Data from: Spatial spread of the West Africa Ebola epidemic

Controlling Ebola outbreaks and planning an effective response to future emerging diseases are enhanced by understanding the role of geography in transmission. Here we show how epidemic expansion may be predicted by evaluating the relative probability of alternative epidemic paths. We compared multiple candidate models to characterize the spatial network over which the 2013-2015 West Africa epidemic of Ebola virus spread and estimate the effects of geographic covariates on transmission during peak spread. The best model was a generalized gravity model where the probability of transmission between locations depended on distance, population density and international border closures between Guinea, Liberia and Sierra Leone and neighboring countries. This model out-performed alternative models based on diffusive spread, the force of infection, mobility estimated from cell-phone records and other hypothesized patterns of spread. These findings highlight the importance of integrated geography to epidemic expansion and may contribute to identifying both the most vulnerable unaffected areas and locations of maximum intervention value.

理解地理因素在埃博拉病毒传播中的作用，有助于管控埃博拉疫情暴发，并为有效应对未来新发传染病提供支撑。本研究通过评估不同疫情传播路径的相对概率，揭示了疫情扩散的预测方法。我们对比了多种候选模型，以刻画2013-2015年西非埃博拉病毒疫情传播所依托的空间网络，并估算了疫情峰值传播阶段地理协变量对传播的影响。最优模型为广义重力模型（generalized gravity model），其中两地间的传播概率取决于距离、人口密度，以及几内亚、利比里亚、塞拉利昂与周边国家之间实施的国际边境关闭政策。该模型的表现优于基于扩散传播、感染力、手机通信记录估算的移动性，以及其他假设传播模式的备选模型。本研究结果凸显了综合地理因素对疫情扩散的重要性，可为识别最脆弱的未受影响地区，以及干预价值最高的地点提供参考。