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

Author:

Dablander Fabian1ORCID,Heesterbeek Hans2,Borsboom Denny1,Drake John M.34ORCID

Affiliation:

1. Department of Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands

2. Department of Population Health Sciences, Utrecht University, Utrecht, The Netherlands

3. Odum School of Ecology, University of Georgia, Athens, GA, USA

4. Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA

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.

Funder

ZonMw

National Science Foundation

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Environmental Science,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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