Simulation Of COVID-19 Epidemic Prevention And Control Based On Multi-agent

The COVID-19 virusis a global public health crisis,and the prevention and control of the epidemic is the top priority of the governments and people of the world.In the process of the spread of the new coronavirus,complex human factors and the interaction of the environment have made the problem changeable.Computer technology and multi-agent modeling can be used to explore the complex interaction and influence between human and environmental factors during the spread of the new coronavirus.Multi-agent simulation can simulate and predict the state feedback and change process of the new coronavirus under multiple influencing factors such as complexity,nonlinearity and interactivity.The various types of residents and medical staff in the new coronavirus transmission system are abstracted into entities.According to the real characteristics of various residents and medical staff,the attributes and behaviors of various entities are abstracted,and then each simulation entity is described by an agent.The agent interacts and learns according to its own attributes and behavior rules,thereby establishing a multi-agent model(Agent-Based Model,ABM).Therefore,this study constructed a multi-agent simulation model for COVID-19 virus prevention and control based on real virus spread data during the epidemic in Taiyuan City,Shanxi Province.The model uses multi-agent simulation modeling technology to abstract the attributes and behaviors of four types of resident agents: government agents,hospital agents,healthy persons,latent persons,diseased persons,and quarantined persons,and studied the interaction between agents of different ages.Interactive infection and state transition rules.The model also conducts simulation experiments for different medical conditions and prevention and control measures issued by the government to obtain the infection status of residents of different age groups,and explores the law of the spread of the new coronavirus with changes in environmental temperature.The behaviors of residents in the age group and government decision-making provide scientific support for decision-making.