Questioning the seasonality of SARS-COV-2: a Fourier spectral analysis
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Abstract
To investigate the hypothesis of a seasonal periodicity, driven by climate, in the contagion resurgence of COVID-19 in the period February 2020–December 2021.
Design
An observational study of 30 countries from different geographies and climates. For each country, a Fourier spectral analysis was performed with the series of the daily SARS-CoV-2 infections, looking for peaks in the frequency spectrum that could correspond to a recurrent cycle of a given length.
Settings
Public data of the daily SARS-CoV-2 infections from 30 different countries and five continents.
Participants
Only publicly available data were utilised for this study, patients and/or the public were not involved in any phase of this study.
Results
All the 30 investigated countries have seen the recurrence of at least one COVID-19 wave, repeating over a period in the range 3–9 months, with a peak of magnitude at least half as large as that of the highest peak ever experienced since the beginning of the pandemic until December 2021. The distance in days between the two highest peaks in each country was computed and then averaged over the 30 countries, yielding a mean of 190 days (SD 100). This suggests that recurrent outbreaks may repeat with cycles of different lengths, without a precisely predictable seasonality of 1 year.
Conclusion
Our findings suggest that COVID-19 outbreaks are likely to occur worldwide, with cycles of repetition of variable lengths. The Fourier analysis of 30 different countries has not found evidence in favour of a seasonality that recurs over 1year period, solely or with a precisely fixed periodicity.
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SciScore for 10.1101/2022.01.26.22269886: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources To conclude, using a Python library called SciPy (https://scipy.org/), we performed a DFT of the time series of the SARS-COV-2 data of each country, that returned all the peaks in the frequency spectrum at their corresponding frequency which can be inverted to obtain the repetition period. Pythonsuggested: (IPython, RRID:SCR_001658)SciPysuggested: (SciPy, RRID:SCR_008058)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This can be seen as a limitation of our study as …
SciScore for 10.1101/2022.01.26.22269886: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources To conclude, using a Python library called SciPy (https://scipy.org/), we performed a DFT of the time series of the SARS-COV-2 data of each country, that returned all the peaks in the frequency spectrum at their corresponding frequency which can be inverted to obtain the repetition period. Pythonsuggested: (IPython, RRID:SCR_001658)SciPysuggested: (SciPy, RRID:SCR_008058)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This can be seen as a limitation of our study as the magnitude of the effects of those factors should be investigated thoroughly. Yet, there are precise motivations behind our choice. On one side, we have decided to avoid taking part in the scientific discussion about the dominant role of climate vs. control measures, including vaccination, as the best solutions that can drive substantial changes to the pandemic trajectory. On the other side, we have tried to observe a natural phenomenon, just resorting to a mathematical technique able to detect the presence of evidence towards periodicity/non-periodicity in the spread of COVID-19, with neutrality and regardless of the underlying factors. Another technical limitation of our approach was the decision not to put a special focus on those countries where the number of cases has had high variability, the reason being most likely that the number of tests done each day can have varied as much. We could have normalized those cases with the number of tests, before subjecting them to the discrete Fourier transform, but this datum is often unreliable and may lead, in turn to unrealistic normalized values, so we decided to avoid this. An additional technical limitation of this study is that the Fourier transform may return results, especially at the lowest frequencies, with a variable degree of uncertainty. Hence, to confirm our results, we have developed a parallel analysis directly performed on the number of the new daily SARS-COV-2 ca...
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.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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