A Universal Physics-Based Model Describing COVID-19 Dynamics in Europe

Yiannis Contoyiannis, Stavros G. Stavrinides, Michael P. Hanias, Myron Kampitakis, Pericles Papadopoulos, Rodrigo Picos and Stelios M. Potirakis
Additional contact information
Yiannis Contoyiannis: Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Stavros G. Stavrinides: School of Science and Technology, International Hellenic University, 57001 Thessaloniki, Greece
Michael P. Hanias: Physics Department, International Hellenic University, 65404 Kavala, Greece
Myron Kampitakis: Major Network Installations Dept, Hellenic Electricity Distribution Network Operator SA, 18547 Athens, Greece
Pericles Papadopoulos: Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece
Rodrigo Picos: Physics Department, University of Balearic Islands, 07122 Palma Majorca, Spain
Stelios M. Potirakis: Department of Electrical and Electronics Engineering, University of West Attica, 12244 Athens, Greece

IJERPH, 2020, vol. 17, issue 18, 1-19

Abstract: The self-organizing mechanism is a universal approach that is widely followed in nature. In this work, a novel self-organizing model describing diffusion over a lattice is introduced. Simulation results for the model’s active lattice sites demonstrate an evolution curve that is very close to those describing the evolution of infected European populations by COVID-19. The model was further examined against real data regarding the COVID-19 epidemic for seven European countries (with a total population of 290 million) during the periods in which social distancing measures were imposed, namely Italy and Spain, which had an enormous spread of the disease; the successful case of Greece; and four central European countries: France, Belgium, Germany and the Netherlands. The value of the proposed model lies in its simplicity and in the fact that it is based on a universal natural mechanism, which through the presentation of an equivalent dynamical system apparently documents and provides a better understanding of the dynamical process behind viral epidemic spreads in general—even pandemics, such as in the case of COVID-19—further allowing us to come closer to controlling such situations. Finally, this model allowed the study of dynamical characteristics such as the memory effect, through the autocorrelation function, in the studied epidemiological dynamical systems.

Keywords: COVID-19; model of the infection diffusion; self-organizing systems; lattice simulations; epidemiology; preventive measures (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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