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一种基于小世界网络的新型SEIAR模型,用于评估新冠疫情中的干预措施。

A new SEIAR model on small-world networks to assess the intervention measures in the COVID-19 pandemics.

作者信息

Li Jie, Zhong Jiu, Ji Yong-Mao, Yang Fang

机构信息

School of Economics and Management, Hebei University of Technology, Tianjin 300401, China.

出版信息

Results Phys. 2021 Jun;25:104283. doi: 10.1016/j.rinp.2021.104283. Epub 2021 May 8.

Abstract

A new susceptible-exposed-infected-asymptomatically infected-removed (SEIAR) model is developed to depict the COVID-19 transmission process, considering the latent period and asymptomatically infected. We verify the suppression effect of typical measures, cultivating human awareness, and reducing social contacts. As for cutting off social connections, the feasible measures encompass social distancing policy, isolating infected communities, and isolating hub nodes. Furthermore, it is found that implementing corresponding anti-epidemic measures at different pandemic stages can achieve significant results at a low cost. In the beginning, global lockdown policy is necessary, but isolating infected wards and hub nodes could be more beneficial as the situation eases. The proposed SEIAR model emphasizes the latent period and asymptomatically infected, thus providing theoretical support for subsequent research.

摘要

开发了一种新的易感-暴露-感染-无症状感染-清除(SEIAR)模型来描述新冠病毒传播过程,该模型考虑了潜伏期和无症状感染者。我们验证了诸如培养公众意识和减少社交接触等典型措施的抑制效果。至于切断社会联系,可行的措施包括社交距离政策、隔离受感染社区以及隔离枢纽节点。此外,研究发现,在不同疫情阶段实施相应的抗疫措施能够以低成本取得显著成效。一开始,全球封锁政策是必要的,但随着形势缓和,隔离受感染病房和枢纽节点可能更有益。所提出的SEIAR模型强调了潜伏期和无症状感染者,从而为后续研究提供了理论支持。

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