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与你的社区在一起:集群之间的桥梁引发了 COVID-19 的传播。

Stay with your community: Bridges between clusters trigger expansion of COVID-19.

机构信息

Department of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo, Japan.

Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan.

出版信息

PLoS One. 2020 Dec 3;15(12):e0242766. doi: 10.1371/journal.pone.0242766. eCollection 2020.

Abstract

In this study, the spread of virus infection was simulated using artificial human networks. Here, real-space urban life was modeled as a modified scale-free network with constraints. To date, the scale-free network has been adopted for modeling online communities in several studies. However, in the present study, it has been modified to represent the social behaviors of people where the generated communities are restricted and reflect spatiotemporal constraints in real life. Furthermore, the networks have been extended by introducing multiple cliques in the initial step of network construction and enabling people to contact hidden (zero-degree) as well as popular (large-degree) people. Consequently, four findings and a policy proposal were obtained. First, "second waves" were observed in some cases of the simulations even without external influence or constraints on people's social contacts or the releasing of the constraints. These waves tend to be lower than the first wave and occur in "fresh" clusters, that is, via the infection of people who are connected in the network but have not been infected previously. This implies that the bridge between infected and fresh clusters may trigger a new spread of the virus. Second, if the network changes its structure on the way of infection spread or after its suppression, a second wave larger than the first can occur. Third, the peak height in the time series of the number of infected cases depends on the difference between the upper bound of the number of people each member actually meets and the number of people they choose to meet during the period of infection spread. This tendency is observed for the two kinds of artificial networks introduced here and implies the impact of bridges between communities on the virus spreading. Fourth, the release of a previously imposed constraint may trigger a second wave higher than the peak of the time series without introducing any constraint so far previously, if the release is introduced at a time close to the peak. Thus, overall, both the government and individuals should be careful in returning to society where people enjoy free inter-community contact.

摘要

在这项研究中,使用人工人类网络模拟了病毒感染的传播。在这里,真实空间的城市生活被建模为具有约束的修改后的无标度网络。迄今为止,无标度网络已被用于模拟在线社区中的多项研究。然而,在本研究中,对其进行了修改,以代表人们的社会行为,其中生成的社区受到限制,并反映了现实生活中的时空约束。此外,通过在网络构建的初始步骤中引入多个密集团以及允许人们接触隐藏(零度)和流行(大度数)的人,扩展了网络。因此,得出了四个发现和一个政策建议。首先,在没有外部影响或对人们的社会联系或约束的释放施加约束的情况下,模拟中某些情况下会观察到“第二波”。这些波往往低于第一波,并且出现在“新鲜”集群中,即通过网络中感染但先前未被感染的人的感染。这意味着感染簇和新鲜簇之间的桥梁可能会引发病毒的新传播。其次,如果网络在感染传播过程中或在其抑制后改变其结构,则可能会发生大于第一波的第二波。第三,感染病例数量的时间序列中的峰值高度取决于上限和下限之间的差异每个人实际上遇到的人数和他们在感染传播期间选择见面的人数。这里引入的两种人工网络都观察到了这种趋势,这意味着社区之间桥梁对病毒传播的影响。第四,如果在接近峰值的时间释放先前施加的约束,则释放可能会引发比时间序列峰值更高的第二波,而无需迄今为止引入任何约束。因此,总体而言,政府和个人在恢复人们享受自由社区间接触的社会时都应小心谨慎。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a962/7714156/cbf28a5197a4/pone.0242766.g001.jpg

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