Reproducing the long term predictions from Imperial College CovidSim Report 9
Reproducing the long term predictions from Imperial College CovidSim Report 9
复制标题
重现帝国理工学院 CovidSim 报告 9 的长期预测
DOI：
10.1101/2020.06.18.20135004
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Rice K
中科院分区：
文献类型：
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作者：
Rice K
1摘要我们使用CovidSim代码进行计算，该代码实现了帝国理工学院基于个人的冠状病毒流行模型。使用2020年3月假定的参数化，我们复制了为2020年3月英国政府政策提供参考的预测。我们发现，如果假设R0的初始值较高，CovidSim将对后续数据给出很好的预测。然后，我们进一步调查疫情的整个轨迹，提出以前没有发表过的结果。我们发现，尽管及时的干预措施在降低ICU高峰需求方面非常有效，但拟议的缓解战略都没有将预计的总死亡人数减少到20万人以下。令人惊讶的是，一些干预措施，如学校关闭，预计会增加预计的总死亡人数。
1AbstractWe present calculations using the CovidSim code which implements the Imperial College individual-based model of the COVID epidemic. Using the parameterization assumed in March 2020, we reproduce the predictions presented to inform UK government policy in March 2020. We find that CovidSim would have given a good forecast of the subsequent data if a higher initial value of R0 had been assumed. We then investigate further the whole trajectory of the epidemic, presenting results not previously published. We find that while prompt interventions are highly effective at reducing peak ICU demand, none of the proposed mitigation strategies reduces the predicted total number of deaths below 200,000. Surprisingly, some interventions such as school closures were predicted to increase the projected total number of deaths.