Inactivated trivalent influenza vaccination is associated with lower mortality among patients with COVID-19 in Brazil

  1. Günther Fink
  2. Nina Orlova-Fink
  3. Tobias Schindler
  4. Sandra Grisi
  5. Ana Paula S Ferrer
  6. Claudia Daubenberger
  7. Alexandra Brentani

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Abstract

To estimate associations between trivalent influenza vaccination and COVID-19 mortality as well as severe clinical outcomes among hospitalised patients.

Design

Retrospective observational study.

Setting

This study was conducted among hospitalised patients with COVID-19 in Brazil.

Participants

We analysed all hospitalised patients with COVID-19 with available vaccination information captured in Brazil’s national electronic respiratory infection data system between 1 January 2020 and 23 June 2020.

Main outcome measures

The primary outcomes were age-specific mortality rates of hospitalised patients with COVID-19 with and without recent inactivated trivalent influenza vaccination.

Results

A total of 53 752 clinically confirmed COVID-19 cases were analysed. Controlling for health facility of treatment, comorbidities as well as an extensive range of sociodemographic factors, patients who received a recent influenza vaccine experienced on average 7% lower odds of needing intensive care treatment (95% CI 0.87 to 0.98), 17% lower odds of requiring invasive respiratory support (95% CI 0.77 to 0.88) and 16% lower odds of death (95% CI 0.78 to 0.90). Protective effects were larger when the vaccine was administered after onset of symptoms as well as among younger patients.

Conclusion

Patients with COVID-19 with recent inactivated influenza vaccination experience significantly better health outcomes than non-vaccinated patients in Brazil. Beneficial off-target effects of influenza vaccination through trained innate immune responses seem plausible and need to be further explored. Large-scale promotion of influenza vaccines seems advisable, especially in populations at high risk for severe COVID-19 disease progression.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.29.20142505: (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
    Materials and Methods:
    Methods
    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.

  2. Version published to 10.1136/bmjebm-2020-111549
  3. ScreenIT

    SciScore for 10.1101/2020.06.29.20142505: (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 variableA positive laboratory test for SARS-CoV-2 was documented in the medical records for 84% of the clinically diagnosed Covid-19 patients. 57% of patients were male, and the median age of patients was 59 years (Table 1).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    These trained, memory like NK cells could potentially be stimulated by other RNA viruses including SARS-CoV-2 as well.
    SARS-CoV-2
    suggested: (Sino Biological Cat# 40143-R019, AB_2827973)

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.06.29.20142505v1 on medRxiv