Application of Markov Chains in Epidemiology

Recently, mathematical models are used to describe epidemic disease spread. Epidemic disease transmission outbreaks are modeled among Markov chain in order to monitor and control epidemic spreads. In this paper SIS (Susceptible- Infections- Susceptible) and SIR (Susceptive- Infectious- Recovered) models with discrete Markov chain are represented. These models are developed to see how the number of infected individuals changes over time. In this paper a review of a discrete model of Markov chain for describing epidemic spread is represented. The aim of this review is to explain the formulation of SIR and SIS epidemic models for the spread of infectious disease and to estimate transmission rate and recovery rates