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.
Deneshkumar et al. (Tue,) studied this question.