Inference of the SARS-CoV-2 generation time using UK household data.
Inference of the SARS-CoV-2 generation time using UK household data.
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DOI：
10.7554/elife.70767
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发表时间：
2022-02-09
期刊：
影响因子：
7.7
通讯作者：
Thompson RN
中科院分区：
文献类型：
--
作者：
Hart WS;Abbott S;Endo A;Hellewell J;Miller E;Andrews N;Maini PK;Funk S;Thompson RN
世代时间的分布(个人感染和传播病毒之间的间隔)表征了SARS-CoV-2感染期间传播风险的变化。推断世代时间分布对于规划和评估公共卫生措施至关重要。我们先前开发了一种估计生成时间的机械性方法，与现有模型(Hart等人，2021年)相比，该方法与新冠肺炎大流行前几个月(2019年12月至2020年3月)的数据提供了更好的拟合。然而，基于大流行后期的数据，几乎没有对发生时间的估计。在这里，使用2020年3月至11月在英国进行的一项家庭研究的数据，我们提供了对世代时间的最新估计。我们既考虑了一种常用的方法，其中假设传播风险与症状发展无关，也考虑了我们的机制模型，在该模型中，传播和症状明确地联系在一起。假设传播和症状独立，我们估计的平均世代时间(4.2天，95%可信区间3.3-5.3天)与其他国家以前的估计相似，但标准差更高(4.9天，3.0-8.3天)。使用我们的机械方法，我们估计了更长的平均世代时间(5.9天，5.2-7.0天)和类似的标准差(4.8天，4.0-6.3天)。除了使用整个研究期间的数据估计世代时间外，我们还考虑了世代时间是否随时间变化。这两个模型都表明，与前几个月相比，2020年9月至11月的平均世代时间更短。由于SARS-CoV-2的发生时间似乎正在改变，有必要进一步收集和分析数据，以继续监测正在进行的传播，并为未来的公共卫生政策决策提供信息。
The distribution of the generation time (the interval between individuals becoming infected and transmitting the virus) characterises changes in the transmission risk during SARS-CoV-2 infections. Inferring the generation time distribution is essential to plan and assess public health measures. We previously developed a mechanistic approach for estimating the generation time, which provided an improved fit to data from the early months of the COVID-19 pandemic (December 2019-March 2020) compared to existing models (Hart et al., 2021). However, few estimates of the generation time exist based on data from later in the pandemic. Here, using data from a household study conducted from March to November 2020 in the UK, we provide updated estimates of the generation time. We considered both a commonly used approach in which the transmission risk is assumed to be independent of when symptoms develop, and our mechanistic model in which transmission and symptoms are linked explicitly. Assuming independent transmission and symptoms, we estimated a mean generation time (4.2 days, 95% credible interval 3.3–5.3 days) similar to previous estimates from other countries, but with a higher standard deviation (4.9 days, 3.0–8.3 days). Using our mechanistic approach, we estimated a longer mean generation time (5.9 days, 5.2–7.0 days) and a similar standard deviation (4.8 days, 4.0–6.3 days). As well as estimating the generation time using data from the entire study period, we also considered whether the generation time varied temporally. Both models suggest a shorter mean generation time in September-November 2020 compared to earlier months. Since the SARS-CoV-2 generation time appears to be changing, further data collection and analysis is necessary to continue to monitor ongoing transmission and inform future public health policy decisions.