Variant-of-concern-attributable health and health system-related outcomes: a population-level propensity-score matched cohort study

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Abstract

Background

As the transmission of SARS-CoV-2 variants intensifies globally, the burden of COVID-19 on the already strained health systems is becoming increasingly concerning. While there is growing literature on the effects of various variants-of-concern (VOC) on increased transmission, the extent to which VOCs may lead to more severe disease remains debated.

Methods

In the current analysis, we use a population-based propensity-score matched cohort study of all incident laboratory-confirmed COVID-19 cases with VOC testing in Ontario, Canada to estimate healthcare resource use and health outcomes attributable to VOCs introduced to Ontario between January 1 and April 9, 2021, relative to the previously circulating wild-type strain.

Results

We find that VOCs are associated with a higher odds of hospitalisation (odds ratio [OR], 2.25; 95% confidence interval [CI], 2.10-2.40) and ICU admission (OR, 3.31; 95%CI, 2.84-3.86); as well as with a higher odds of mortality for both the general COVID-19 population (OR 1.75; 1.47-2.09) and hospitalised cases (OR, 1.62; 95%CI, 1.23-2.15).

Conclusion

Taken together, these findings suggest that health systems may face increased demand for healthcare resources as VOCs predominate worldwide in view of low global vaccination coverage.

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  1. SciScore for 10.1101/2021.06.02.21257869: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    13 Statistical analyses were performed using R version 3.6.3 with RStudio (R Core Team, 2020).
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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:
    However, our study also has limitations. The analysis is limited by the inability to control for unmeasured confounders especially in terms of missing comorbidity profiles and by right censoring of data. We were also unable to stratify by specific VOC lineage given lagging sequencing information, though the vast majority VOC cases are likely to be B.1.1.7. 11 Moreover, because data on ICU-related outcomes is likely to be underreported in the CCM dataset by ∼45% at the time of the analysis, ICU-related outcomes (i.e., ICU admission and ventilation/intubation) should be interpreted with caution. In conclusion, this study suggests that VOCs that that harbour the N501Y mutation, which confers greater infectivity, is also associated with more severe disease manifestations relative to earlier strains. Taken together, these findings suggest that compared to the previous phases of the pandemic, health systems will likely face increased demand for acute care hospital and ICU resources as VOCs predominate worldwide, especially in view of limited global vaccination coverage. Therefore, prompt vaccine roll-out particularly in regions with high incidence of VOC is warranted to reduce the global burden of COVID-19 going forward.

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.