Spatiotemporal disease suitability prediction for Oropouche virus and the role of vectors across the Americas.
TL;DR
The resulting suitability model identifies high transmission risk areas in Central and South America, and reveals that environmental suitability patterns align with seasonal fluctuations in case numbers, with peaks in Amazonian states at the beginning of the year and an expansion into non-Amazonian regions later in the year.
Abstract
Oropouche virus (OROV) is an emerging arbovirus with increasing outbreaks in South America, yet its environmental drivers and potential range remain poorly understood. Using ecological niche modeling (ENM) with random forests, we assessed the environmental suitability of OROV and its primary vector, Culicoides paraensis, across Brazil and the Americas. We evaluated five pseudo-absence sampling techniques, considering pseudo-absence ratios, buffer radii, and density smoothing factors to determine the most effective modeling approach. Key environmental predictors included humidity, agricultural land-use, and forest cover, while temperature had minimal influence for both the virus and the vector. The resulting suitability model identifies high transmission risk areas in Central and South America, and reveals that environmental suitability patterns align with seasonal fluctuations in case numbers, with peaks in Amazonian states at the beginning of the year and an expansion into non-Amazonian regions later in the year. A bivariate suitability map highlighted strong spatial overlap between OROV and Culicoides paraensis, with potential co-suitability areas with Culex quinquefasciatus mosquito, a suspected secondary vector. These findings enhance understanding of OROV transmission dynamics, supporting risk assessment, surveillance, and vector control strategies.