Construction And Application Of COVID-19 Transmission Model

The COVID-19 pandemic has caused a significant impact on the global economy and disrupted people’s normal rhythms of life.The study of the transmission patterns and prevention strategies of COVID-19 has become a key focus for governments,society,and academic research.However,existing studies on the transmission patterns of COVID-19 have overlooked the impact of population structure on its spread.Against this background,this thesis investigates the characteristics of COVID-19 transmission in a population network and constructs a population network structure model similar to population linkage relationships to study the transmission patterns of COVID-19 and predict its development trends,and proposes prevention and strategies.This thesis investigates the classification of infectious diseases in population transmission on scale-free networks,and analyzes effective strategies for preventing and controlling epidemics based on model parameters.Firstly,based on the characteristics of group infection in the transmission process of COVID-19,the research object is changed from individuals to households.A scale-free network model of SIRS infectious disease is constructed using households as units,and the roles of network centrality and structural holes in disease transmission are analyzed.Quantitatively study the impact of infection rate,cure rate and number of immunized people on infectious disease transmission in SIRS model under scale-free network,and use Net Logo to carry out numerical simulation of infectious disease transmission process.Secondly,in order to study the characteristics of the infectiousness of latent individuals and the existence of asymptomatic infections in the transmission process of COVID-19,the traditional SEIR model is modified by adding new compartments: asymptomatic infected population and isolated population,constructing a more realistic SEAIR model.The model’s validity is verified by simulating transmission trends using end-of-year 2021 epidemic data from Xi’an,and the impact of isolation measures,timely prevention and control,and vaccine distribution on epidemic transmission is analyzed.The research results show that:(1)As key nodes in the network,network central points and structural hole point play an important role in the epidemic transmission process,and controlling such nodes can curb the spread of infectious diseases in the network.(2)Reducing the infection rate,increasing the recovery rate,and early immunity of key nodes can control the development of infectious diseases in the network.(3)The prevention and control measures adopted in China,such as isolation and control,timely regional blockade,and vaccination,can effectively reduce the rate of epidemic spread.This study enriches the model of population structure classification for the COVID-19 epidemic and provides a theoretical basis for optimizing subsequent infectious disease prevention and control strategies.