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The Western Africa Ebola Virus Disease Epidemic Exhibits Both Global Exponential and Local Polynomial Growth Rates

机译:西非埃博拉病毒病疫情呈全球性和局部多项式增长率

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摘要

Background: While many infectious disease epidemics are initially characterized by an exponential growth in time, we show that district-level Ebola virus disease (EVD) outbreaks in West Africa follow slower polynomial-based growth kinetics over several generations of the disease.Methods: We analyzed epidemic growth patterns at three different spatial scales (regional, national, and subnational) of the Ebola virus disease epidemic in Guinea, Sierra Leone and Liberia by compiling publicly available weekly time series of reported EVD case numbers from the patient database available from the World Health Organization website for the period 05-Jan to 17-Dec 2014.Results: We found significant differences in the growth patterns of EVD cases at the scale of the country, district, and other subnational administrative divisions. The national cumulative curves of EVD cases in Guinea, Sierra Leone, and Liberia show periods of approximate exponential growth. In contrast, local epidemics are asynchronous and exhibit slow growth patterns during 3 or more EVD generations, which can be better approximated by a polynomial than an exponential function.Conclusions: The slower than expected growth pattern of local EVD outbreaks could result from a variety of factors, including behavior changes, success of control interventions, or intrinsic features of the disease such as a high level of clustering. Quantifying the contribution of each of these factors could help refine estimates of final epidemic size and the relative impact of different mitigation efforts in current and future EVD outbreaks.
机译:背景:虽然许多传染病的流行最初都以时间呈指数增长为特征,但我们表明,西非地区级埃博拉病毒病(EVD)爆发在疾病的几代人中都遵循基于多项式的缓慢增长动力学。通过汇总可从世界各地获得的患者数据库中每周可公开获得的报告EVD病例数的每周时间序列,分析了几内亚,塞拉利昂和利比里亚的埃博拉病毒病流行的三个不同空间尺度(区域,国家和国家以下)的流行病增长模式卫生组织2014年1月5日至12月17日的网站。结果:我们发现EVD病例在国家,地区和其他地方以下行政区划的规模增长方式上存在显着差异。几内亚,塞拉利昂和利比里亚的EVD病例的国家累积曲线显示出近似指数增长时期。相比之下,局部流行病是异步的,并且在3个或更多EVD世代中表现出缓慢的增长模式,与指数函数相比,可以用多项式更好地近似。结论:局部EVD爆发的增长模式低于预期的增长模式可能是由于影响因素,包括行为改变,控制干预措施的成功或疾病的固有特征,例如高度聚集。量化这些因素中的每一个的贡献可以帮助完善最终流行病规模的估计以及当前和未来EVD爆发中不同缓解措施的相对影响。

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