Research And Application Of Stochastic SEIR Model In COVID-19

At the beginning of 2020,the COVID-19 epidemic is spreading rapidly around the world,posing severe challenges to human survival,development,production and life.Up to now,the COVID-19 epidemic has been basically under control in China,but imported cases and the resumption of work and production at home still put pressure on the prevention and control work.Therefore,it is of great significance to establish models to simulate the transmission characteristics and development rules of COVID-19 and to find effective measures for epidemic prevention and control.In this paper,based on the data related to COVID-19 reported by Hubei Provincial Health Commission from January 28,2020 to April 26,2020,we preprocessed the data and established classical SIR model,random SIR model,classical SEIR model and random SEIR model respectively,and estimated the dynamic parameters of the model.Nonparametric Wilcoxon-Mann-Whitney rank-sum test was used to test whether there was significant difference between the model fitting data and the real data.Compared with THE SIR model,the stochastic SEIR model is more consistent with the characteristics of COVID-19,and it takes into account the interference of random factors on the spread of COVID-19 in reality,which is more consistent with the spread of COVID-19.Therefore,the stochastic SEIR model is selected as the optimal infectious disease dynamics model to describe the development of COVID-19.Comparing the least square method and the weighted least square method to estimate the parameters of the random SEIR model,it is found that the least square method has better estimation effect,so the least square method is chosen to estimate the parameters of the model.The transmission data of six large-scale outbreaks in China between 2020 and 2021 were collected and verified by the random SEIR model.The accuracy of the method selected in this paper was verified by actual data.Based on the established stochastic SEIR model,this paper uses the model to estimate the important threshold that can determine whether the outbreak will continue.The basic regeneration number of COVID-19 is 5.82.Based on the stochastic SEIR model,the data that had been reported inaccurately due to limited detection capacity and insufficient attention to COVID-19 were repaired.Furthermore,in this paper,the SEIQR model with isolation chamber was established to discuss the change of epidemic development trend under different isolation intensity and delayed implementation of isolation measures,and to prove the effectiveness of epidemic prevention and control.At the same time,considering the current vaccine protection rate in China,the SEIVR model with vaccination warehouse was established to discuss the changes of epidemic development under different vaccination rates,so as to provide theoretical basis for the country to encourage active vaccination of all staff.