MODELING AND SIMULATION OF DISEASE SPREAD BASED ON CELLULAR AUTOMATA

This paper presents a model of disease spread in a closed system, based on the characteristics of multiagent systems, the SIR (Susceptible-Infectious-Recovered) model and the theory of cellular automata. The aim of this study is to investigate specific aspects of disease spread, such as spatial disposition, individual response to infection, and probability of contagion, which are often treated in a superficial manner in other epidemiological models. By integrating these approaches, the proposed model provides a robust tool to aid decision-making in public health policies and disease control strategies. The computational implementation is carried out with simulations that allow the exploration of different scenarios, emphasizing the influence of spatial distribution on the spread of the fictitious disease. This approach enables the analysis of different intervention and control strategies, helping to make more effective decisions to mitigate the spread of diseases in populations or in other contexts.