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使用网络元种群模型研究控制新冠病毒传播措施的时间、强度和持续时间。

Investigating time, strength, and duration of measures in controlling the spread of COVID-19 using a networked meta-population model.

作者信息

Zhang Jiang, Dong Lei, Zhang Yanbo, Chen Xinyue, Yao Guiqing, Han Zhangang

机构信息

School of Systems Science, Beijing Normal University, Beijing, 100875 China.

School of Earth and Space Sciences, Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing, 100871 China.

出版信息

Nonlinear Dyn. 2020;101(3):1789-1800. doi: 10.1007/s11071-020-05769-2. Epub 2020 Jun 27.

Abstract

Policy makers around the world are facing unprecedented challenges in making decisions on when and what degrees of measures should be implemented to tackle the COVID-19 pandemic. Here, using a nationwide mobile phone dataset, we developed a networked meta-population model to simulate the impact of intervention in controlling the spread of the virus in China by varying the effectiveness of transmission reduction and the timing of intervention start and relaxation. We estimated basic reproduction number and transition probabilities between health states based on reported cases. Our model demonstrates that both the time of initiating an intervention and its effectiveness had a very large impact on controlling the epidemic, and the current Chinese intense social distancing intervention has reduced the impact substantially but would have been even more effective had it started earlier. The optimal duration of the control measures to avoid resurgence was estimated to be 2 months, although would need to be longer under less effective controls.

摘要

世界各地的政策制定者在决定何时以及应实施何种程度的措施来应对新冠疫情方面面临着前所未有的挑战。在此,我们利用全国手机数据集开发了一个网络化的元种群模型,通过改变传播减少的有效性以及干预开始和放松的时间,来模拟干预措施在中国控制病毒传播的影响。我们根据报告病例估计了基本再生数和健康状态之间的转移概率。我们的模型表明,启动干预的时间及其有效性对控制疫情都有非常大的影响,当前中国严格的社会距离干预措施已大幅降低了疫情影响,但如果更早开始实施,效果会更好。为避免疫情反弹,控制措施的最佳持续时间估计为2个月,不过在效果较差的控制措施下可能需要更长时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce8b/7320847/b7ac191dab30/11071_2020_5769_Fig1_HTML.jpg

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