Population Changes in Seroprevalence among a Statewide Sample in the United States

  1. Kristen Malecki
  2. Maria Nikodemova
  3. Amy A. Schultz
  4. Andrew Bersch
  5. Matthew C Walsh
  6. Ajay K Sethi
  7. Paul Peppard
  8. Corinne Engelman
  9. Lisa Cadmus-Bertram
  10. Nasia Safdar
  11. Allen Bateman
  12. Ryan Westergaard

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Abstract

Antibody surveillance provides essential information for public health officials to work with communities to discuss the spread and impact of COVID-19. At the start of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in the United States, diagnostic testing was limited with many asymptomatic and thus undetected cases. Irrespective of symptom severity, antibodies develop within two to three weeks after exposure and may persist 6 months or more.; Thus, antibody surveillance is an important tool for tracking trends in past infections across diverse populations. This study includes adults and children (≥12 years old) recruited from a statewide sample of past 2014-2020 Survey of the Health of Wisconsin (SHOW) participants. SHOW, an ongoing population-based health examination study including a randomly selected sample of households, partnered with the Wisconsin Department of Health Services and the Wisconsin State Laboratory of Hygiene to conduct longitudinal antibody surveillance using the Abbott Architect SARS-CoV-2 IgG antibody test, which detects antibodies against the nucleocapsid protein. Three WAVES of sample collection were completed in 2020-2021, tracking mid-summer, late fall, and early spring COVID-19 trends prior to vaccine availability. Crude estimates of seroprevalence in the total study population increased ten-fold from 1.4% during WAVE I to 11.5% in WAVE III. Within the statewide probability sample, weighted estimates increased from 1.6% (95% CI:0.6-2.5%), to 6.8% (95% CI:4.3-9.4%) in WAVE II and to 11.4% (95% CI:8.2, 14.6%) in WAVE III. Longitudinal trends in seroprevalence match statewide case counts. Local seroprevalence showed variation by state health region with increasing prevalence among higher income (>200% poverty income ratio), and rural health regions of the state seeing the highest increase in COVID-19 prevalence over time. Significant disparities in prevalence by racial and ethnic groups also exist, with greater than two times seroprevalence among Latino and black participants compared to non-Hispanic whites. This public health and academic partnership provides critical data for the ongoing pandemic response and lays the foundation for future research into longer-term immunity, health impacts and population-level disparities.

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  1. Version published to 10.1101/2020.12.18.20248479v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.12.18.20248479: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: The statewide surveillance was deemed public health exempt, however, additional approval included consent for use of data and additional sample collection for future COVID-19 research was approved by the University of Wisconsin Health Sciences Institutional Review Board (IRB).
    IRB: The statewide surveillance was deemed public health exempt, however, additional approval included consent for use of data and additional sample collection for future COVID-19 research was approved by the University of Wisconsin Health Sciences Institutional Review Board (IRB).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The samples were then collected by currier each evening and sent immediately to the Wisconsin State Laboratory of Hygiene, where they were processed using the Abbott Architect SARS-CoV-2 IgG antibody test, with estimated specificity of 99.6%[11, 12].
    SARS-CoV-2 IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    The samples were then collected by currier each evening and sent immediately to the Wisconsin State Laboratory of Hygiene, where they were processed using the Abbott Architect SARS-CoV-2 IgG antibody test, with estimated specificity of 99.6%[11, 12].
    Abbott Architect
    suggested: (Abbott ARCHITECT i1000sr System, RRID:SCR_019328)

    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.

  3. Version published to 10.1101/2020.12.18.20248479v1 on medRxiv