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Criticality in epidemic spread: An application in the case of COVID19 infected population.
Contoyiannis, Y; Stavrinides, S G; Hanias, M P; Kampitakis, M; Papadopoulos, P; Picos, R; Potirakis, S M; Kosmidis, E K.
  • Contoyiannis Y; Department of Electrical and Electronics Engineering, University of West Attica, Ancient Olive Grove Campus, 250 Thivon and P. Ralli, Aigaleo, Athens GR-12244, Greece.
  • Stavrinides SG; School of Science and Technology, International Hellenic University, Thermi Campus, 57001 Thessaloniki, Greece.
  • Hanias MP; Physics Department, International Hellenic University, St Lucas, 65404 Kavala, Greece.
  • Kampitakis M; Major Network Installations Department, Hellenic Electricity Distribution Network Operator S.A., 18547 Athens, Greece.
  • Papadopoulos P; Department of Electrical and Electronics Engineering, University of West Attica, Ancient Olive Grove Campus, 250 Thivon and P. Ralli, Aigaleo, Athens GR-12244, Greece.
  • Picos R; Department of Industrial Engineering and Construction, University of Balearic Islands, 07122 Palma, Spain.
  • Potirakis SM; Department of Industrial Engineering and Construction, University of Balearic Islands, 07122 Palma, Spain.
  • Kosmidis EK; Laboratory of Physiology, Department of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Chaos ; 31(4): 043109, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1185499
ABSTRACT
Recently, it has been successfully shown that the temporal evolution of the fraction of COVID-19 infected people possesses the same dynamics as the ones demonstrated by a self-organizing diffusion model over a lattice, in the frame of universality. In this brief, the relevant emerging dynamics are further investigated. Evidence that this nonlinear model demonstrates critical dynamics is scrutinized within the frame of the physics of critical phenomena. Additionally, the concept of criticality over the infected population fraction in epidemics (or a pandemic) is introduced and its importance is discussed, highlighting the emergence of the critical slowdown phenomenon. A simple method is proposed for estimating how far away a population is from this "singular" state, by utilizing the theory of critical phenomena. Finally, a dynamic approach applying the self-organized diffusion model is proposed, resulting in more accurate simulations, which can verify the effectiveness of restrictive measures. All the above are supported by real epidemic data case studies.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Limits: Humans Language: English Journal: Chaos Journal subject: Science Year: 2021 Document Type: Article Affiliation country: 5.0046772

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Limits: Humans Language: English Journal: Chaos Journal subject: Science Year: 2021 Document Type: Article Affiliation country: 5.0046772