Modelling transmission and control of the COVID-19 pandemic in Australia.
Modelling transmission and control of the COVID-19 pandemic in Australia.
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DOI：
10.1038/s41467-020-19393-6
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发表时间：
2020-11-11
影响因子：
16.6
通讯作者：
Prokopenko M
中科院分区：
文献类型：
--
作者：
Chang SL;Harding N;Zachreson C;Cliff OM;Prokopenko M
对于旨在控制新冠肺炎传播的各种缓解和抑制战略的相对好处，仍存在持续的争论。在这里，我们报告了基于代理的建模结果，使用的是对澳大利亚正在进行的新冠肺炎大流行的细粒度计算模拟。该型号经过校准，以匹配新冠肺炎传输的关键特征。一个重要的校准结果是有症状病例的年龄相关比例，儿童的这一比例被发现是成年人的五分之一。我们应用该模型比较了几种干预策略，包括限制国际航空旅行、病例隔离、家庭隔离、遵守程度不同的社会距离和学校关闭。人们发现，关闭学校并不能带来决定性的好处，除非伴随着高度的社会距离遵守。我们报告了几个权衡，以及社会疏远依从性水平的一个重要转变，在70%到80%的水平之间，遵从性在90%的水平被发现可以在13-14周内控制疾病，再加上有效的病例隔离和国际旅行限制。关于有效结合控制COIVD-19的战略的争论仍在继续。在这里，作者使用一个基于代理人的模型来量化和比较几种干预策略，并确定在澳大利亚控制疫情所需的最低社会距离遵从性水平。
There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to match key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, with this fraction for children found to be one-fifth of such fraction for adults. We apply the model to compare several intervention strategies, including restrictions on international air travel, case isolation, home quarantine, social distancing with varying levels of compliance, and school closures. School closures are not found to bring decisive benefits unless coupled with high level of social distancing compliance. We report several trade-offs, and an important transition across the levels of social distancing compliance, in the range between 70% and 80% levels, with compliance at the 90% level found to control the disease within 13–14 weeks, when coupled with effective case isolation and international travel restrictions. There is ongoing debate about the effective combination of strategies for COIVD-19 control. Here, the authors use an agent-based model to quantify and compare several intervention strategies, and identify minimal levels of social distancing compliance required to control the epidemic in Australia.
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影响因子：
2.4
作者：
Guisoni, Nara;Loscar, Ernesto S.;Albano, Ezequiel V.
通讯作者：
Albano, Ezequiel V.
影响因子：
4.2
作者：
Cliff, Oliver M.;Harding, Nathan;Prokopenko, Mikhail
通讯作者：
Prokopenko, Mikhail
影响因子：
56.9
作者：
Halloran, ME;Longini, IM;Yang, Y
通讯作者：
Yang, Y
影响因子：
4.3
作者：
Chao DL;Halloran ME;Obenchain VJ;Longini IM Jr
通讯作者：
Longini IM Jr
影响因子：
3.3
作者：
Balcan, Duygu;Goncalves, Bruno;Hu, Hao;Ramasco, Jose J.;Colizza, Vittoria;Vespignani, Alessandro
通讯作者：
Vespignani, Alessandro