Computational Experiment on the Evolution of Social Group Behavior in Major Public Health Emergencies:A Case Study of COVID-19 Epidemic
Scientific understanding of social group behavior and its evolution in major public health emergencies is the key way to improve the government's social governance ability.Firstly,a cellular automata(CA)model for the evolution of group behavior is constructed by describing the state,behaviors and evolution rules of differ-ent groups under the COVID-19 epidemic.Secondly,the evolution of group behavior under different scenarios is simulated by using the computational experimental method.Finally,according to the simulation results,the corresponding social governance countermeasures are put forward.The results indicated that:In view of the scientific social governance of the evolution of group behavior in the transmission of COVID-19,the spread of the epidemic can be effectively controlled.The main factors affecting the evolution of group behavior include initial infection rate,infection rate,incubation period and public opinion.Among them,the initial infection rate,infection rate and public opinion have a significant impact on the evolution of group behavior,while the effect of incubation period on the evolution of group behavior is not significant.Reducing the initial infection rate and infection rate can directly reduce the number of infected people,encourage individuals to take positive behavior,and guide the evolution of group behavior to positive behavior.If the management of public opinion is improper and most individuals take zero or negative behaviors,negative group behaviors will emerge in the social system,and almost all the society will be infected,which will increase the difficulty of social governance,and vice versa.Therefore,scientifically guiding the behavior of social groups and strengthening the social governance capacity of the government are important ways to effectively control the spread of COVID-19.
COVID-19evolution of group behaviorsocial governancecomputational experiment
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NSTL
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