摘要
We investigate the effect of risk estimate on the spread of diseases by the standard susceptible-infected- susceptible （SIS） model. The perception of the risk of being infected is explained as cutting off links among individuals, either healthy or infected, We study this simple dynamics on scale-free networks by analytical methods and computer simulations. We obtain the self-consistency form for the infection prevalence in steady states. For a given transmission rate, there exists a linear relationship between the reciprocal of the density of infected nodes and the estimate parameter. We confirm all the results by sufficient numerical simulations.
We investigate the effect of risk estimate on the spread of diseases by the standard susceptible-infected- susceptible （SIS） model. The perception of the risk of being infected is explained as cutting off links among individuals, either healthy or infected, We study this simple dynamics on scale-free networks by analytical methods and computer simulations. We obtain the self-consistency form for the infection prevalence in steady states. For a given transmission rate, there exists a linear relationship between the reciprocal of the density of infected nodes and the estimate parameter. We confirm all the results by sufficient numerical simulations.
