The paper “COVID-19 Spatial Diffusion: A Markovian Agent-Based Model”, authored by Marco Gribaudo (Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano), Mauro Iacono (Dipartimento Matematica e Fisica, Università degli Studi della Campania “Luigi Vanvitelli”) e Daniele Manini (Dipartimento di Informatica, Università degli Studi di Torino), has been issued on the international scientific journal Mathematics.
The paper proposes a flexible modeling technique capable of representing dynamics of large populations interacting in space and time, namely Markovian Agents, to study the evolution of COVID-19 in Italy. According to the authors, this modeling approach, that is based on mean field analysis models, provides good performances in describing the diffusion of phenomena, like COVID-19. The paper describes the application of this modeling approach to the Italian scenario and results are validated against real data available about the Italian official documentation of the diffusion of COVID-19. The model of each agent is organized similarly to what largely established in literature in the Susceptible-Infected-Recovered (SIR) family of approaches. Results match the main events taken by the Italian government and their effects.
The paper is available for free on the open access platform MDPI.