Genetic Drift Versus Climate Region Spreading Dynamics of COVID-19

  1. R. Di Pietro
  2. M. Basile
  3. L. Antolini
  4. S. Alberti

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Abstract

Background: The current propagation models of COVID-19 are poorly consistent with existing epidemiological data and with evidence that the SARS-CoV-2 genome is mutating, for potential aggressive evolution of the disease.

Objectives: We looked for fundamental variables that were missing from current analyses. Among them were regional climate heterogeneity, viral evolution processes versus founder effects, and large-scale virus containment measures.

Methods: We challenged regional versus genetic evolution models of COVID-19 at a whole-population level, over 168,089 laboratory-confirmed SARS-CoV-2 infection cases in Italy, Spain, and Scandinavia at early time-points of the pandemic. Diffusion data in Germany, France, and the United Kingdom provided a validation dataset of 210,239 additional cases.

Results: Mean doubling time of COVID-19 cases was 6.63 days in Northern versus 5.38 days in Southern Italy. Spain extended this trend of faster diffusion in Southern Europe, with a doubling time of 4.2 days. Slower doubling times were observed in Sweden (9.4 days), Finland (10.8 days), and Norway (12.95 days). COVID-19 doubling time in Germany (7.0 days), France (7.5 days), and the United Kingdom (7.2 days) supported the North/South gradient model. Clusters of SARS-CoV-2 mutations upon sequential diffusion were not found to clearly correlate with regional distribution dynamics.

Conclusion: Acquisition of mutations upon SARS-CoV-2 spreading failed to explain regional diffusion heterogeneity at early pandemic times. Our findings indicate that COVID-19 transmission rates are rather associated with a sharp North/South climate gradient, with faster spreading in Southern regions. Thus, warmer climate conditions may not limit SARS-CoV-2 infectivity. Very cold regions may be better spared by recurrent courses of SARS-CoV-2 infection.

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  1. Version published to 10.3389/fgene.2021.663371
  2. ScreenIT

    SciScore for 10.1101/2020.05.08.20095448: (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
    SentencesResources
    The correlation between COVID-19 spreading rates versus normalized climate-area values was computed by Anova.
    Anova
    suggested: (ANOVA, RRID:SCR_002427)
    Software: Stata software version 16 was used for data importing, manipulation and graphics (StataCorp. 2019. Stata Statistical Software:
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

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  3. Version published to 10.1101/2020.05.08.20095448 on medRxiv