Using household rosters from survey data to estimate all-cause excess death rates during the COVID pandemic in India

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Abstract

No abstract available

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  1. SciScore for 10.1101/2021.07.20.21260577: (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
    Statistical analysis was conducted with Stata v16.1.
    Stata
    suggested: (Stata, RRID:SCR_012763)

    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:
    Our findings have several limitations. First, response rates were low, especially during India’s lockdown. However, much of the non-response was because CPHS randomly sampled only 50% of households during the lockdown. We employ non-response weights to adjust non-response. Moreover, non-responding households in one round may report deaths from that round in subsequent rounds; we estimate excess deaths using that data in the Supplement. Second, CPHS may not be as representative as official excess-death numbers 6. We estimate a higher baseline death rate in 2019 than Global Burden of Disease 4. However, official all-cause mortality is only available for 10 states (out of 28) and the two sources give comparable answers.

    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.