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

Marco Gribaudo, Mauro Iacono and Daniele Manini
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Marco Gribaudo: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy
Mauro Iacono: Dipartimento Matematica e Fisica, Università degli Studi della Campania “Luigi Vanvitelli”, 81100 Caserta, Italy
Daniele Manini: Dipartimento di Informatica, Università degli Studi di Torino, 10149 Torino, Italy

Mathematics, 2021, vol. 9, issue 5, 1-12

Abstract: We applied 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. Our purpose was to show that 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.

Keywords: COVID-19; spatial diffusion model; Markovian Agents (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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