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 geographical 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 neighbouring 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.明晰传播过程中的地理维度作用，可强化埃博拉疫情暴发的防控能力，并助力规划针对未来新发传染病的高效应对方案。本研究通过评估各类备选疫情传播路径的相对概率，阐明了疫情扩张的预测方法。我们对比了多种候选模型，以刻画2013至2015年西非埃博拉病毒疫情传播的空间网络，并估算了疫情峰值传播阶段地理协变量对病毒传播的影响。最优模型为广义重力模型，该模型中两地间的传播概率取决于空间距离、人口密度，以及几内亚、利比里亚、塞拉拉利昂与周边国家之间的国际边境封锁政策。相较于基于扩散传播、感染压力、手机信令数据估算的移动性，以及其他假设性传播模式的备选模型，该模型表现更优。本研究结果凸显了综合地理要素对疫情扩张的重要性，同时可为识别最脆弱的未受影响区域以及干预价值最高的地点提供参考依据。