Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale

TL;DR

This study used GIS-based multicriteria evaluation to create landscape-scale maps of Ebola spillover risk, revealing high spatial and temporal variability and aligning with known outbreak locations, aiding future surveillance.

Contribution

It introduces a knowledge-based GIS-MCE approach to map Ebola spillover risk areas at the landscape scale, integrating environmental, climatic, and anthropogenic factors.

Findings

Spillover events occurred in areas of intermediate to high suitability.

The suitability maps showed high spatial and temporal variability.

The approach is robust and can be updated with new data.

Abstract

The unexpected Ebola virus outbreak in West Africa in 2014 involving the Zaire ebolavirus made clear that other regions outside Central Africa, its previously documented niche, were at risk of future epidemics. The complex transmission cycle and a lack of epidemiological data make mapping areas at risk of the disease challenging. We used a Geographic Information System-based multicriteria evaluation (GIS-MCE), a knowledge-based approach, to identify areas suitable for Ebola virus spillover to humans in regions of Guinea, Congo and Gabon where Ebola viruses already emerged. We identified environmental, climatic and anthropogenic risk factors and potential hosts from a literature review. Geographical data layers, representing risk factors, were combined to produce suitability maps of Ebola virus spillover at the landscape scale. Our maps show high spatial and temporal variability in the suitability for Ebola virus spillover at a fine regional scale. Reported spillover events fell in areas of intermediate to high suitability in our maps, and a sensitivity analysis showed that the maps produced were robust. There are still important gaps in our knowledge about what factors are associated with the risk of Ebola virus spillover. As more information becomes available, maps produced using the GIS-MCE approach can be easily updated to improve surveillance and the prevention of future outbreaks.