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

Arran Hamlet (), Daniel Garkauskas Ramos, Katy A. M. Gaythorpe, Alessandro Pecego Martins Romano, Tini Garske and Neil M. Ferguson
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Arran Hamlet: Imperial College London
Daniel Garkauskas Ramos: Brazilian Ministry of Health
Katy A. M. Gaythorpe: Imperial College London
Alessandro Pecego Martins Romano: Brazilian Ministry of Health
Tini Garske: Imperial College London
Neil M. Ferguson: Imperial College London

Nature Communications, 2021, vol. 12, issue 1, 1-11

Abstract: Abstract Yellow fever virus (YFV) is a zoonotic arbovirus affecting both humans and non-human primates (NHP’s) in Africa and South America. Previous descriptions of YF’s seasonality have relied purely on climatic explanations, despite the high proportion of cases occurring in people involved in agriculture. We use a series of random forest classification models to predict the monthly occurrence of YF in humans and NHP’s across Brazil, by fitting four classes of covariates related to the seasonality of climate and agriculture (planting and harvesting), crop output and host demography. We find that models captured seasonal YF reporting in humans and NHPs when they considered seasonality of agriculture rather than climate, particularly for monthly aggregated reports. These findings illustrate the seasonality of exposure, through agriculture, as a component of zoonotic spillover. Additionally, by highlighting crop types and anthropogenic seasonality, these results could directly identify areas at highest risk of zoonotic spillover.

Date: 2021
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DOI: 10.1038/s41467-021-23926-y

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