Disparities in SARS-CoV-2 seroprevalence among individuals presenting for care in central North Carolina over a six-month period

  1. Cesar A. Lopez
  2. Clark H. Cunningham
  3. Sierra Pugh
  4. Katerina Brandt
  5. Usaphea P. Vanna
  6. Matthew J. Delacruz
  7. Quique Guerra
  8. Samuel Jacob Goldstein
  9. Yixuan J. Hou
  10. Margaret Gearhart
  11. Christine Wiethorn
  12. Candace Pope
  13. Carolyn Amditis
  14. Kathryn Pruitt
  15. Cinthia Newberry-Dillon
  16. John Schmitz
  17. Lakshmanane Premkumar
  18. Adaora A. Adimora
  19. Michael Emch
  20. Ross Boyce
  21. Allison E. Aiello
  22. Bailey K. Fosdick
  23. Daniel B. Larremore
  24. Aravinda M. de Silva
  25. Jonathan J Juliano
  26. Alena J. Markmann

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Abstract

Background

Robust community-level SARS-CoV-2 prevalence estimates have been difficult to obtain in the American South and outside of major metropolitan areas. Furthermore, though some previous studies have investigated the association of demographic factors such as race with SARS-CoV-2 exposure risk, fewer have correlated exposure risk to surrogates for socioeconomic status such as health insurance coverage.

Methods

We used a highly specific serological assay utilizing the receptor binding domain of the SARS-CoV-2 spike-protein to identify SARS-CoV-2 antibodies in remnant blood samples collected by the University of North Carolina Health system. We estimated the prevalence of SARS-CoV-2 in this cohort with Bayesian regression, as well as the association of critical demographic factors with higher prevalence odds.

Findings

Between April 21 st and October 3 rd of 2020, a total of 9,624 unique samples were collected from clinical sites in central NC and we observed a seroprevalence increase from 2·9 (1·7, 4·3) to 9·1 (7·2, 11·1) over the study period. Individuals who identified as Latinx were associated with the highest odds ratio of SARS-CoV-2 exposure at 7·77 overall (5·20, 12·10). Increased odds were also observed among Black individuals and individuals without public or private health insurance.

Interpretation

Our data suggests that for this care-accessing cohort, SARS-CoV-2 seroprevalence was significantly higher than cumulative total cases reported for the study geographical area six months into the COVID-19 pandemic in North Carolina. The increased odds of seropositivity by ethnoracial grouping as well as health insurance highlights the urgent and ongoing need to address underlying health and social disparities in these populations.

RESEARCH IN CONTEXT

Evidence before this study

We searched PubMed for studies published through March 21 st , 2021. We used search terms that included “COVID-19”, “SARS-CoV-2”, “prevalence” and “seroprevalence”. Our search resulted in 399 papers, from which we identified 58 relevant studies describing SARS-CoV-2 seroprevalence at sites around the United States from March 1 to December 9, 2020, 12 of which utilized remnant clinical samples and three of which overlapped with our study area. Most notably, one study of 4,422 asymptomatic inpatients and outpatients in central NC from April 28-June 19, 2020 found an estimated seroprevalence of 0·7 −0·8%, and another study of 177,919 inpatients and outpatients (3,817 from NC) from July 27-September 24, 2020 found an estimated seroprevalence of 2·5 −6·8%.

Added value of this study

This is the largest SARS-CoV-2 seroprevalence cohort published to date in NC. Importantly, we used a Bayesian framework to account for uncertainty in antibody assay sensitivity and specificity and investigated seropositivity by important demographic variables that have not yet been studied in this context in NC. This study corroborates other reports that specific demographic factors including race, ethnicity and the lack of public or private insurance are associated with elevated risk of SARS-CoV-2 infection. Furthermore, in a subset of serum samples, we identify other SARS-CoV-2 antibodies elicited by these individuals, including functionally neutralizing antibodies.

Implications of all the available evidence

It is difficult to say the exact seroprevalence in the central North Carolina area, but a greater proportion of the population accessing healthcare has been infected by SARS-CoV-2 than is reflected by infection cases confirmed by molecular testing. Furthermore, local governments need to prioritize addressing the many forms of systemic racism and socioeconomic disadvantage that drive SARS-CoV-2 exposure risk, such as residential and occupational risk, and an urgent need to provide access to SARS-CoV-2 testing and vaccination to these groups.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.03.25.21254320: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Written informed consent was not required due to the use of routinely collected samples.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableEach group was compared to females, non-Latinx white, ages 5-17, outpatient, and private payor health insurance status as respective baseline categories.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    23 SARS-CoV-2 Neutralization Assays: To further characterize the SARS-CoV-2 antibody responses of this study, viral neutralization assays were obtained for 110 ELISA-positive samples that were selected randomly using the sample_n() function of the dplyr R package.
    SARS-CoV-2
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Luciferase-expressing, full-length SARS-CoV-2 isolate WA1 strain (GenBank Accession#: MT020880) was engineered and recovered via reverse genetics and used to titer serially diluted sera on Vero E6 USAMRID cell as described previously.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Nucleocapsid protein ELISA: Detection of IgG antibody to SARS-CoV-2 N antigen was performed with the EUA approved Abbott SARS-CoV-2 IgG assay (Abbott Laboratories) on the Abbott Architect i2000SR immunoassay analyzer as previously described.
    Abbott Laboratories
    suggested: None
    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: We detected the following sentences addressing limitations in the study:
    The primary limitation of this study is that the study population, composed of individuals accessing care at UNC area hospitals and clinics may differ from the overall population in central North Carolina in ways that are not captured in demographic data (e.g., overall health status). Accordingly, we have chosen to not weight our dataset to county demographics and therefore do not provide overall estimates of seroprevalence in the six-county area as that would require more representative sampling methodology.34 Furthermore, many clinics and hospital elective procedures were closed or only seeing patients virtually during the first few months of the study period. The unexpected seroprevalence peak observed at the Johnston County hospital suggests that the population accessing care at these clinical sites did not have consistent exposure risk over time. As expected, seroprevalence estimates in this cohort track closely with COVID-19 hospitalizations in the four hospitals in this study with a two-week lag which could be due to time to seroconvert. Declining antibody over this time period to undetectable levels is unlikely, as the length of the study is shorter than it takes for significant antibody decline to undetectable levels, although little is known about antibody levels over time in the asymptomatic population.31 Other limitations of the study include that we could not break down odds ratios by all races and/or by race and ethnicity at the same time, or by multiracial cate...

    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.
    • Thank you for including a protocol registration statement.

    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.

  2. Version published to 10.1101/2021.03.25.21254320 on medRxiv