Overlapping timescales obscure early warning signals of the second COVID-19 wave
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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.
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SciScore for 10.1101/2021.07.27.21261226: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Some limitations of this study should be kept in mind. Our empirical analysis takes the reported number of cases across European countries at face value. While we accounted for reporting delays, we disregarded any issues related to changes in reporting or …
SciScore for 10.1101/2021.07.27.21261226: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Some limitations of this study should be kept in mind. Our empirical analysis takes the reported number of cases across European countries at face value. While we accounted for reporting delays, we disregarded any issues related to changes in reporting or testing that may affect the estimation of Rt. While the flexible method proposed by Abbott et al. (2020) renders any bias induced by a change of testing transient, any bias may have indeed changed the true value at which Rt crosses one. A more extensive analysis would look at all countries that experienced a second wave. However, we chose to limit ourselves to European countries because of the comparatively good reporting standards and the fact that there is sufficiently large heterogeneity in epidemic trajectories across European countries for the purposes of this study. On a similar note, because the time period between the end of the first and the beginning of the second wave was shorter than the time period it takes the system to settle at its new stable equilibrium after the first wave recedes in virtually all countries, we expect our findings to generalize well to non-European countries. We used an admittedly conservative criterion for date stamping the end of the first wave and the start of the second one to reduce the extent of the transient period we incorporate for indicator estimation. In particular, we chose the day at which Rt reaches its lowest value as starting point for the computation of early warning indica...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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- Thank you for including a protocol registration statement.
Results from scite Reference Check: We found no unreliable references.
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