Markov SIR Model for Infectious Disease Transmission

This study assesses the effectiveness of transmission models, including the Markov SIR, Gillespie Algorithm, and Reed-Frost Model, in simulating disease trends. Each model was estimated using daily infection and recovery counts and applied to project the progression of active cases. The Markov SIR model demonstrated a strong fit for COVID-19 transmission, particularly in modeling ongoing outbreaks. These findings emphasize its potential for forecasting the spread of infectious diseases, highlighting its adaptability for future outbreak monitoring and response efforts.