SEIR-Based COVID-19 Transmission Model and Inflection Point Prediction Analysis

Q4 Engineering 电子科技大学学报 Pub Date : 2020-05-01 DOI:10.12178/1001-0548.9_2020029
Fan Ruguo, Wang Yi-bo, Luo Ming, Zhang Yingqing, Zhu Chao-ping
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引用次数: 26

Abstract

The COVID-19 has severely affected the country, and people's social and economic lives have been greatly disrupted. Based on the complex network theory, a SEIR dynamic model of the COVID-19 epidemic with a latency period is established in this paper. By setting three scenarios of different incubation periods of the virus, based on national and partial epidemic data, the model parameters are simulated and analyzed for different scenarios. The inflection points of the three cases are predicted, and the results showed that the model analysis is basically consistent with the true performance of the epidemic development. Finally, the paper concludes with specific countermeasures and suggestions for strengthening the prevention and control of the epidemic.
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基于SEIR的新冠肺炎传播模型及拐点预测分析
新冠肺炎严重影响国家,人民的社会经济生活受到极大干扰。本文基于复杂网络理论,建立了新冠肺炎疫情具有潜伏期的SEIR动态模型。通过设置病毒不同潜伏期的三个场景,基于全国和部分疫情数据,对不同场景下的模型参数进行模拟和分析。预测了三个病例的拐点,结果表明,模型分析与疫情发展的真实表现基本一致。最后,文章提出了加强疫情防控的具体对策和建议。
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来源期刊
电子科技大学学报
电子科技大学学报 Engineering-Electrical and Electronic Engineering
CiteScore
1.40
自引率
0.00%
发文量
7228
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