Estimating the Period Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection During the Omicron (BA.1) Surge in New York City (NYC), 1 January to 16 March 2022

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

In a population-based survey of adults in New York City, we assessed positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests (including via exclusive at-home testing) and possible cases among untested respondents. An estimated 27.4% (95% confidence interval [CI]: 22.8%–32.0%) or 1.8 million adults (95% CI: 1.6–2.1 million) had SARS-CoV-2 infection between 1 January and 16 March 2022.

Article activity feed

  1. SciScore for 10.1101/2022.04.23.22274214: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study protocol was approved by the Institutional Review Board at the City University of New York (CUNY).
    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:
    While our study suggests a viable and simple approach to gather important and timely information about the prevalence of SARS-CoV-2 infections among adults in NYC, it also has limitations. First, we measured testing outcomes and symptoms via self-report over a long recall period, which is subject to recall bias. More frequent surveys with shorter recall periods (e.g., 7-14 days), could improve the accuracy of estimates. Our prevalence estimates also included possible SARS-CoV-2 cases based on self-reported symptoms who had a known contact with a confirmed/probable case, which, even though both prevalence of exposures and attack rates were very high during the BA.1 Omicron surge11, could lead to an overestimate of prevalence. Conversely, our estimates may not have captured some SARS-CoV-2 cases that are asymptomatic for their entire infection, resulting in an underestimate (e.g., by 10-30%).7 In addition, our survey excludes children and adolescents <18, those who died (about 4,426 NYC residents) during the study period. The small sample size limits the precision of some estimates across respondent characteristics. Part of our sample (32%) was derived from online panel data, as opposed to a population-based sampling frame (see Statistical Appendix), which could introduce bias. Finally, those who chose to participate in the survey could be more or less likely to have had COVID-19 recently (participation bias). Population-based representative surveys are an important adjunct sur...

    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.