niche Model to Estimate the Potential Presence of Venezuelan Equine Encephalitis Virus in Costa Rica

Bernal León, Carlos Jiménez-Sánchez and Mónica Retamosa-Izaguirre
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Bernal León: Biosecurity Laboratory, Veterinary Service National Laboratory, Animal Health National Service, Ministry of Agriculture and Cattle, Heredia 40104, Costa Rica
Carlos Jiménez-Sánchez: Laboratory of Virology, Tropical Diseases Research Program (PIET), School of Veterinary Medicine, National University, Heredia 40101, Costa Rica
Mónica Retamosa-Izaguirre: International Institute for Wildlife Conservation and Management, National University of Costa Rica, Heredia 40101, Costa Rica

IJERPH, 2020, vol. 18, issue 1, 1-12

Abstract: Venezuelan equine encephalitis virus (VEEV) is an arbovirus transmitted by arthropods, widely distributed in the Americas that, depending on the subtype, can produce outbreaks or yearly cases of encephalitis in horses and humans. The symptoms are similar to those caused by dengue virus and in the worst-case scenario, involve encephalitis, and death. MaxEnt is software that uses climatological, geographical, and occurrence data of a particular species to create a model to estimate possible niches that could have these favorable conditions. We used MaxEnt with a total of 188 registers of VEEV presence, and 20 variables, (19 bioclimatological plus altitude) to determine the niches promising for the presence of VEEV. The area under the ROC curve (AUC) value for the model with all variables was 0.80 for the training data and 0.72 for the test. The variables with the highest contribution to the model were Bio11 (mean temperature of the coldest quarter) 32.5%, Bio17 (precipitation of the driest quarter) 16.9%, Bio2 (annual mean temperature) 15.1%, altitude (m.a.s.l) 6.6%, and Bio18 (precipitation of the warmest quarter) 6.2%. The product of this research will be useful under the one health scheme to animal and human health authorities to forecast areas with high propensity for VEEV cases in the future.

Keywords: VEEV; predicted map; MaxEnt; Costa Rica; arbovirus; zoonotic (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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