AI Article Synopsis

  • * The model achieved high accuracy rates of 97% for internal validation and around 83% to 98% for various external groups, indicating its reliability across different populations.
  • * A smart device application was created from this model to help quickly determine when antibody levels may dip below protective thresholds.

Article Abstract

Tools that can be used to estimate antibody waning following COVID-19 vaccinations can facilitate an understanding of the current immune status of the population. In this study, a two-compartment-based mathematical model is formulated to describe the dynamics of the anti-SARS-CoV-2 antibody in healthy adults using serially measured waning antibody concentration data obtained in a prospective cohort study of 673 healthcare providers vaccinated with two doses of BNT162b2 vaccine. The datasets of 165 healthcare providers and 292 elderly patients with or without hemodialysis were used for external validation. Internal validation of the model demonstrated 97.0% accuracy, and external validation of the datasets of healthcare workers, hemodialysis patients, and nondialysis patients demonstrated 98.2%, 83.3%, and 83.8% accuracy, respectively. The internal and external validations demonstrated that this model also fits the data of various populations with or without underlying illnesses. Furthermore, using this model, we developed a smart device application that can rapidly calculate the timing of negative seroconversion.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9988198PMC
http://dx.doi.org/10.1038/s41541-023-00626-wDOI Listing

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