A Node-based SIRS Epidemic Model With Infective Media On Networks

In this thesis,we focus on the node-based epidemic modeling for complex networks,introduce the propagation medium and propose a node-based SusceptibleInfected-Recovered-Susceptible(SIRS)epidemic model with infective media.Theoretical investigations show that the endemic equilibrium is globally asymptotically stable.Numerical examples of three typical network structures also verify the theoretical results.Furthermore,comparison between network node degree and its infected percents implies that there is a strong positive correlation between both,namely,the node with bigger degree is infected with more percents.Finally,we discuss the impact of the epidemic spreading rate of media as well as the effective recovered rate on the network average infected state.Theoretical and numerical results show that(1)network average infected percents go up(down)with the increase of the infected rate of media(the effective recovered rate);(2)the infected rate of media has almost no influence on network average infected percents for the fully-connected network and NW small-world network;(3)network average infected percents decrease exponentially with the increase of the effective recovered rate,implying that the percents can be controlled at low level by an appropriate large effective recovered rate.