《Nature,6月8日,Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe》

  • 来源专题:COVID-19科研动态监测
  • 编译者: zhangmin
  • 发布时间:2020-06-09
  • Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe

    Seth Flaxman, Swapnil Mishra, Axel Gandy, H. Juliette T. Unwin, Thomas A. Mellan, Helen Coupland, Charles Whittaker, Harrison Zhu, Tresnia Berah, Jeffrey W. Eaton, Mélodie Monod, Imperial College COVID-19 Response Team, Azra C. Ghani, Christl A. Donnelly, Steven M. Riley, Michaela A. C. Vollmer, Neil M. Ferguson, Lucy C. Okell & Samir Bhatt

    Nature (2020)

    Abstract

    Following the emergence of a novel coronavirus1 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions such as closure of schools and national lockdowns. We study the impact of major interventions across 11 European countries for the period from the start of COVID-19 until the 4th of May 2020 when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. We use partial pooling of information between countries with both individual and shared effects on the reproduction number. Pooling allows more information to be used, helps overcome data idiosyncrasies, and enables more timely estimates.

  • 原文来源:https://www.nature.com/articles/s41586-020-2405-7
相关报告
  • 《Nature,5月4日,Effect of non-pharmaceutical interventions to contain COVID-19 in China》

    • 来源专题:COVID-19科研动态监测
    • 编译者:zhangmin
    • 发布时间:2020-05-05
    • Effect of non-pharmaceutical interventions to contain COVID-19 in China Shengjie Lai, Nick W. Ruktanonchai, Liangcai Zhou, Olivia Prosper, Wei Luo, Jessica R. Floyd, Amy Wesolowski, Mauricio Santillana, Chi Zhang, Xiangjun Du, Hongjie Yu & Andrew J. Tatem Nature (2020) Abstract On March 11, 2020, the World Health Organization declared COVID-19 a pandemic1. The outbreak containment strategies in China based on non-pharmaceutical interventions (NPIs) appear to be effective2, but quantitative research is still needed to assess the efficacy of NPIs and their timings3. Using epidemiological and anonymised human movement data4,5, here we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimated that there were a total of 114,325 COVID-19 cases (interquartile range 76,776 - 164,576) in mainland China as of February 29, 2020. Without NPIs, the COVID-19 cases would likely have shown a 67-fold increase (interquartile range 44 - 94) by February 29, 2020, with the effectiveness of different interventions varying.
  • 《Lancet,6月2日,Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study》

    • 来源专题:COVID-19科研动态监测
    • 编译者:zhangmin
    • 发布时间:2020-06-03
    • Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study Nicholas G Davies, DPhil Adam J Kucharski, PhD * Rosalind M Eggo, PhD * Amy Gimma, MSc Prof W John Edmunds, PhD on behalf of theCentre for the Mathematical Modelling of Infectious Diseases COVID-19 working group † Show footnotes Open AccessPublished:June 02, 2020DOI:https://doi.org/10.1016/S2468-2667(20)30133-X Summary Background Non-pharmaceutical interventions have been implemented to reduce transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been crucial to support evidence-based policy making during the early stages of the epidemic. This study assesses the potential impact of different control measures for mitigating the burden of COVID-19 in the UK. Methods We used a stochastic age-structured transmission model to explore a range of intervention scenarios, tracking 66·4 million people aggregated to 186 county-level administrative units in England, Wales, Scotland, and Northern Ireland. The four base interventions modelled were school closures, physical distancing, shielding of people aged 70 years or older, and self-isolation of symptomatic cases. We also modelled the combination of these interventions, as well as a programme of intensive interventions with phased lockdown-type restrictions that substantially limited contacts outside of the home for repeated periods. We simulated different triggers for the introduction of interventions, and estimated the impact of varying adherence to interventions across counties. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (ie, admission to the intensive care units [ICU]) treatment, and deaths, and compared the effect of each intervention on the basic reproduction number, R0.