《 Lancet,3月25日,The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study》

  • 来源专题:COVID-19科研动态监测
  • 编译者: xuwenwhlib
  • 发布时间:2020-03-26
  • The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study

    Kiesha Prem, PhD *Yang Liu, PhD *Timothy W Russell, PhD,Adam J Kucharski, PhD,Rosalind M Eggo, PhD,Nicholas Davies, PhD

    Published:March 25, 2020DOI:https://doi.org/10.1016/S2468-2667(20)30073-6

    Summary

    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.

  • 原文来源:https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(20)30073-6/fulltext#
相关报告
  • 《MedRxiv,3月12日,The effect of control strategies that reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China》

    • 来源专题:COVID-19科研动态监测
    • 编译者:zhangmin
    • 发布时间:2020-03-13
    • The effect of control strategies that reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China Kiesha Prem, Yang Liu, Tim Russell, Adam J Kucharski, Rosalind M Eggo, Nicholas Davies, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Mark Jit, Petra Klepac doi: https://doi.org/10.1101/2020.03.09.20033050 Abstract BACKGROUND: In December 2019, a novel strain of SARS-CoV-2 emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures and efforts in response to the outbreak. METHODS: We quantified the effects of control measures on population contact patterns in Wuhan, China, to assess their effects on the progression of the outbreak. We included the latest estimates of epidemic parameters from a transmission model fitted to data on local and internationally exported cases from Wuhan in the age-structured epidemic framework. Further, we looked at the age-distribution of cases. Lastly, we 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. *注,本文为预印本论文手稿,是未经同行评审的初步报告,其观点仅供科研同行交流,并不是结论性内容,请使用者谨慎使用.
  • 《Lancet,3月25日,COVID-19: extending or relaxing distancing control measures》

    • 来源专题:COVID-19科研动态监测
    • 编译者:xuwenwhlib
    • 发布时间:2020-03-26
    • COVID-19: extending or relaxing distancing control measures Tim Colbourn Open AccessPublished:March 25, 2020DOI:https://doi.org/10.1016/S2468-2667(20)30072-4 The study by Kiesha Prem and colleagues1 in The Lancet Public Health is crucial for policy makers everywhere, as it indicates the effects of extending or relaxing physical distancing control measures on the coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China. Prem and colleagues1 use observed data on COVID-19 spread from Wuhan and finely detailed empirical data from China on the number of contacts per day by age group at home, school, work, and other locations.2 Their model indicates that if the physical distancing measures begun in late January, 2020, in Wuhan are gradually relaxed in March, the virus could start to resurge 3 months later in June, and generate a second peak 5 months later at the end of August, 2020. However, if measures were relaxed a month later in April, 2020, the resurgence would start an additional 2 months later, in August, 2020, and peak in October. Their projections suggest that an additional month of physical distancing measures (or other methods, such as widespread testing) could buy 2 additional months before such measures would have to be reinstated to prevent the resurgence of the epidemic toward health-care system overload. This potential resurgence mirrors that shown to be likely in the model developed by Ferguson and colleagues.3