Analysis Of SEIR Revision Model And COVID-2019 Wuhan Epidemic

In the course of human development,the repeated appearance and prevalence of infectious diseases have caused tremendous damage to people’s health and the normal operation of society.An unknown case of pneumonia appeared in Wuhan at the end of 2019,and the epidemic quickly spread across the country.At present,the epidemic situation in China is normalized,but the epidemic situation around the world is still severe,and the risk of a rebound of the imported case epidemic still exists.The establishment of a model for the spread of new coronary pneumonia is not only a retrospective restoration of historical events,but also a study of the mechanism and characteristics of virus transmission,which can provide a reference for the prevention and control of the epidemic.The classic differential equation model of infectious diseases cannot fully fit the more complicated dynamical systems of infectious diseases in reality,so it is necessary to establish a new model based on the actual situation on this basis.This article studies the spread of COVID-19 in Wuhan.Considering the incubation period of the disease,the SEIR model is established;considering the government’s isolation measures and the infectivity of patients during the incubation period,the SEIQR model is established;Existed,the SEIAQR model was established.The basic reproduction number is an important indicator in the study of disease transmission models,which represents the transmission capacity of infectious diseases.The basic regeneration number and disease balance point of the model are calculated.The solution of model parameters is the focus of this article.This paper mainly studies two intelligent optimization algorithms,particle swarm algorithm and search algorithm.The particle swarm algorithm is a heuristic algorithm,and the search algorithm is a blind search.The search algorithm runs for a long time and may fall into a local optimum.The particle swarm algorithm has shorter search time,higher accuracy,and avoids falling into the local optimum.The three-stage numerical simulation in this paper uses particle swarm optimization.According to the development of the epidemic,the whole process is divided into three stages: the early stage of the epidemic,the peak of the epidemic,and the end of the epidemic.Numerical simulations are carried out with actual official data,particle swarm algorithm is used to search for unknown parameters in the model,and the ode45 function is used to solve the equations.Calculating the basic reproduction number at each stage,the results show that as the epidemic gradually subsides,the basic reproduction number keeps getting smaller.The sensitivity analysis of the basic reproductive number shows that the inoculation rate and contact rate have the greatest impact on the numerical fluctuation of the basic reproductive number.As the inoculation rate and cure rate increase,the basic reproductive number decreases.Increase,the basic reproduction number increases.At this stage,countries all over the world are promoting vaccination.In order to study the effect of vaccination on epidemic prevention and control,this article evaluates the basic reproductive number through analysis and calculation.It is found that when the vaccination rate is greater than 82.08%,the basic reproductive number is less than 1.The disease will not be epidemic.Through the above analysis,it is concluded that for the prevention and control of the epidemic,measures such as vaccination of susceptible people,isolation of suspected people,social distancing,and wearing masks should be taken.