Computer Science ›› 2016, Vol. 43 ›› Issue (Z6): 64-67.doi: 10.11896/j.issn.1002-137X.2016.6A.014

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SIRS Epidemic Model and its Threshold Based on State Transition Probability

GU Hai-jun, JIANG Guo-ping and XIA Ling-ling   

  • Online:2018-12-01 Published:2018-12-01

Abstract: For SIRS (Susceptible-Infected-Removed-Susceptible) epidemic model,we used the method of state transition probability to study the SIRS epidemic process through calculating the probability in each state over time.First,we established state probability equations to describe the probability in susceptible state,infection state and immune state of each node at each moment.Then,we derived the epidemic threshold of SIRS model by the theory of steady state analysis.Finally,using the Monte Carlo method,we analyzed and simulated the epidemic threshold in both homogeneous network and heterogeneous network.Compared with the traditional mean-field method,the simulation results show that the threshold obtained by the state probability equations is much closer to real Monte Carlo value and has no relations with the immune deficiency rate.

Key words: Epidemic threshold,Probability equations,SIRS model,Mean-field method

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