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Seasonality of agricultural exposure as an important predictor of seasonal yellow fever spillover in Brazil

Medicine and Health

Seasonality of agricultural exposure as an important predictor of seasonal yellow fever spillover in Brazil

A. Hamlet, D. G. Ramos, et al.

Discover how research by Arran Hamlet, Daniel Garkauskas Ramos, Katy A. M. Gaythorpe, Alessandro Pecego Martins Romano, Tini Garske, and Neil M. Ferguson reveals that agricultural seasonality is a critical predictor of yellow fever virus occurrence in Brazil. This study challenges traditional climate-based models and opens new avenues for identifying high-risk areas through the lens of agriculture.

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Playback language: English
Abstract
Yellow fever virus (YFV) is a zoonotic arbovirus affecting both humans and non-human primates (NHPs) in Africa and South America. This study uses random forest classification models to predict the monthly occurrence of YF in humans and NHPs across Brazil, considering climate and agricultural factors. The findings show that models incorporating agricultural seasonality (planting and harvesting) are better predictors of YF occurrence than climate-based models, especially for monthly aggregated data. This highlights the seasonality of human exposure through agricultural activities as a key factor in zoonotic spillover and suggests that focusing on crop types and anthropogenic seasonality can identify high-risk areas for spillover.
Publisher
Nature Communications
Published On
Jun 15, 2021
Authors
Arran Hamlet, Daniel Garkauskas Ramos, Katy A. M. Gaythorpe, Alessandro Pecego Martins Romano, Tini Garske, Neil M. Ferguson
Tags
yellow fever virus
random forest classification
zoonotic spillover
agricultural seasonality
Brazil
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