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Criticality in epidemic spread: An application in the case of COVID19 infected population.

Y ContoyiannisStavros G StavrinidesMichael P HaniasM KampitakisP PapadopoulosRodrigo PicosStelios M PotirakisEfstratios K Kosmidis
Published in: Chaos (Woodbury, N.Y.) (2021)
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.
Keyphrases
  • coronavirus disease
  • sars cov
  • randomized controlled trial
  • systematic review
  • respiratory syndrome coronavirus
  • high resolution
  • machine learning
  • electronic health record
  • atomic force microscopy
  • mass spectrometry