COMPARISON OF CONTINUOUS TIME MARKOV CHAIN (CTMC) SIRS AND SIQRS EPIDEMIC MODEL SIMULATION RESULTS ON THE SPREAD OF MONKEYPOX DISEASE

Abstract

The uncontrolled spread of infectious diseases over a long period of time can cause epidemic. The pattern of spread of an infectious disease can be described through a mathematical model called an epidemic model. The development of the SIR epidemic model which assumes that recovered individuals have temporary immunity so that they can be re-infected is called the SIRS epidemic model. Quarantine is an effort to restrict movement to prevent the transmission of disease among individuals in a society. The SIQRS epidemic model is a modification of the SIRS model which assumes a quarantine phase for infected individuals. The SIQRS epidemic model that follows the Markov process and changes in the number of individuals are viewed in continuous time is the SIQRS continuous time Markov chain (CTMC) epidemic model. Monkeypox or monkeypox is an infectious disease that has hit several countries in Central and West Africa. The aims of this research are to explain the CTMC SIQRS epidemic model and compare the simulation results between the CTMC SIQRS and CTMC SIRS epidemic models on the spread of monkeypox. The research’s method is literature study by discussing relevant theories and previous research. The results of this research are the CTMC SIQRS model in the form of transition probabilities. The simulation of CTMC SIRS epidemic model on the spread of monkeypox shows that the end of epidemic occur at days years, whereas in the CTMC SIQRS model, the end of epidemic occur at days years. Therefore, it was concluded that the quarantine phase can speed up the end of the epidemic.