Journal
EMERGING INFECTIOUS DISEASES
Volume 23, Issue 3, Pages 415-422Publisher
CENTERS DISEASE CONTROL & PREVENTION
DOI: 10.3201/eid2303.160101
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Funding
- National Science Foundation under a Rapid Response Research grant [1515194]
- Research and Policy for Infectious Disease Dynamics program of the Science and Technology Directorate of the US Department of Homeland Security
- Fogarty International Center of the National Institutes of Health
- National Institute of General Medical Sciences of the National Institutes of Health [U01GM110744]
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [1515194] Funding Source: National Science Foundation
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Because the natural reservoir of Ebola virus remains unclear and disease outbreaks in humans have occurred only sporadically over a large region, forecasting when and where Ebola spillovers are most likely to occur constitutes a continuing and urgent public health challenge. We developed a statistical modeling approach that associates 37 human or great ape Ebola spillovers since 1982 with spatiotemporally dynamic covariates including vegetative cover, human population size, and absolute and relative rainfall over 3 decades across sub-Saharan Africa. Our model (area under the curve 0.80 on test data) shows that spillover intensity is highest during transitions between wet and dry seasons; overall, high seasonal intensity occurs over much of tropical Africa; and spillover intensity is greatest at high (>1,000/km(2)) and very low (<100/km(2)) human population densities compared with intermediate levels. These results suggest strong seasonality in Ebola spillover from wild reservoirs and indicate particular times and regions for targeted surveillance.
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