Construction And Research Of Infectious Disease Model With Asymptomatic Infection Introduced On Complex Networ

The Novel Corona Virus outbreak in 2019 posed a grave threat to people’s lives,health,and safety.As a new virus,its epidemiological characteristics are different from those of the previous viruses.This virus has a latent period and can transmit during the latent period,and there are many asymptomatic infected people.In order to further reveal the transmission law of the new coronavirus,the main work of this paper is as follows:First,based on the theoretical framework of the classic SEIR model,this dissertation redefines the states and parameters in the model by combining the transmission characteristics of the Novel Corona Virus,asymptomatic infection status,and the impact of time on the state transition of the model.It proposes a new transmission model containing five statuses: "susceptible status,close contact status,asymptomatic infection status,the confirmed status,and removal status." This dissertation used the epidemic data of Hubei province for comparative experiments.Root mean square error and mean absolute percentage error was used as evaluation indexes.The results showed that the SCUIR model significantly improved the fitting accuracy and reduced the fitting error by 8.3%-47.6%compared with the traditional model.In addition,taking the United States and Shanghai as examples,this dissertation simulated different prevention and control measures through quantitative adjustment of parameters,predicted the epidemic’s development trend in the two places,and gave recommendations for epidemic prevention and control decisions based on the prediction results.Second,this dissertation analyzes the propagation law of the SCUIR infectious disease model in ER random network and BA scale-free network.It obtains the basic reproduction number in the two networks.The results show that the main factors affecting the spread of the disease are: the infection rate of the virus,the average density of the population,the confirmed rate of asymptomatic infections,the recovery rate and the mortality rate of confirmed patients.Therefore,we can focus on these four aspects to formulate efficient measures for the actual epidemic prevention and control.Further,this dissertation conducts the verification experiment of the propagation threshold and equilibrium point stability using the numerical simulation method,which verifies the existence of the propagation threshold for disease propagation in complex networks and stable of the equilibrium point in the system.The experimental results show that the virus cannot spread in the network when the basic reproduction number is less than the propagation threshold.When the basic reproduction number is greater than the spreading threshold,the virus will continue to spread in the network.Finally,this dissertation conducts an empirical analysis using the COVID-19 epidemic data in Hubei Province,proving the correctness of the basic reproduction number derived in this dissertation.