Epidemic Dynamics Model And Vaccination Strategy Based On Information Dissemination

The transmission dynamics of complex networks is an important direction to study the transmission characteristics and internal evolution mechanism of infectious diseases,the discovery of small-world,scale-free and high-clustering characteristics of COVID-19 transmission has significant implications for the spread of cognitive diseases in humans.In addition,compared with the SARS epidemic in 2003,the media and environment on which information dissemination depends have been greatly different during the COVID-19 epidemic,thus changing the characteristics of information dissemination in the past,such as localised information dissemination,relatively fixed audiences and asymmetric access to information.Therefore,the analysis of the characteristics of COVID-19 information transmission,the establishment of interactive transmission model of information and virus,and the understanding of the interaction between the two can provide a basis for formulating immunization strategies to effectively control the spread of the virus.On the other hand,vaccination is a powerful measure to control the further spread and outbreak of COVID-19.Raising awareness of COVID-19 vaccination can stimulate individuals to adopt spontaneous behavioral responses to vaccination,which plays a very important role in expanding vaccination coverage to contain disease outbreaks.Therefore,the analysis of the characteristics of the spread of COVID-19 information,the establishment of the interaction between individual awareness and vaccination,and the analysis of the interaction between the two can provide a basis for the development of vaccination strategies to effectively control the spread of the virus.In view of this,this paper mainly considers the influence of individual contact patterns,disease information dissemination and individual vaccination behavior on virus transmission dynamics in complex networks.Specifically,it includes the following aspects and innovations:(1)Based on the transmission characteristics of COVID-19,the SEIR/V-UA model was proposed to study the interaction between the spread of COVID-19 and the spread of information.In this paper,the dynamic process of the model is studied based on the dynamic equation,the popular stability expression of the model is derived by using the eigenvalues of the Jacobian matrix,and then the model is verified by monte Carlo numerical simulation.In addition,the model combined the COVID-19 epidemic case data and the four-stage strict measures taken by the Chinese government.Through simulation and data fitting,it showed that the existing peak had sufficient goodness of fit,and the number of infected people declined dynamically,highlighting the effectiveness of the measures taken by the Chinese government.(2)According to individual subjective behavior of epidemic severity and vaccine safety,two parameters of information transmission rate and information sensitivity were introduced and SEIR/V model was constructed to study the impact of information transmission on vaccination.The basic regeneration number was calculated by using the method of next-generation matrix.On this basis,the effects of information transmission rate and sensitivity rate on basic reproduction number,vaccination and epidemic control were studied by numerical simulation.In addition,a comparative analysis of the differences in vaccination behavior between China and the United States at various stages was made based on the COVID-19 vaccination data,thus providing a deep understanding of decision-making behavior for COVID-19 vaccination.At the same time,the paper suggests that to address vaccine hesitancy and free-riding,governments need to disseminate accurate vaccine information and provide health education and communication to ease public concerns about vaccine safety.