This research emphasizes the versatility of cellular automata in studying the spatial and temporal aspects of disease spread. By simulating various intervention strategies, such as vaccination campaigns and social distancing measures, the model provides a platform for assessing their efficacy and optimizing resource allocation. The findings contribute to the development of informed public health policies aimed at curbing the impact of infectious diseases. Mathematical modeling using cellular automata emerges as a valuable approach in unraveling the complexities of infectious disease dynamics. The versatility of this framework allows for a nuanced exploration of diverse scenarios, fostering a deeper understanding of the interplay between individual-level interactions and broader population dynamics. The insights gained from such models hold the potential to guide evidence-based decision-making in the ongoing battle against infectious diseases.