The prevalence of SARS-CoV-2 infection and other public health outcomes during the BA.2/BA.2.12.1 surge, New York City, April-May 2022

  1. Saba A Qasmieh
  2. McKaylee M Robertson
  3. Chloe A Teasdale
  4. Sarah G Kulkarni
  5. Heidi Jones
  6. David A. Larsen
  7. John J. Dennehy
  8. Margaret McNairy
  9. Luisa N. Borrell
  10. Denis Nash

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Abstract

Background

Routine case surveillance data for SARS-CoV-2 are incomplete, unrepresentative, missing key variables of interest, and may be increasingly unreliable for both timely surge detection and understanding the burden of infection and access to treatment.

Methods

We conducted a cross-sectional survey of a representative sample of 1,030 New York City (NYC) adult residents ≥18 years on May 7-8, 2022, when BA.2.12.1 comprised 47% of reported cases per genomic surveillance. We estimated the prevalence of SARS-CoV-2 infection during the preceding 14-day period (April 23-May 8), weighted to represent the 2020 NYC adult population. Respondents were asked about SARS-CoV-2 testing (including at-home rapid antigen tests), testing outcomes, COVID-like symptoms, and contact with SARS-CoV-2 cases. Based on responses, we classified individuals into three mutually exclusive categories of SARS-CoV-2 infection according to a hierarchical case definition as follows: confirmed (positive test with a provider), probable (positive at home rapid test), and possible (COVID-like symptoms and close contact with a confirmed/probable case). SARS-CoV-2 prevalence estimates were age- and sex-adjusted to the 2020 US population. Individuals with SARS-CoV-2 were asked about awareness/use of antiviral medications. We triangulated survey-based prevalence estimates with NYC’s official SARS-CoV-2 metrics on cases, hospitalizations, and deaths, as well as SARS-CoV-2 concentrations in wastewater for the same time period.

Results

An estimated 22.1% (95%CI 17.9%-26.2%) of respondents had SARS-CoV-2 infection during the two-week study period, corresponding to ∼1.5 million adults (95%CI 1.3-1.8 million). The official SARS-CoV-2 case count during the study period was 51,218. This 22.1% prevalence estimate included 11.4%, 6.5%, and 4.3% who met the confirmed, probable, and possible criteria of our case definition, respectively. Prevalence was estimated at 34.9% (95%CI 26.9%-42.8%) among individuals with co-morbidities, 14.9% (95% CI 11.0%-18.8%) among those 65+ years, and 18.9% (95%CI 10.2%-27.5%) among unvaccinated persons. Hybrid immunity (i.e., history of both vaccination and prior infection) was 66.2% (95%CI 55.7%-76.7%) among those with COVID and 46.3% (95%CI 40.2-52.2) among those without. Among individuals with COVID, 44.1% (95%CI 33.0%-55.1%) were aware of the antiviral nirmatrelvir/ritonavir (Paxlovid™), and 15.1% (95%CI 7.1%-23.1%) reported receiving it. Deaths and hospitalizations increased, but remained well below the levels of the BA.1 surge. SARS-CoV-2 virus concentrations in wastewater surveillance showed only a modest signal in comparison to that of the BA.1 surge.

Conclusions and Relevance

The true magnitude of NYC’s BA.2/BA.2.12.1 surge may have been vastly underestimated by routine SARS-CoV-2 case counts and wastewater surveillance. Hybrid immunity, bolstered by the recent BA.1 surge, likely limited the impact of the BA.2/BA.2.12.1 surge on severe outcomes. Representative surveys are needed as part of routine surveillance for timely surge detection, and to estimate the true burden of infection, hybrid immunity, and uptake of time-sensitive treatments among those most vulnerable to severe COVID.

Short abstract

Changes in testing practices and behaviors, including increasing at-home rapid testing and decreasing provider-based testing make it challenging to assess the true prevalence of SARS-CoV-2. We conducted a population-representative survey of adults in New York City to estimate the prevalence of SARS-CoV-2 infection during the BA.2./BA.2.12.1 surge in late April/early May 2022. We triangulated survey-based SARS-CoV-2 prevalence estimates with contemporaneous city-wide SARS-CoV-2 metrics on diagnosed cases, hospitalizations, deaths, and SARS-CoV-2 concentration in wastewater. Survey-based prevalence estimates were nearly 30 times higher than official case counts, and estimates of recently acquired hybrid immunity among those with active infection were high. We conclude that no single data source provides a complete or accurate assessment of the epidemiologic situation. Taken together, however, our results suggest that the magnitude of the BA.2/BA.2.12.1 surge was likely significantly underestimated, and high levels of hybrid immunity likely prevented a major surge in BA.2/BA.2.12.1-associated hospitalizations/deaths.

Article activity feed

  1. Version published to 10.1101/2022.05.25.22275603v3 on medRxiv
  2. Version published to 10.1101/2022.05.25.22275603v2 on medRxiv
  3. Rapid Reviews Infectious Diseases

    Melissa Briggs-Hagen

    Review 2: "The Prevalence of SARS-CoV-2 Infection and Uptake of COVID-19 Antiviral Treatments During the BA.2/BA.2.12.1 Surge, New York City, April-May 2022"

    Overall, reviewers note that the manuscript doesn't report details such as response rates or seem to control for potential confounders, which limits the manuscript's believability.

  4. Rapid Reviews Infectious Diseases

    Travis Lim

    Review 1: "The Prevalence of SARS-CoV-2 Infection and Uptake of COVID-19 Antiviral Treatments During the BA.2/BA.2.12.1 Surge, New York City, April-May 2022"

    Overall, reviewers note that the manuscript doesn't report details such as response rates or seem to control for potential confounders, which limits the manuscript's believability.

  6. ScreenIT

    SciScore for 10.1101/2022.05.25.22275603: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: 17 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:
    Our cross-sectional study has limitations, including self-report of testing outcomes over a 14-day recall period (subject to recall bias) and limited sample size especially in subgroups of those with evidence of COVID-19. For those with prior COVID, we did not capture information on timing of prior infections, which underestimates the degree of hybrid protection, though a substantial proportion of NYC adults were infected during the recent BA.1 surge.9,16 Our case definition would likely capture some, but not all, of the estimated 20-30% of individuals whose SARS-CoV-2 infection may remain asymptomatic throughout their infection,30,31 as well as those who were symptomatic but were not aware of a close contact. Finally, our survey could not include those whose primary language was not English or Spanish. Strengths include the representative nature of the study, the study’s timing at the start of the BA.2 /BA.2.12.1 surge, and measurement of several important factors that are not currently available through routine surveillance, including outcomes among those who do not test positive with a provider, prevalence among individuals vulnerable to COVID-19, hybrid protection, and awareness/uptake of nirmatrelvir/ritonavir.

    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.

  7. Version published to 10.1101/2022.05.25.22275603v1 on medRxiv