基于动态SEIR模型的小规模疫情预测  

Prediction of Small-scale Epidemic Situation Based on Dynamic SEIR Model

作　　者：李瑞沂 王瑞 冯和棠 曹沛根 黄猛 LI Ruiyi;WANG Rui;FENG Hetang;CAO Peigen;HUANG Meng(School of Information Engineering,Institute of Disaster Prevention Technology,Langfang 065201,China)

机构地区：[1]防灾科技学院信息工程学院,河北廊坊065201

出　　处：《现代信息科技》2023年第23期146-150,共5页Modern Information Technology

基　　金：防灾科技学院2022大学生创新创业项目(202211775011)。

摘　　要：基于动态SEIR模型的小规模疫情数据预测研究可为目前社会各界的生活安排、工作规划等提供重要的参考依据。传统的SEIR模型中感染率是恒定的,但在新冠病毒传播情况下,接触率随时间而变化,进而预测结果受到影响。同时现有的大规模疫情数据受外界因素影响较大,传统的SEIR模型无法完全适用于复杂情况下的疫情预测,故提出一种基于动态的SEIR模型的预测方法。将接触率通过逻辑函数计算得出,对小规模疫情数据进行预测,该模型的构建与研究具有一定的应用价值。The prediction research of small-scale epidemic situation data based on dynamic SEIR model can provide an important reference for the living arrangements and work planning of all sectors of society.In the traditional SEIR model,the infection rate is constant,but in the case of COVID-19 transmission,the exposure rate changes with time,and then the prediction results are affected.At the same time,the existing large-scale epidemic situation data are greatly affected by external factors,and the traditional SEIR model cannot be fully applied to the epidemic situation prediction in complex situations.Therefore,a prediction method based on dynamic SEIR model is proposed.The exposure rate is calculated by logical function to predict small-scale epidemic situation data.The construction and research of this model has certain application value.

关 键 词：动态SEIR模型 传染病模型 趋势分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]