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

Area of Science:

• Epidemiology
• Complex Systems
• Mathematical Modeling

Background:

• Self-organization is a fundamental natural process observed across various systems.
• Understanding epidemic dynamics is crucial for public health interventions, especially during pandemics like COVID-19.

Purpose of the Study:

• To introduce a novel self-organizing model for simulating diffusion on a lattice.
• To validate the model's efficacy by comparing its simulation results with real-world COVID-19 spread data in European countries.

Main Methods:

• Development of a novel self-organizing lattice diffusion model.
• Simulation of active lattice sites to generate evolution curves.
• Comparison of model-generated curves with COVID-19 epidemic data from seven European nations.

Main Results:

• The model's active lattice site evolution curves closely matched COVID-19 spread patterns in European populations.
• The model successfully represented epidemic dynamics across diverse countries (Italy, Spain, Greece, France, Belgium, Germany, Netherlands) under social distancing.
• Analysis revealed dynamical characteristics, including memory effects, within the epidemiological systems.

Conclusions:

• The proposed self-organizing model provides a simple yet powerful tool for understanding and potentially controlling viral epidemic spreads.
• The model's basis in universal natural mechanisms enhances its applicability to pandemics like COVID-19.
• Further research can leverage this model to study epidemiological dynamics and inform public health strategies.