The introduction of population migration to SEIAR for COVID-19 epidemic modeling with an efficient intervention strategy
The introduction of population migration to SEIAR for COVID-19 epidemic modeling with an efficient intervention strategy
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DOI：
10.1016/j.inffus.2020.08.002
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发表时间：
2020-12-01
影响因子：
18.6
通讯作者：
Wang, Lin
中科院分区：
文献类型：
--
作者：
Chen, Min;Li, Miao;Wang, Lin
在本文中，我们根据 COVID-19 大流行的特点提出了传染病的数学模型。所提出的增强模型将被称为人口迁移的 SEIR（易感-暴露-感染-恢复）模型，其灵感来自于无症状感染者以及人口流动在病毒传播中发挥的关键作用。模型中比较了干预政策影响下的感染者和基本繁殖数。实验模拟结果显示了社交距离和迁入率对减少感染总数和基本繁殖率的影响。然后，验证了控制迁入人口数量和限制居民流动政策在防止COVID-19大流行传播方面的重要性。
In this paper, we present a mathematical model of an infectious disease according to the characteristics of the COVID-19 pandemic. The proposed enhanced model, which will be referred to as the SEIR (Susceptible-Exposed-Infectious-Recovered) model with population migration, is inspired by the role that asymptomatic infected individuals, as well as population movements can play a crucial role in spreading the virus. In the model, the infected and the basic reproduction numbers are compared under the influence of intervention policies. The experimental simulation results show the impact of social distancing and migration-in rates on reducing the total number of infections and the basic reproductions. And then, the importance of controlling the number of migration-in people and the policy of restricting residents' movements in preventing the spread of COVID-19 pandemic are verified.