SDL-PAND: Pandemic Simulation to Test the Effectiveness of Containment Strategies through Cellular Automata and Intelligent Agents Using Formal Languages

The objective of this project is to develop a functional prototype that enables the evaluation of pandemic containment alternatives. This is based on a graphical conceptualization of models representing the modeling hypotheses. The system is designed to be expandable, allowing for the incorporation of new working hypotheses. It relies on two fundamental sources: data on the pandemic's evolution (which provides a historical perspective) and sensor data (from mobile phones or other devices) offering a current view of the situation. This data will facilitate the definition of forecasting models for pandemic propagation, derived from the analysis of citizens' behavior. The model is also designed to expand its semantics and computational capabilities (for example, through co-simulation) to include traffic management, evacuation models, etc.

The project aims to generate a web application for analyzing alternatives and to define a working methodology. This methodology will establish a common framework for various specialists who must collaborate in defining complex models. This approach will enable a better understanding of the hypotheses governing the models and, consequently, the causality derived from the multidisciplinary knowledge provided by specialists from different areas. Without this framework, these specialists might not otherwise engage in this discussion.