Effect of school closures on mortality from coronavirus disease 2019: old and new predictions.
Effect of school closures on mortality from coronavirus disease 2019: old and new predictions.
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DOI：
10.1136/bmj.m3588
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发表时间：
2020-10-07
期刊：
影响因子：
--
通讯作者：
Ackland GJ
中科院分区：
文献类型：
--
作者：
Rice K;Wynne B;Martin V;Ackland GJ
复制并分析英国 2020 年 3 月做出封锁决定时英国政策制定者可获得的信息。使用 CovidSim 代码进行独立计算，该代码实现了伦敦帝国理工学院基于个人的模型，并将 2020 年 3 月提供的数据应用于 2019 年冠状病毒病 (covid-19) 疫情。考虑 covid-19 在英国和北爱尔兰传播的模拟。大约 7000 万模拟人物尽可能接近真实的英国人口统计、地理和社会行为。复制向英国政府紧急情况科学咨询小组 (SAGE) 报告的 covid-19 疫情摘要数据，并对未发表的结果进行详细研究，特别是学校停课的影响。如果以 covid-19 的复制数约为 3.5 进行初始化，CovidSim 模型将对后续数据进行良好的预测。该模型预测，学校关闭和年轻人隔离将增加死亡总数，尽管会推迟到第二波及后续浪潮。这项研究的结果表明，及时的干预措施在减少重症监护病房 (ICU) 床位的高峰需求方面非常有效，但也会延长流行病的时间，在某些情况下会导致更多的长期死亡。发生这种情况是因为与 covid-19 相关的死亡率高度偏向于老年群体。在缺乏有效的疫苗接种计划的情况下，英国提出的任何缓解策略都无法将预计的死亡总人数降低到 200 万人以下。2020 年 3 月曾预测，为应对 covid-19，广泛的封锁而不是重点保护社会最脆弱的成员，将减少对 ICU 床位的直接需求，但长期而言，代价是更多的死亡。在 covid-19 流行病中拯救生命的最佳策略不同于针对具有不同死亡率年龄特征的流感流行病的预期策略。
To replicate and analyse the information available to UK policymakers when the lockdown decision was taken in March 2020 in the United Kingdom. Independent calculations using the CovidSim code, which implements Imperial College London’s individual based model, with data available in March 2020 applied to the coronavirus disease 2019 (covid-19) epidemic. Simulations considering the spread of covid-19 in Great Britain and Northern Ireland. About 70 million simulated people matched as closely as possible to actual UK demographics, geography, and social behaviours. Replication of summary data on the covid-19 epidemic reported to the UK government Scientific Advisory Group for Emergencies (SAGE), and a detailed study of unpublished results, especially the effect of school closures. The CovidSim model would have produced a good forecast of the subsequent data if initialised with a reproduction number of about 3.5 for covid-19. The model predicted that school closures and isolation of younger people would increase the total number of deaths, albeit postponed to a second and subsequent waves. The findings of this study suggest that prompt interventions were shown to be highly effective at reducing peak demand for intensive care unit (ICU) beds but also prolong the epidemic, in some cases resulting in more deaths long term. This happens because covid-19 related mortality is highly skewed towards older age groups. In the absence of an effective vaccination programme, none of the proposed mitigation strategies in the UK would reduce the predicted total number of deaths below 200 000. It was predicted in March 2020 that in response to covid-19 a broad lockdown, as opposed to a focus on shielding the most vulnerable members of society, would reduce immediate demand for ICU beds at the cost of more deaths long term. The optimal strategy for saving lives in a covid-19 epidemic is different from that anticipated for an influenza epidemic with a different mortality age profile.
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DOI：
10.1073/pnas.0706849105
发表时间：
2008-03-25
影响因子：
11.1
作者：
Halloran, M. Elizabeth;Ferguson, Neil M.;Cooley, Philip
通讯作者：
Cooley, Philip
影响因子：
64.8
作者：
Ferguson, NM;Cummings, DAT;Burke, DS
通讯作者：
Burke, DS
减轻流感大流行的策略。
影响因子：
64.8
作者：
Ferguson NM;Cummings DA;Fraser C;Cajka JC;Cooley PC;Burke DS
通讯作者：
Burke DS
影响因子：
64.8
作者：
Flaxman, Seth;Mishra, Swapnil;Bhatt, Samir
通讯作者：
Bhatt, Samir