Pigott David M, Millear Anoushka I, Earl Lucas, Morozoff Chloe, Han Barbara A, Shearer Freya M, Weiss Daniel J, Brady Oliver J, Kraemer Moritz Ug, Moyes Catherine L, Bhatt Samir, Gething Peter W, Golding Nick, Hay Simon I
Institute for Health Metrics and Evaluation, University of Washington, Seattle, United States.
Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, United Kingdom.
Elife. 2016 Jul 14;5:e16412. doi: 10.7554/eLife.16412.
As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers.
由于西非埃博拉病毒病（EVD）疫情现已得到控制，关注点正从疫情控制转向未来疫情的预测与预防。本研究以之前发表的人畜共患病生态位地图（皮戈特等人，2014年）为基础，纳入了新的人类和动物出现数据，并扩展了潜在蝙蝠埃博拉病毒病宿主物种的纳入方式。此次更新展示了整合和更新用于生成预测适宜性地图的数据的潜力。文中还讨论了一个用于共享此类地图的新数据门户。此成果代表了对非洲埃博拉病毒病人畜共患病风险范围的最新估计。这些地图有助于加强监测和应对能力，以控制病毒性出血热。
