Estimation of Total Immunity to SARS-CoV-2 in Texas

  1. Stacia M. Desantis
  2. Luis G. León-Novelo
  3. Michael D. Swartz
  4. Ashraf S. Yaseen
  5. Melissa A. Valerio
  6. Frances A. Brito
  7. Jessica A. Ross
  8. Harold W. Kohl
  9. Sarah E. Messiah
  10. Steve H. Kelder
  11. Leqing Wu
  12. Shiming Zhang
  13. Kimberly A. Aguillard
  14. Michael O. Gonzalez
  15. Onyinye S. Omega-Njemnob
  16. Camille J. Breaux
  17. David L Lakey
  18. Jennifer A. Shuford
  19. Stephen Pont
  20. Eric D Boerwinkle

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Abstract

Given the underestimate of seroprevalence in the US due to insufficient testing, accurate estimates of population immunity to SARS-CoV-2 or vaccinations do not exist. Although model-based estimates have been proposed, they require inputting unknown parameters such as viral reproduction number, longevity of immune response, and other dynamic factors. In contrast to a model-based approach for estimating population immunity, or simplistic summing of natural- and vaccine-induced immunity, the current study presents a data-driven statistical procedure for estimating the total immunity rate in a region using prospectively collected serological data along with state-level vaccination data. We present a detailed procedure so that efforts can be replicated regionally to inform policy-making decisions relevant to SARS-CoV-2. Specifically, we conducted a prospective longitudinal statewide cohort serological survey with 10,482 participants and more than 14,000 blood samples beginning on September 30, 2020. Along with Department of State Health Services vaccination data, as of July 4, 2021, the estimated percentage of those with naturally occurring antibodies to SARS-CoV-2 in Texas is 35.3% (95% CI = (33.7%, 36.9%) and total estimated immunity is 69.1%. We conclude the seroprevalence of SARS-CoV-2 is 4 times higher than the state-confirmed COVID-19 cases (8.8%). This methodology is integral to pandemic preparedness.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.05.21261610: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Serological Assay and Vaccination Records: Antibody status was determined using the Roche Elecsys® Anti-SARS-CoV-2 (qualitative) assay detection of neutralizing antibodies against SARS-CoV-2 nucleocapsid (N) protein, hereafter referred to as “Roche N-test”.
    Anti-SARS-CoV-2
    suggested: None
    SARS-CoV-2 nucleocapsid ( N
    suggested: None

    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:
    Limitations may occur in observational serological surveys; e.g., sample demographics may not be fully representative of the state, which is true for some variables in the current survey. Sampling variability or selection biases may operate within small time windows of a serological survey, and can result in inaccuracies in seroprevalence estimates. It will therefore generally be necessary to smooth estimates using a chosen time window dependent on factors such as the magnitude of the wave of infection and participant accrual rate. Fortunately, we observe that the application of an isotonic restriction to reflect the assumption that seroprevalence should not decrease in a reasonably small time window mostly overcomes the issue of daily or weekly sampling variability. Further, it is necessary to estimate the percentage of people who have both had natural COVID-19 infection and are fully vaccinated in a given time window in order to subtract that proportion from the overall sum. Finally, it is important to age-adjust estimated serological and vaccination rates to the state census so they are commensurate with population demographics. This is especially important since vaccination was rolled out by age group, with older adults first priority in January-March 2021. To our knowledge, this is the first fully data-driven estimation of total immunity to SARS-CoV-2 in the state of Texas, which is the second largest state in the US with a population of 29.2 million. The method proposed...

    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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  2. Version published to 10.1101/2021.08.05.21261610v1 on medRxiv