Every time there is an epidemic outbreak in some part of the world, billions of dollars are being set aside in anticipation of it spreading to the rest of the world. Various government and non government agencies mobilize resources to prevent and control the expansion of the epidemic by curbing ingress and egress of people from infected location, by launching vaccinations programs and quarantining the suspected. In order to achieve success in their efforts, they need to know what is the window available to them for vaccination, which immigrants should be quarantined and after how long they should anticipate first full blown case.

In this thesis we have developed a software model named "Epimodel" to help those agencies make their preparations. Epimodel simulates an epidemic by mapping the population through seven different states and by tracking the movement population from one state to another using Markov chain. The model has been developed to do the "what-if" analysis by varying the different parameters in an epidemic like rate of contagion, rate of immunization etc. An attempt also has been made to compare the Epimodel with Susceptible Infected Exposed Recovered (SIER) models for outbreak of measles epidemic.