Coronavirus Disease 2019 Vaccine Effectiveness Against Severe Acute Respiratory Syndrome Coronavirus 2 Infection in the United States Before the Delta- and Omicron-Associated Surges: A Retrospective Cohort Study of Repeat Blood Donors

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Background

To inform public health policy, it is critical to monitor coronavirus disease 2019 vaccine effectiveness (VE), including against acquiring infection.

Methods

We estimated VE using self-reported vaccination in a retrospective cohort of repeat blood donors who donated during the first half of 2021, and we demonstrated a viable approach for monitoring VE via serological surveillance.

Results

Using Poisson regression, we estimated an overall VE of 88.8% (95% confidence interval, 86.2–91.1), adjusted for demographic covariates and variable baseline risk.

Conclusions

The time since first reporting vaccination, age, race and/or ethnicity, region, and calendar time were statistically significant predictors of incident infection.

Article activity feed

  1. SciScore for 10.1101/2022.04.15.22273412: (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

    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: We detected the following sentences addressing limitations in the study:
    Several limitations need to be considered when interpreting these results. The serological assays employed in this study have high sensitivity and specificity for past infection and vaccination-induced Abs, but lower sensitivity than molecular assays for acute infection. We did not have detailed information on COVID-19 vaccination timing, number of doses, or vaccine type, and there is the potential for misreporting of vaccination status by donors on the DHQ. To limit the impact of potential misclassification of vaccination status, we required serological evidence of a vaccination response (presence of anti-S Abs and absence of anti-NC Abs) to corroborate self-reported vaccination, although donors could still have been classified as vaccinated after receiving only the first of a two-dose series or not long enough after receiving a single-dose vaccine or the second dose of a two-dose series to have developed robust Ab responses and be considered fully vaccinated. Sporadic presentation for donation, which for some donors may be very infrequent, is inherent to repeat blood donation datasets. We developed methods to account for interval censoring of both vaccination and infection events, but some data were excluded because vaccination status or the ordering of vaccination and infection events was uncertain during the interval. We used Vitalant region as a proxy geographic variable, however this may not capture with adequate granularity the heterogeneity in local transmission. Bloo...

    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.