Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions
Serial interval of SARS-CoV-2 was shortened over time by nonpharmaceutical interventions
复制标题
通过非药物干预措施，SARS-CoV-2 的序列间隔随着时间的推移而缩短
DOI：
10.1126/science.abc9004
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发表时间：
2020-08-28
期刊：
影响因子：
56.9
通讯作者：
Cowling, Benjamin J.
中科院分区：
文献类型：
--
作者：
Ali, Sheikh Taslim;Wang, Lin;Cowling, Benjamin J.
在流行病学中，从一个感染者开始出现症状到下一个感染者出现症状的连续时间间隔被测量。对于任何特定的感染，假设连续间隔是固定的特征。利用中国大陆冠状病毒病（COVID-19）的有价值的传播对数据，Ali等人注意到，随着非药物干预措施的引入，平均序列间隔发生了变化。于2020年1月中旬，连续的间隔期平均为7. 8天，而于2020年2月初，则减少至平均2. 2天。感染者被识别和隔离得越快，连续间隔时间就越短，病毒传播的机会就越少。序列间隔的变化不仅可以衡量感染控制干预措施的有效性，还可以表明人口免疫力的提高。《科学》，本期第1106页COVID-19的连续间隔分布随着干预措施的变化而变化，并提供了控制有效性的衡量标准。由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引起的新型冠状病毒病2019（COVID-19）的研究报告了流行病学参数的不同估计，包括序列区间分布-即，传播链中连续病例发病之间的时间--以及生育数量。通过编制中国大陆传播对的线路列表数据库，我们发现COVID-19的平均连续间隔在一个月内（2020年1月9日至2月13日）从7. 8天大幅缩短至2. 6天。这种变化是由加强非药物干预，特别是病例隔离驱动的。我们还表明，使用实时估计的序列间隔允许随时间的变化提供了更准确的估计繁殖数量比使用传统的固定序列间隔分布。这些发现可以提高我们评估传播动态、预测未来发病率和估计控制措施影响的能力。
From cough to splutter In epidemiology, serial intervals are measured from when one infected person starts to show symptoms to when the next person infected becomes symptomatic. For any specific infection, the serial interval is assumed to be a fixed characteristic. Using valuable transmission pair data for coronavirus disease (COVID-19) in mainland China, Ali et al. noticed that the average serial interval changed as nonpharmaceutical interventions were introduced. In mid-January 2020, serial intervals were on average 7.8 days, whereas in early February 2020, they decreased to an average of 2.2 days. The more quickly infected persons were identified and isolated, the shorter the serial interval became and the fewer the opportunities for virus transmission. The change in serial interval may not only measure the effectiveness of infection control interventions but may also indicate rising population immunity. Science, this issue p. 1106 The serial interval distribution of COVID-19 changes in response to interventions and offers a measure for effectiveness of control. Studies of novel coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have reported varying estimates of epidemiological parameters, including serial interval distributions—i.e., the time between illness onset in successive cases in a transmission chain—and reproduction numbers. By compiling a line-list database of transmission pairs in mainland China, we show that mean serial intervals of COVID-19 shortened substantially from 7.8 to 2.6 days within a month (9 January to 13 February 2020). This change was driven by enhanced nonpharmaceutical interventions, particularly case isolation. We also show that using real-time estimation of serial intervals allowing for variation over time provides more accurate estimates of reproduction numbers than using conventionally fixed serial interval distributions. These findings could improve our ability to assess transmission dynamics, forecast future incidence, and estimate the impact of control measures.