Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020
Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020
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DOI：
10.2807/1560-7917.es.2020.25.17.2000257
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发表时间：
2020-04-30
期刊：
影响因子：
19
通讯作者：
Hens, Niel
中科院分区：
文献类型：
--
作者：
Ganyani, Tapiwa;Kremer, Cecile;Hens, Niel
背景：从冠状病毒病(新冠肺炎)暴发中估计关键传染病参数对于建模研究和指导干预策略至关重要。目的：估计新冠肺炎的世代间隔、序列间隔、症状前传播比例和有效繁殖数。我们证明了基于序列区间估计计算的复制数可能是有偏差的。方法：我们利用新加坡、天津、中国等地暴发疫情的数据，在承认潜伏期分布和潜在传播网络的不确定性的同时，根据症状开始数据估计世代间隔。从这些估计中，我们得到了序列间隔、症状前传播和繁殖数量的比例。结果：平均世代间隔新加坡为5.20天(95%可信区间：3.78~6.78)，天津为3.95天(95%可信区间：3.01~4.91)。新加坡症状前传播比例为48%(95%CRL：32-67)，天津为62%(95%CRL：50-76)。基于世代间隔分布的繁殖次数估计略高于基于序列间隔分布的估计。敏感性分析表明，根据暴发数据估计这些数量需要详细的接触者追踪信息。结论：对症状前传播比例的高估计意味着病例发现和接触者追踪需要辅之以物理距离措施，以控制新冠肺炎暴发。值得注意的是，在收集数据时，检疫和其他遏制措施已经到位，这可能会夸大来自无症状个人的感染比例。
Background: Estimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies. Aim: We estimate the generation interval, serial interval, proportion of presymptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased. Methods: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers. Results: The mean generation interval was 5.20 days (95% credible interval (Crl): 3.78-6.78) for Singapore and 3.95 days (95% Crl: 3.01-4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% Crl: 32-67) for Singapore and 62% (95% Crl: 50-76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information. Conclusion: High estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals.