SIMULATION OF THE DISCRETE TIME MARKOV CHAIN SUSCEPTIBLE INFECTED RECOVERED (DTMC SIR) EPIDEMIC MODEL FOR COVID-19 TRANSMISSION IN CENTRAL JAVA - Valentino, Yohanes Felix; Respatiwulan, Respatiwulan; Slamet, Isnandar (FORPIM PTKIS ZONA TAPAL KUDA, 2024)
An epidemic is a situation when an area has a very high number of cases of individuals infected with an infectious disease in a short time frame. Susceptible Infected Recovered (SIR) epidemic models that explain changes in the number of infected individuals in discrete time intervals are called Discrete Time Markov Chain SIR (DTMC SIR) epidemic models. This research aims to discuss the DTMC SIR epidemic model and its simulation of the COVID-19 outbreak. The research methods used are literature reviews and simulation of the dynamics of COVID-19 transmission in Central Java. Central Java's COVID-19 dynamics are analyzed using the obtained DTMC SIR model with a contact rate and cure rate . This research has yielded a DTMC SIR epidemic model that uses transition probabilities to study the dynamics of COVID-19 transmission. The model applied with an initial value of and , and shows that COVID-19 stops when and occurs at . The model was also applied when the contact rate was reduced and increased. The conclusion is that the smaller the contact rate, the longer the epidemic ends and the fewer individuals are infected at the time the epidemic ends.