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估算未被发现的埃博拉溢出。

Estimating undetected Ebola spillovers.

机构信息

Department of Veterinary Medicine, University of Cambridge, Cambridge United Kingdom.

出版信息

PLoS Negl Trop Dis. 2019 Jun 13;13(6):e0007428. doi: 10.1371/journal.pntd.0007428. eCollection 2019 Jun.

Abstract

The preparedness of health systems to detect, treat, and prevent onward transmission of Ebola virus disease (EVD) is central to mitigating future outbreaks. Early detection of outbreaks is critical to timely response, but estimating detection rates is difficult because unreported spillover events and outbreaks do not generate data. Using three independent datasets available on the distributions of secondary infections during EVD outbreaks across West Africa, in a single district (Western Area) of Sierra Leone, and in the city of Conakry, Guinea, we simulated realistic outbreak size distributions and compared them to reported outbreak sizes. These three empirical distributions lead to estimates for the proportion of detected spillover events and small outbreaks of 26% (range 8-40%, based on the full outbreak data), 48% (range 39-62%, based on the Sierra Leone data), and 17% (range 11-24%, based on the Guinea data). We conclude that at least half of all spillover events have failed to be reported since EVD was first recognized. We also estimate the probability of detecting outbreaks of different sizes, which is likely less than 10% for single-case spillover events. Comparing models of the observation process also suggests the probability of detecting an outbreak is not simply the cumulative probability of independently detecting any one individual. Rather, we find that any individual's probability of detection is highly dependent upon the size of the cluster of cases. These findings highlight the importance of primary health care and local case management to detect and contain undetected early stage outbreaks at source.

摘要

卫生系统做好准备以发现、治疗和预防埃博拉病毒病(EVD)的进一步传播,这对于减轻未来疫情至关重要。及早发现疫情对于及时作出反应至关重要,但由于未报告的溢出事件和疫情不会产生数据,因此难以估计检测率。我们利用在塞拉利昂西部行政区、几内亚科纳克里市和整个西非三个独立数据集,分析了埃博拉疫情期间二次感染的分布情况,对现实疫情规模分布进行了模拟,并将其与报告的疫情规模进行了比较。这三个经验分布导致对检测到的溢出事件和小型疫情的比例估计为 26%(基于完整疫情数据,范围为 8-40%)、48%(基于塞拉利昂数据,范围为 39-62%)和 17%(基于几内亚数据,范围为 11-24%)。我们得出结论,自首次发现埃博拉病毒以来,至少有一半的溢出事件未被报告。我们还估计了不同规模疫情的检测概率,对于单个病例的溢出事件,其检测概率可能小于 10%。比较观察过程的模型也表明,检测到疫情的概率并不简单地等于独立检测到任何一个个体的累积概率。相反,我们发现,任何个体的检测概率都高度依赖于病例集群的大小。这些发现凸显了初级卫生保健和当地病例管理在发现和遏制源头未被发现的早期疫情中的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/026d/6563953/5c9c6cdc8b76/pntd.0007428.g001.jpg

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