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

• Published in: Mathematical and computational applications Vol. 26; no. 1; p. 14
• Main Authors: Signes-Pont, Maria Teresa, Cortés-Plana, José Juan, Mora-Mora, Higinio
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 2021
• Subjects: Approximation; Asymptomatic; computational modelling; Coronaviruses; COVID-19; Differential equations; Disease; Epidemics; Homology; Information dissemination; Medical research; multigrid implementation; Neighborhoods; Ordinary differential equations; Pandemics; Pests; Propagation; Quarantine; Social networks; space time framework; update binary rules; Von Neumann and Moore neighborhoods; France; Italy; Germany
• ISSN: 2297-8747; 1300-686X; 2297-8747
• DOI: 10.3390/mca26010014

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.