Markovian modelling of transmission of tuberculosis cases in Indonesia

Indonesia is ranked as the second highest contributor to global cases of Tuberculosis (TB), which requires a focused approach to the transmission of tuberculosis within the country. This research aims to model and analyze the spread of TB cases in Indonesia. This research uses a discrete-time Markov chain with S-I-T-R-D states and Maximum Likelihood Estimation to model the transmission of TB cases. This research provides innovation in modeling the transmission of TB cases with a more complex model by including the possibility of relapse and treatment outcomes using historical data of TB cases in Indonesia. This research produces a matrix of transition probabilities for each state, first transition probabilities, steady state states, expected times for each transition and lifetime.