Macrolevel association of COVID-19 with non-communicable disease risk factors in India

  1. Kiran Gaur
  2. Raghubir S. Khedar
  3. Kishore Mangal
  4. Arvind K. Sharma
  5. Rajinder K. Dhamija
  6. Rajeev Gupta

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.dsx.2021.01.005
  2. ScreenIT

    SciScore for 10.1101/2020.12.21.20248684: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: 14,22 The project proposal was approved by the institutional ethics committee as part of COVID-19 database at our centre.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    To determine association of COVID-19 cases and death with state-level NCD and risk factors, healthcare indices and sociodemographic variables we calculated Pearson’s correlation coefficient (r value) using SPSS Statistical Package.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Other limitations of our analyses are absence of detailed readily available cause-specific morbidity and mortality data, lack of population based registries of COVID-19 cases and deaths, absence of concurrent mortality data to evaluate excess deaths from COVID-19 and absence of other collinear data. Our study shows that COVID-19 burden is significantly greater in more developed and urbanized states of the country where there is a greater prevalence of NCD risk factors. These findings have important implications for prioritization of deployment of preventive strategies and vaccinations. Large scale government-led non-pharmaceutical prevention strategies that have proven effective in COVID-19 control include mandatory mask-wearing in public spaces, limited public gatherings (<100 or <10 people depending on context), closure of non-essential businesses, schools and universities, and stay at home orders with appropriate exemptions.42 Individual level non-pharmacological interventions include proper masking, physical distancing and avoiding crowded spaces. Although, vaccines have become available and need scientifically appropriate strategies to achieve maximum impact and development of population-level immunity.43,44 Equitable vaccine distribution is essential.45 However, in the present macrolevel scenario highlighted in this report we posit that more developed states, who are at forefront of the COVID-19 epidemic, need non-pharmacological interventions as well as vaccines more t...

    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.

  3. Version published to 10.1101/2020.12.21.20248684 on medRxiv