The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study
The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study
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DOI：
10.1016/s2468-2667(20)30073-6
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发表时间：
2020-05-01
影响因子：
50
通讯作者：
Klepac, Petra
中科院分区：
文献类型：
--
作者：
Prem, Kiesha;Liu, Yang;Klepac, Petra
背景2019年12月，一种新型冠状病毒--严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）在中国武汉出现。从那时起，武汉市采取了前所未有的措施来应对疫情，包括延长学校和工作场所的关闭时间。我们的目的是评估物理距离措施对COVID-19疫情进展的影响，希望为世界其他地区提供一些见解。方法为了研究人口混合的变化如何影响武汉的疫情进展，我们在武汉使用了合成的特定地点接触模式，并在学校关闭，工作场所延长关闭，减少了整个社区的混合。使用这些矩阵和武汉疫情流行病学参数的最新估计，我们使用年龄结构的暴露-感染-移除（SEIR）模型模拟了武汉疫情的持续轨迹。我们在一个年龄结构流行病框架中，将来自传播模型的流行病参数的最新估计值与武汉本地和国际输出病例的数据进行了拟合，并调查了病例的年龄分布。我们还通过允许人们以分阶段的方式重返工作岗位来模拟解除控制措施，并研究了在潜在疫情的不同阶段重返工作岗位的影响（在3月或4月初）。结果我们的预测表明，物理距离措施是最有效的，如果交错返回工作是在4月初;这使2020年年中和2020年底的感染人数中位数分别减少了92%（IQR 66 - 97）和24%（13 - 90）。将这些措施持续到4月有好处，可以推迟和降低高峰的高度，2020年底的流行病规模中位数，并为医疗保健系统提供更多的时间来扩大和应对。然而，物理距离措施的模拟效果因传染性持续时间和学生在疫情中的作用而异。解读对武汉活动的限制如果维持到4月，可能有助于推迟疫情高峰。我们的预测表明，过早和突然取消干预可能会导致更早的第二个高峰，这可能会通过逐步放松干预来消除。然而，我们的分析存在局限性，包括R-0估计值和传染性持续时间的较大不确定性。版权所有（C）2020作者。爱思唯尔有限公司出版
Background In December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world.Methods To examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April).Findings Our projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66-97) and 24% (13-90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic.Interpretation Restrictions on activities in Wuhan, if maintained until April, would probably help to delay the epidemic peak. Our projections suggest that premature and sudden lifting of interventions could lead to an earlier secondary peak, which could be flattened by relaxing the interventions gradually. However, there are limitations to our analysis, including large uncertainties around estimates of R-0 and the duration of infectiousness. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.