Has the age distribution of hospitalized Covid-19 patients changed in Brazil?

  1. Carla Lourenço Tavares de Andrade
  2. Sheyla Maria Lemos Lima
  3. Monica Martins
  4. Claudia Cristina de Aguiar Pereira
  5. Margareth Crisóstomo Portela

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Abstract

The aim of this study was to compare the age profile of hospitalized Covid-19 patients during the first year of the pandemic, as well as hospital mortality and use of ICUs, by age group, in large geographic regions of Brazil. We used data from the Influenza Epidemiological Surveillance Information System for patients who presented the first symptoms of the disease between the epidemiological weeks 8 of 2020 and 7 of 2021, which were divided into three periods.

779,257 records of patients hospitalized by Covid-19 were obtained. Of this total, 720,363 (92.4%) referred to discharged hospitalizations, considered in the analysis of ICU use and death. Among 244,611 hospitalizations (34.0%) with indication for use of ICU, 190,833 allowed the calculation of the time in ICU. There was variation in the age profile of hospitalized patients between the three periods, but there was no evidence in favor of the hypothesis of an increase, in the last period, in the participation of adults between 18 and 50 years old in hospitalizations by Covid-19. A differentiated increase in the mortality of young adults in the North suggests the possibility of greater severity of the P1 variant in this population. The results also show that the participation of young adults in hospitalizations and hospital deaths was never negligible and is related to hospital mortality rates close to or above 10%.

The Covid-19 “youthening” phenomenon in Brazil is based on the country’s own sociodemographic and economic characteristics and may have been strengthened by the increasing circulation of viral variants. It is important to continue monitoring its progression and effects.

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  1. ScreenIT

    SciScore for 10.1101/2021.03.30.21254650: (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

    No key resources detected.

    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.

  2. Version published to 10.1101/2021.03.30.21254650v1 on medRxiv