Comparing COVID-19 mortality across selected states in India: The role of age structure

  1. Mohamed Jainul Azarudeen
  2. Khyati Aroskar
  3. Karishma Krishna Kurup
  4. Tanzin Dikid
  5. Himanshu Chauhan
  6. S.K. Jain
  7. S.K. Singh

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

No abstract available

Article activity feed

  1. Version published to 10.1016/j.cegh.2021.100877
  2. ScreenIT

    SciScore for 10.1101/2021.07.18.21259093: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study protocol was approved by the public health emergency operational research review board of National Centre for Disease Control to initiate this analysis.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We performed all the analysis using Microsoft Excel 2018 and Open Epi (an open-source epidemiologic statistics for public health) Version 3.01.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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:
    We faced limitations in our analysis with regard to the provisional nature of mortality data extracted from the Integrated Disease Surveillance Programme special surveillance portal up to November 16, 202 0. We tried to validate the mortality data with daily COVID 19 bulletins released by the states to ensure greater accuracy; some inconsistencies with the final mortality numbers cannot be ruled out. However, they are unlikely to impact the estimate and standardized mortality rates for comparison between the states and age groups.

    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.

    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.

  3. Version published to 10.1101/2021.07.18.21259093 on medRxiv