An Epidemic Grid Model to Address the Spread of Covid-19: A Comparison Between Italy, Germany and France

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Title: An Epidemic Grid Model to Address the Spread of Covid-19: A Comparison Between Italy, Germany and France
Authors: Signes Pont, María Teresa | Cortés-Plana, José Juan | Mora, Higinio
Research Group/s: Informática Industrial y Redes de Computadores | Arquitecturas Inteligentes Aplicadas (AIA)
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Keywords: COVID-19 | Computational modelling | Space time framework | Multigrid implementation | Update binary rules | Von Neumann and Moore neighborhoods
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: 8-Feb-2021
Publisher: MDPI
Citation: Signes-Pont MT, Cortés-Plana JJ, Mora-Mora H. An Epidemic Grid Model to Address the Spread of Covid-19: A Comparison Between Italy, Germany and France. Mathematical and Computational Applications. 2021; 26(1):14. https://doi.org/10.3390/mca26010014
Abstract: This paper presents a discrete compartmental Susceptible–Exposed–Infected–Recovered/Dead (SEIR/D) model to address the expansion of Covid-19. This model is based on a grid. As time passes, the status of the cells updates by means of binary rules following a neighborhood and a delay pattern. This model has already been analyzed in previous works and successfully compared with the corresponding continuous models solved by ordinary differential equations (ODE), with the intention of finding the homologous parameters between both approaches. Thus, it has been possible to prove that the combination neighborhood-update rule is responsible for the rate of expansion and recovering/death of the disease. The delays (between Susceptible and Asymptomatic, Asymptomatic and Infected, Infected and Recovered/Dead) may have a crucial impact on both height and timing of the peak of Infected and the Recovery/Death rate. This theoretical model has been successfully tested in the case of the dissemination of information through mobile social networks and in the case of plant pests.
URI: http://hdl.handle.net/10045/112739
ISSN: 1300-686X (Print) | 2297-8747 (Online)
DOI: 10.3390/mca26010014
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Peer Review: si
Publisher version: https://doi.org/10.3390/mca26010014
Appears in Collections:INV - I2RC - Artículos de Revistas
INV - AIA - Artículos de Revistas

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