Interactions between SARS-CoV-2 and influenza, and the impact of coinfection on disease severity: a test-negative design

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Abstract

Background

The impact of SARS-CoV-2 alongside influenza is a major concern in the northern hemisphere as winter approaches.

Methods

Test data for influenza and SARS-CoV-2 from national surveillance systems between 20 January 2020 and 25 April 2020 were used to estimate influenza infection on the risk of SARS-CoV-2 infection. A test-negative design was used to assess the odds of SARS-CoV-2 in those who tested positive for influenza compared with those who tested negative. The severity of SARS-CoV-2 was also assessed using univariable and multivariable analyses.

Results

The risk of testing positive for SARS-CoV-2 was 58% lower among influenza-positive cases and patients with a coinfection had a risk of death of 5.92 (95% confidence interval: 3.21–10.91) times greater than among those with neither influenza nor SARS-CoV-2. The odds of ventilator use or death and intensive care unit admission or death were greatest among coinfected patients.

Conclusions

Coinfection of these viruses could have a significant impact on morbidity, mortality and health-service demand.

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  1. SciScore for 10.1101/2020.09.18.20189647: (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.