COVID-19 Spatial Diffusion: A Markovian Agent-Based Model

We applied a flexible modeling technique capable of representing dynamics large populations interacting in space and time, namely Markovian Agents, to study the evolution COVID-19 Italy. Our purpose was show that this approach, is based on mean field analysis models, provides good performances describing diffusion phenomena, like COVID-19. The paper describes application approach Italian scenario results are validated against real data available about official documentation model each agent organized similarly what largely established literature Susceptible-Infected-Recovered (SIR) family approaches. Results match main events taken by government their effects.