基于SEIR模型的新型冠状病毒肺炎疫情分析  

EPIDEMIC ANALYSIS OF COVID-19 BASED ON SEIR MODEL

作　　者：须成杰 覃开舟 Xu Chengjie;Qin Kaizhou(Obstetrics&Gynecology Hospital of Fudan University,Shanghai 200090,China)

机构地区：[1]复旦大学附属妇产科医院,上海200090

出　　处：《计算机应用与软件》2021年第12期87-90,共4页Computer Applications and Software

摘　　要：对新型冠状病毒肺炎的传播规律进行研究,为传染病防控提供科学依据。基于每日发布的新冠肺炎确诊人数数据集,采用经典的SEIR(Susceptible-Exposed-Infected-Recovered)传染病动力学模型模拟疫情传播过程;利用最小二乘法对感染系数β和恢复系数γ进行参数估计;通过过滤原始数据集、优化感染人群初始值I_(0)和恢复系数γ等方法进一步提高模型预测的准确率。该方法能够合理地预测疫情确诊人数和疫情拐点,对全国、湖北省确诊人数的预测误差率分别不超过2.04%、1.25%,对于疫情防控具有实用价值。The transmission rule of COVID-19 is studied to provide scientific basis for prevention and control of infectious diseases.Based on the data set of COVID-19 confirmed cases published every day,the classic SEIR epidemic dynamics model was used to simulate the epidemic transmission process.Infection coefficientβand recovery coefficientγof the model were estimated by least square method.The model s prediction accuracy was further improved by filtering the original data set,optimizing the initial value I_(0)of the infected population and the recovery coefficientγ.This method can reasonably predict the number of confirmed cases and the inflection point of epidemic situation.The prediction error rates of the number of confirmed cases in China,Hubei Province are less than 2.04%、1.25%respectively.It has practical value for epidemic prevention and control.

关 键 词：新型冠状病毒肺炎 SEIR模型 疫情分析 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]