Norovirus, a highly contagious illness, affects the digestive system and is a common cause of morbidity globally. This study explores the spread of Norovirus using a hybrid SIR model integrated with cellular automata. Our simulation models the transmission and recovery processes in a sampled population under varying probabilities of susceptibility and infection. By employing cellular automata, the model captures localized interactions and provides a visual representation of spatial disease progression. Our model assumes a static population, deterministic state transitions, and fixed durations for infection and immunity. The simulation outcomes demonstrate how initial conditions, such as high susceptibility or infection rates, influence epidemic patterns over time. High susceptibility results in rapid disease spread due to limited initial immunity. Conversely, high initial infection rates lead to rapid saturation with immune individuals, followed by cyclical reinfections as immunity wanes. The findings highlight the interactions between susceptibility, infection, and temporary immunity, offering insights into effective epidemic control measures.

Authors: Amaya Hernandez, Kimberly & Ismail, Najma