Mobility and COVID-19 in Andorra: Country-Scale Analysis of High-Resolution Mobility Patterns and Infection Spread

  1. Ronan Doorley
  2. Alex Berke
  3. Ariel Noyman
  4. Luis Alonso
  5. Josep Ribo
  6. Vanesa Arroyo
  7. Marc Pons
  8. Kent Larson

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Abstract

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  1. Version published to 10.1109/jbhi.2021.3121165
  2. ScreenIT

    SciScore for 10.1101/2021.02.18.21251977: (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

    Antibodies
    SentencesResources
    Participants were tested for presence of both IgM and IgG antibodies twice, with two weeks between each round of testing.
    IgG
    suggested: None
    Where nT = number of positive tests N = size of the population D = actually has a current or previous infection T = tested positive for IgG and/or IgM antibodies se = combined sensitivity of the test for IgG and/or IgM sp = combined specificity of the test for IgG and/or IgM 3.3 Telecoms Data: For this study, telecoms data were provided by Andorra Telecom (AT).
    IgM
    suggested: None

    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.

  3. Version published to 10.1101/2021.02.18.21251977v2 on medRxiv
  4. Version published to 10.1101/2021.02.18.21251977v1 on medRxiv