Public health interventions slowed but did not halt the spread of COVID‐19 in India

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Abstract

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  1. SciScore for 10.1101/2020.06.06.20123893: (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
    These data are publicly available from Google and represent the percent change from baseline mobility within various domains (retail and recreation mobility, grocery and pharmacy mobility, parks mobility, transit stations mobility, workplace mobility, and residential mobility) according to cell phone-user geolocation data.
    Google
    suggested: (Google, RRID:SCR_017097)
    Statistical analyses: All statistical analyses were conducted using R version 3·6·3 (R Development Core Team, http://www.r-project.org).
    R Development Core
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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:
    The current study had some limitations. Overall testing rate has not been very high in India; as of 23 May 2020, the country had tested 2,943,421 samples at a rate of 2,432 per million people. As of 1 June 2020, the United States had tested 17,612,125 samples at a rate of 53,911 per million people26. Information on the diagnostic testing patterns remain unknown. However, there was a shortage of testing during early phase of the epidemic. India tested 100 samples per day before 20 March 2020 but this was scaled-up to 100,000 tests per day on 20 May 202027. It has been demonstrated that changes in testing rates affect the epidemic curve of COVID-1928. Therefore, an underestimated case rate in the initial stage of the epidemic cannot be ruled out. Additionally, migration of COVID-19 cases between states cannot be excluded. As per the census of India (2011), 29·9% of total human population are migrants and 13·8% of the total population migrates between states, possibly due to social, economic and political reasons29. Many anecdotal reports reveal interstate movement of many of these migrants due to national lockdown/curfew and loss of jobs; however, exact figures remain unknown. Interstate migration of COVID-19 positive cases resulted in an unexplained bias in state-level estimates. For example, Tamil Nadu state reported 646 cases as of 26 May 2020, with 54 cases being persons returning from other states30. Although these cases were not included for Tamil Nadu estimates, such dat...

    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.