Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil

  1. William Marciel de Souza
  2. Lewis Fletcher Buss
  3. Darlan da Silva Candido
  4. Jean-Paul Carrera
  5. Sabrina Li
  6. Alexander E. Zarebski
  7. Rafael Henrique Moraes Pereira
  8. Carlos A. Prete
  9. Andreza Aruska de Souza-Santos
  10. Kris V. Parag
  11. Maria Carolina T. D. Belotti
  12. Maria F. Vincenti-Gonzalez
  13. Janey Messina
  14. Flavia Cristina da Silva Sales
  15. Pamela dos Santos Andrade
  16. Vítor Heloiz Nascimento
  17. Fabio Ghilardi
  18. Leandro Abade
  19. Bernardo Gutierrez
  20. Moritz U. G. Kraemer
  21. Carlos K. V. Braga
  22. Renato Santana Aguiar
  23. Neal Alexander
  24. Philippe Mayaud
  25. Oliver J. Brady
  26. Izabel Marcilio
  27. Nelson Gouveia
  28. Guangdi Li
  29. Adriana Tami
  30. Silvano Barbosa de Oliveira
  31. Victor Bertollo Gomes Porto
  32. Fabiana Ganem
  33. Walquiria Aparecida Ferreira de Almeida
  34. Francieli Fontana Sutile Tardetti Fantinato
  35. Eduardo Marques Macário
  36. Wanderson Kleber de Oliveira
  37. Mauricio L. Nogueira
  38. Oliver G. Pybus
  39. Chieh-Hsi Wu
  40. Julio Croda
  41. Ester C. Sabino
  42. Nuno Rodrigues Faria

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.1038/s41562-020-0928-4
  2. ScreenIT

    SciScore for 10.1101/2020.04.25.20077396: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Individual-level data on notified cases from Brazil: To investigate individual-level diagnostic, demographic, self-reported travel history, place of residence and likely place of infection, differential diagnosis for other respiratory pathogens, as well as clinical details, including comorbidities, we collected case data notified to the REDCap database8 from February 25 to March 25, 2020.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    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:
    We identified several limitations in our study. First, detailed individual-level data was only available for the first month of the epidemic in Brazil. Moreover, several cases had incomplete documentation, such as hospitalization date, mechanical ventilation, and travel history. Real-time aggregated data and open-access open line lists have the potential to provide real-time insights into transmissibility14. Secondly, our retrospective study has focused predominantly on symptomatic patients (92%) that presented themselves to health services for testing. Therefore, we cannot describe the full spectrum of disease. Population-based serologic surveys are urgently needed to properly determine the asymptomatic and oligosymptomatic fraction. Finally, many patients remained hospitalized when the dataset was extracted, and, we were unable to estimate clinical outcomes given the long duration of infection. Together with changes in surveillance guidelines, socioeconomic bias in testing suggests that the number of confirmed case counts may substantially underestimate the true number of cases in the population. Additional reasons for underreporting include (i) a significant proportion of asymptomatic infections15, (ii) people with mild and even moderate disease are unlikely to present to health services for testing, (iii) limited testing capacity in public health service in Brazil in face of the large number of cases due to delays in importing reagents and kits used in molecular testing. ...

    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 10.1101/2020.04.25.20077396v1 on medRxiv