Structural Entropy of Daily Number of COVID-19 Related Fatalities

  1. Eren Unlu

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Abstract

A recently proposed temporal correlation-based- network framework applied on financial markets called Struc- tural Entropy has prompted us to utilize it as a means of analysis for COVID-19 fatalities across countries. Our observation on the resemblance of volatility of fluctuations of daily novel coronavirus related number of deaths to the daily stock exchange returns suggests the applicability of this approach.

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  1. ScreenIT

    SciScore for 10.1101/2020.10.19.20215673: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot 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: 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.

    About SciScore

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  2. Version published to 10.1101/2020.10.19.20215673v1 on medRxiv