Estimation of Case Fatality Rate during an Epidemic: an Example from COVID-19 Pandemic

  1. Masud Yunesian
  2. Akbar Fotouhi
  3. Mina Aghaei

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

The case fatality rate (CFR) is an important index in epidemics and policymakers need to be aware of this statistic for making sound decisions. However, there are some uncertainties in the calculation of the fatality rate and the true case fatality rate can be calculated after an epidemic subsides, we calculated the fatality rate for 20 countries which had the highest number of confirmed cases with three scenarios. In this study, we provided detailed information to discuss the studies that calculate the case fatality rate during the COVID-19 pandemic and highlight the estimation bias in these studies

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.19.20106468: (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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.19.20106468 on medRxiv