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用于COVID-19传播的具有未报告感染人群和动态参数的SEIR模型。

SEIR model with unreported infected population and dynamic parameters for the spread of COVID-19.

作者信息

Chen Ziren, Feng Lin, Lay Harold A, Furati Khaled, Khaliq Abdul

机构信息

Department of Mathematics, Middle Tennessee State University, Murfreesboro, TN 37132, USA.

Thompson Machinery Commerce Corporation, 1245 Bridgestone Blvd LaVergne, TN 37086, USA.

出版信息

Math Comput Simul. 2022 Aug;198:31-46. doi: 10.1016/j.matcom.2022.02.025. Epub 2022 Feb 25.

DOI:10.1016/j.matcom.2022.02.025
PMID:35233147
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8876059/
Abstract

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be transmitted through human interaction. In this paper, we present a Piecewise Susceptible-Exposed-Infectious-Unreported-Removed model for infectious diseases and discuss qualitatively and quantitatively. The parameters are explored by mathematical and statistical methods. Numerical simulations of these models are performed on COVID-19 US data and Python is used in the visualization of results. Outbreak factor is generated by piecewise model to explore the future trend of the US pandemic. Several error metrics are given to discuss the accuracy of the models. The main achievement of this paper is to propose the piecewise model and find the relationship between spread of pandemic and mitigation measures to control it by observing the results of numerical simulations. Performance analysis of piecewise model is presented based on COVID-19 data obtained by 'worldmeter'.

摘要

2019冠状病毒病（COVID-19）是一种由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引起的传染病，可通过人际接触传播。在本文中，我们提出了一种用于传染病的分段易感-暴露-感染-未报告-清除模型，并进行了定性和定量讨论。通过数学和统计方法探索参数。这些模型在美国COVID-19数据上进行了数值模拟，并使用Python进行结果可视化。分段模型生成爆发因子以探索美国大流行的未来趋势。给出了几个误差指标来讨论模型的准确性。本文的主要成果是提出了分段模型，并通过观察数值模拟结果，找出了大流行传播与控制其的缓解措施之间的关系。基于从“世界ometers”获得的COVID-19数据，对分段模型进行了性能分析。

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