Estimating undetected Ebola spillovers

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.

公共卫生体系对埃博拉病毒病（EVD）的检测、治疗和预防传播的准备程度对于减轻未来疫情爆发至关重要。疫情的早期检测对于及时响应至关重要，但估计检测率却十分困难，因为未报告的溢出事件和疫情并未产生数据。利用三个独立的、关于西非埃博拉病毒病爆发期间二次感染分布的dataset，在塞拉利昂一个单一地区（西部地区）和几内亚首都科纳克里，我们模拟了实际的疫情规模分布，并将其与报告的疫情规模进行比较。这三个经验分布导致了对检测到的溢出事件和小型疫情比例的估计，分别为26%（范围8–40%，基于完整的疫情数据）、48%（范围39–62%，基于塞拉利昂数据）和17%（范围11–24%，基于几内亚数据）。我们得出结论，自EVD首次被识别以来，至少一半的溢出事件未能得到报告。我们还估计了检测不同规模疫情的概率，这可能是低于10%的单例溢出事件。比较观察过程的模型也表明，检测到疫情的概率并非简单地独立检测任何一个人的累积概率。相反，我们发现任何个体的检测概率高度依赖于病例群的大小。这些发现突显了初级卫生保健和当地病例管理对于在源头检测和遏制未被发现早期阶段疫情的重要性。