Strategies to Estimate Prevalence of SARS-CoV-2 Antibodies in a Texas Vulnerable Population: Results From Phase I of the Texas Coronavirus Antibody Response Survey

  1. Melissa A. Valerio-Shewmaker
  2. Stacia DeSantis
  3. Michael Swartz
  4. Ashraf Yaseen
  5. Michael O. Gonzalez
  6. Harold W. III Kohl
  7. Steven H. Kelder
  8. Sarah E. Messiah
  9. Kimberly A. Aguillard
  10. Camille Breaux
  11. Leqing Wu
  12. Jennifer Shuford
  13. Stephen Pont
  14. David Lakey
  15. Eric Boerwinkle

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Abstract

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and immunity remains uncertain in populations. The state of Texas ranks 2nd in infection with over 2.71 million cases and has seen a disproportionate rate of death across the state. The Texas CARES project was funded by the state of Texas to estimate the prevalence of SARS-CoV-2 antibody status in children and adults. Identifying strategies to understand natural as well as vaccine induced antibody response to COVID-19 is critical.

Materials and Methods: The Texas CARES (Texas Coronavirus Antibody Response Survey) is an ongoing prospective population-based convenience sample from the Texas general population that commenced in October 2020. Volunteer participants are recruited across the state to participate in a 3-time point data collection Texas CARES to assess antibody response over time. We use the Roche Elecsys® Anti-SARS-CoV-2 Immunoassay to determine SARS-CoV-2 antibody status.

Results: The crude antibody positivity prevalence in Phase I was 26.1% (80/307). The fully adjusted seroprevalence of the sample was 31.5%. Specifically, 41.1% of males and 21.9% of females were seropositive. For age categories, 33.5% of those 18–34; 24.4% of those 35–44; 33.2% of those 45–54; and 32.8% of those 55+ were seropositive. In this sample, 42.2% (89/211) of those negative for the antibody test reported having had a COVID-19 test.

Conclusions: In this survey we enrolled and analyzed data for 307 participants, demonstrating a high survey and antibody test completion rate, and ability to implement a questionnaire and SARS-CoV-2 antibody testing within clinical settings. We were also able to determine our capability to estimate the cross-sectional seroprevalence within Texas's federally qualified community centers (FQHCs). The crude positivity prevalence for SARS-CoV-2 antibodies in this sample was 26.1% indicating potentially high exposure to COVID-19 for clinic employees and patients. Data will also allow us to understand sex, age and chronic illness variation in seroprevalence by natural and vaccine induced. These methods are being used to guide the completion of a large longitudinal survey in the state of Texas with implications for practice and population health.

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  1. Version published to 10.3389/fpubh.2021.753487
  2. ScreenIT

    SciScore for 10.1101/2021.08.04.21261613: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: All study protocols were reviewed and approved by the University of Texas Health Science Center Houston Institutional Review Board prior to any data collection.
    Consent: Enrollment required contact information, demographic characteristics and informed consent for three blood draws over 6-12 months.
    Sex as a biological variableThese features provide an optimal combination of high specificity and sensitivity for the detection of immune exposure to SARS-CoV-2 in the general population, including in pregnant women and pediatric populations.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The larger study aims to enroll participants from four populations across the state of Texas; pediatric school children 5-17 years of age, FQHC or community clinic patients, kindergarten to -12th grade educators and allied staff and Texas workforce employees who will be tested for SARS-CoV-2 antibodies at three points over a 6-12 month period.
    SARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    The full adjustment analysis was completed using SPSS version 27 and by hand.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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 inclusion of COVID-19 positive and negative participants is important as it has been a limitation of other studies and allows us to more accurately determine the seroprevalence and human response over time in a diverse representative population. Therefore, ability to determine antibodies in individual with no previous history of COVID-19 over time is a unique aspect of our program approach that may inform understanding of the timing of neutralizing antibodies across a 6-month period; current estimate indicate antibodies may be stable for 5-7 months after SARS-CoV-2 infection13. Although self-reported the COVID-19 test positivity and self-report of symptoms allows us to better determine the cycle and decline of antibody levels in a large sample of Texans over a 6-month period. It is estimated that over one-third of patients that have recovered from COVID-19 have antibodies given mild or asymptomatic disease,11 it is important to note that in our sample, 68.7% of those with a previous positive COVID-19 test had a positive SARS-CoV-2 antibody test. The timing of the data collection from the start of the first reported cases in Texas was approximately 6 months from the start of our data collection. The positive cases will be monitored for decline of antibody levels and collection of additional COVID-19 testing, positive results and symptoms over a further six-month enrollment period. Although the highest neutralizing antibody titers are found in severe disease,19 the expected...

    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.

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  3. Version published to 10.1101/2021.08.04.21261613v1 on medRxiv