Objectives: The Western equine encephalitis virus (WEEV) is a globally relevant vector-borne pathogen that causes encephalitis. The role of environmental variables in the epidemiology of WEEV has become greater in the context of climate change. In December 2023, a significant resurgence of WEEV began in South America, with major ongoing outbreaks in Argentina and Uruguay. In this study, we employed a machine learning algorithm to model the distribution of WEEV in South America, considering both present and future scenarios.
Study design: Ecological retrospective study.
Methods: We conducted a modelling study to identify areas with the highest prevalence of WEEV in South America, based on confirmed human and equine cases during the 2023/2024 outbreak and climatic variables. Our analysis utilised Maxent software, a machine learning algorithm for species distribution modelling.
Results: Our results indicate that environmental variables, particularly thermal seasonality and annual rainfall, can directly influence the occurrence of WEEV, leading to increased virus incidence. Consequently, high-risk areas may shift in the future. Countries, such as Paraguay, Venezuela, Colombia, and various regions in Brazil, particularly the Northeast, Midwest, and the Pantanal biomes, will be significantly impacted, drastically altering the current distribution of WEEV.
Conclusions: The ongoing WEEV outbreak in South America is concerning because it coincides with migratory bird stopovers. These birds are natural hosts that can spread the virus to unaffected areas. Our results will help to identify priority areas for developing preventive measures and establishing epidemiological surveillance.
Keywords: Epidemiology; Maxent; Mosquito; Outbreak; Temperature; Vector.
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