Statistical model checker for Epidemics Progression on Complex Network

In this thesis uses the susceptible-infected-recovered (SIR) model to show how the epi-demic spread over the complex network, which can be used for the early prediction for epidemic spread, so we can determine the proper cause of the action. The propagation of epidemics on a small-world network with and without immunization has been shown. Immunization helps to control the outbreaks of the epidemics. Our approach is to using the modeling the SIR model with Discrete event simulation which is one way to simulate the complex systems, which allows us to ask the interesting queries regarding how the epidemics spread over the time, at what time will be the peak time for spread and many more. In this work we uses the one of java lib. i.e. Graph Stream for our purpose to generate the small world network and we have also uses MultiVesta tool which is a Statical model checker tool. This work can be use in application of modeling the human disease as well as modeling the computer malware because it has similarity with spreading the human disease as the computer viruses