A Mathematical Model of the Within-Host Kinetics of SARS-CoV-2 Neutralizing Antibodies Following COVID-19 Vaccination

  1. Lisette de Pillis
  2. Rebecca Caffrey
  3. Ge Chen
  4. Mark D. Dela
  5. Leif Eldevik
  6. Joseph McConnell
  7. Shahrokh Shabahang
  8. Stephen A. Varvel

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Abstract

Compelling evidence continues to build to support the idea that SARS-CoV-2 Neutralizing Antibody (NAb) levels in an individual can serve as an important indicator of the strength of protective immunity against infection. It is not well understood why NAb levels in some individuals remain high over time, while in others levels decline rapidly. In this work, we present a two-population mathematical model of within-host NAb dynamics in response to vaccination. By fitting only four host-specific parameters, the model is able to capture individual-specific NAb levels over time as measured by the AditxtScore ™ for NAbs. The model can serve as a foundation for predicting NAb levels in the long-term, understanding connections between NAb levels, protective immunity, and break-through infections, and potentially guiding decisions about whether and when a booster vaccination may be warranted.

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    SciScore for 10.1101/2022.05.11.491557: (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

    Software and Algorithms
    SentencesResources
    Parameter Fitting and Numerical Solution: Subject-specific parameters were fit with a variety of built-in MATLAB methods that are part of the Global Optimization toolbox [24].
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  2. Version published to 10.1101/2022.05.11.491557v1 on bioRxiv