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Overlapping timescales obscure early warning signals of the second COVID-19 wave

  • Fabian Dablander
  • , Hans Heesterbeek
  • , Denny Borsboom
  • , John M Drake
    • University of Amsterdam
    • University of Georgia

    Research output: Contribution to journalArticleAcademicpeer-review

    Abstract

    Early warning indicators based on critical slowing down have been suggested as a model-independent and low-cost tool to anticipate the (re)emergence of infectious diseases. We studied whether such indicators could reliably have anticipated the second COVID-19 wave in European countries. Contrary to theoretical predictions, we found that characteristic early warning indicators generally decreased rather than increased prior to the second wave. A model explains this unexpected finding as a result of transient dynamics and the multiple timescales of relaxation during a non-stationary epidemic. Particularly, if an epidemic that seems initially contained after a first wave does not fully settle to its new quasi-equilibrium prior to changing circumstances or conditions that force a second wave, then indicators will show a decreasing rather than an increasing trend as a result of the persistent transient trajectory of the first wave. Our simulations show that this lack of timescale separation was to be expected during the second European epidemic wave of COVID-19. Overall, our results emphasize that the theory of critical slowing down applies only when the external forcing of the system across a critical point is slow relative to the internal system dynamics.

    Original languageEnglish
    Article number20211809
    Pages (from-to)1-11
    Number of pages11
    JournalProceedings. Biological sciences
    Volume289
    Issue number1968
    DOIs
    Publication statusPublished - 9 Feb 2022

    Bibliographical note

    Funding Information:
    F.D. and H.H. were supported by ZonMw grant no. 10430022010001. H.H. was also supported by ZonMw grant no. 10430032010011. J.M.D. was supported by NSF grant no. 2027786.

    Publisher Copyright:
    © 2022 The Authors.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • COVID-19
    • critical slowing down
    • early warning signals
    • timescale separation

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