基于SEIR的新冠肺炎传播模型及拐点预测分析

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

新型冠状病毒肺炎疫情对全国造成了严重影响,社会经济生活受到了极大干扰。该文基于复杂网络理论建立了带有潜伏期的COVID-19流行病SEIR动力学模型,通过设定了3种不同病毒潜伏期情景,依据国家及部分地区疫情数据,针对不同情景对模型参数进行仿真分析,对3种情形下的疫情拐点进行了预测。结果表明,模型分析与疫情发展的真实表现基本吻合。最后提出了加强疫情防控的对策建议,对精准做好疫情防控具有较好的指导作用。

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.