Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China.
Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China.
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DOI：
10.12688/wellcomeopenres.15842.1
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发表时间：
2020-01-01
影响因子：
--
通讯作者：
Funk, Sebastian
中科院分区：
文献类型：
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作者：
Endo, Akira;Abbott, Sam;Funk, Sebastian
背景：一种新的冠状病毒病(新冠肺炎)暴发现已蔓延至全球多个国家。虽然人与人之间传播的持续传播链表明基本繁殖数R0很高，但二次传播(通常以所谓的超级传播事件为特征)的数量变化可能很大，因为一些国家观察到的本地传播比其他国家更少。方法：我们通过应用数学模型对受影响国家的暴发规模进行观察，量化了新冠肺炎传播中个体水平的差异。我们从世界卫生组织的情况报告中提取了受影响国家的输入性和地方性病例的数量，并应用了一个分支过程模型，其中二次传播的数量假设为负二项分布。结果：我们的模型表明新冠肺炎的传播存在高度的个体水平差异。在目前R0(2-3)的共识范围内，负二项分布的超扩散参数k估计约为0.1(中位数估计为0.1；当R0=2.5时，95%CRI：0.05-0.2)，表明80%的二次传播可能是由一小部分感染者(~10%)引起的。联合估计得到了R0和k的可能范围(95%CRI：R01.4-12；k0.04-0.2)；然而，R0的上限没有得到模型和数据的很好信息，这与先前分布没有显著差异。结论：我们发现高度过度分散的子代分布突出了将干预努力集中在超扩散上的潜在好处。由于大多数受感染的个体不会促进疫情的扩大，因此通过防止相对罕见的超级传播事件，有效繁殖数量可能会大幅减少。
Background: A novel coronavirus disease (COVID-19) outbreak has now spread to a number of countries worldwide. While sustained transmission chains of human-to-human transmission suggest high basic reproduction number R 0, variation in the number of secondary transmissions (often characterised by so-called superspreading events) may be large as some countries have observed fewer local transmissions than others. Methods: We quantified individual-level variation in COVID-19 transmission by applying a mathematical model to observed outbreak sizes in affected countries. We extracted the number of imported and local cases in the affected countries from theWorld Health Organization situation report and applied a branching process model where the number of secondary transmissions was assumed to follow a negative-binomial distribution. Results: Our model suggested a high degree of individual-level variation in the transmission of COVID-19. Within the current consensus range of R 0 (2-3), the overdispersion parameter k of a negative-binomial distribution was estimated to be around 0.1 (median estimate 0.1; 95% CrI: 0.05-0.2 for R0 = 2.5), suggesting that 80% of secondary transmissions may have been caused by a small fraction of infectious individuals (~10%). A joint estimation yielded likely ranges for R 0 and k (95% CrIs: R 0 1.4-12; k 0.04-0.2); however, the upper bound of R 0 was not well informed by the model and data, which did not notably differ from that of the prior distribution. Conclusions: Our finding of a highly-overdispersed offspring distribution highlights a potential benefit to focusing intervention efforts on superspreading. As most infected individuals do not contribute to the expansion of an epidemic, the effective reproduction number could be drastically reduced by preventing relatively rare superspreading events.