COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

  1. Clarisse Lins de Lima
  2. Cecilia Cordeiro da Silva
  3. Ana Clara Gomes da Silva
  4. Eduardo Luiz Silva
  5. Gabriel Souza Marques
  6. Lucas Job Brito de Araújo
  7. Luiz Antônio Albuquerque Júnior
  8. Samuel Barbosa Jatobá de Souza
  9. Maíra Araújo de Santana
  10. Juliana Carneiro Gomes
  11. Valter Augusto de Freitas Barbosa
  12. Anwar Musah
  13. Patty Kostkova
  14. Wellington Pinheiro dos Santos
  15. Abel Guilhermino da Silva Filho

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Abstract

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  1. Version published to 10.3389/fpubh.2020.580815
  2. ScreenIT

    SciScore for 10.1101/2020.05.30.20117945: (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

    No key resources detected.

    Results from OddPub: Thank you for sharing your code.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Among the limitations of this study, we have the fact that, for the prediction, we only used the accumulated case history of Covid-19 for each of the 27 federative units. Therefore, factors related to probable virus mutations were disregarded, as well as demographic information and risk factors.

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2020.05.30.20117945v1 on medRxiv