On the effectiveness of imposing restrictive measures in a graded Self-Organized Criticality epidemic spread model The case of COVID-19
Y. Contoyiannis, S.G. Stavrinides, M.P. Hanias, M. Kampitakis, P., Papadopoulos, S. Potirakis

TL;DR
This study adapts a self-organized criticality model to epidemic spread, analyzing how restrictive measures influence COVID-19 dynamics and identifying critical thresholds for virus density and intervention effectiveness.
Contribution
It introduces a physical SOC-based epidemic model that accounts for virus aggressiveness and critical phenomena, providing insights into the impact of restrictions and herd immunity thresholds.
Findings
Critical virus density determines epidemic safety and duration.
Near the critical point, epidemic exhibits critical slowing-down and phase transition behavior.
Restrictive measures significantly affect epidemic dynamics and herd immunity limits.
Abstract
The scope of this work is to serve as a guiding tool against subjective estimations on real pandemic situations (mainly due to the inability to acquire objective real data over whole populations). The previously introduced model of closed self-organized criticality (SOC), is adapted in the case of a virus-induced epidemic. In this version this physical model can distinguish the virus spread according to the virus aggressiveness. The study presented, highlights the critical value of virus density over a population. For low values of the initial virus density (lower than the critical value) it is proved that the virus-diffusion behavior is safe and quantitatively similar to usual real epidemical data. However, it is revealed that very close to the critical point, the critical slowing-down (CSD) phenomenon, introduced by the theory of critical phenomena, emerges, leading to a tremendous…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Mental Health Research Topics · Ecosystem dynamics and resilience
