近期活動

Abstract
In this talk, we use various methods to our study on calculating the final size distribution, a key measure in epidemic analysis, with a focus on COVID-19. In particular, we investigate both the Markov-Chain SIR Model and the Markov-Chain SIRV Model. We compared three Monte Carlo methods and found that Sellke’s approach works best. We also developed a faster algorithm with time complexity of and memory requirement of that saves over 20% of computation time and needs less memory, making it useful for sensitivity analysis. Using this, our analysis suggests through parameter estimation that COVID-19 will continue to exist and that society will need to coexist with the disease.

We have also studied a two-strain influenza model with quarantine and cross-immunity to examine the dynamics of influenza. Our analysis shows that longer quarantine can destabilize the system. However, once control measures are relaxed, influenza outbreaks are likely to return. This is supported by recent reports of the 2025 flu season in California being the worst in five years. These results demonstrate how epidemic dynamics can be better understood through the framework of final size distributions.