title: SIS evolutionary game model and multi-agent simulation of an infectious disease emergency.
abstract: BACKGROUND
  Susceptible-Infected-Susceptible (SIS) infectious disease outbreaks are hazardous events. However, if governments sectors do not adequately supervise such outbreaks, these infectious diseases could spread significantly, resulting in large economic losses and social issues.
  
  
  OBJECTIVE
  In this paper, an evolutionary game and simulation model based on the interactions between strategies and states was proposed, and the game between the public and government sectors and its impact on epidemic situations was discussed.
  
  
  METHODS
  Replicator dynamics equations and the multi-agent model simulation were used for analysis.
  
  
  RESULTS
  According to replicator dynamics equations as well as the multi-agent model simulation, the public all eventually adopted the mobility strategy. In addition, the supervision strength of the governmental sectors was equal to 0 after the strength fluctuated at a low level under the trigger strategy. Ultimately, the entire public shifted to the S state throughout the course of the emergency.
  
  
  CONCLUSIONS
  Social order was maintained and social loss was controlled to a certain extent in the final analysis.
authors.affiliation: School of Management, Wuhan University of Technology, Wuhan, Hubei, China.
authors.forename: Fan
authors.initials: F
authors.lastname: Yang
authors.affiliation: School of Management, Wuhan University of Technology, Wuhan, Hubei, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Yang
authors.affiliation: School of Management, Wuhan University of Technology, Wuhan, Hubei, China.
authors.forename: Xingxing
authors.initials: X
authors.lastname: Liu
authors.affiliation: School of Automation, Wuhan University of Technology, Wuhan, Hubei, China.
authors.forename: Pan
authors.initials: P
authors.lastname: Wang
mesh_terms: D058872:Epidemics; D005716:Game Theory; D006801:Humans; D008962:Models, Theoretical; D017149:Private Sector / Q000458:organization & administration*; D017150:Public Sector / Q000458:organization & administration*
keywords: SIS evolution; cellular automata; evolution game; evolutionarily stable strategy; multi-agent simulation; replicator dynamics equations