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Predicting antibody kinetics and duration of protection against SARS-CoV-2 following vaccination from sparse serological data.

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  • Additional Information
    • Source:
      Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE
    • Publication Information:
      Original Publication: San Francisco, CA : Public Library of Science, [2005]-
    • Subject Terms:
      COVID-19*/prevention & control ; COVID-19*/immunology ; Antibodies, Viral*/immunology ; Antibodies, Viral*/blood ; SARS-CoV-2*/immunology ; COVID-19 Vaccines*/immunology; Humans ; Male ; Longitudinal Studies ; Female ; Middle Aged ; Vaccination ; BNT162 Vaccine/immunology ; Adult ; Immunoglobulin G/immunology ; Immunoglobulin G/blood ; Kinetics ; Aged ; Computational Biology ; Models, Immunological
    • Abstract:
      Vaccination against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) generates an antibody response that shows large inter-individual variability. This variability complicates the use of antibody levels as a correlate of protection and the evaluation of population- and individual-level infection risk without access to broad serological testing. Here, we applied a mathematical model of antibody kinetics to capture individual anti-SARS-CoV-2 IgG antibody trajectories and to identify factors driving the humoral immune response. Subsequently, we evaluated model predictions and inferred the corresponding duration of protection for new individuals based on a single antibody measurement, assuming sparse access to serological testing. We observe a reduced antibody response in older and in male individuals, and in individuals with autoimmune diseases, diabetes and immunosuppression, using data from a longitudinal cohort study conducted in healthcare workers at Sheba Medical Center, Israel, following primary vaccination with the BNT162b2 COVID-19 vaccine. Our results further suggest that model predictions of an individual's antibody response to vaccination can be used to predict the duration of protection when serological data is limited, highlighting the potential of our approach to estimate infection risk over time on both the population and individual level to support public health decision-making in future pandemics.
      (Copyright: © 2025 Deichmann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
    • Abstract:
      The authors have declared that no competing interests exist.
    • References:
      Nat Commun. 2023 May 26;14(1):3032. (PMID: 37230973)
      Nat Commun. 2024 Feb 19;15(1):1492. (PMID: 38374032)
      Clin Infect Dis. 2023 Feb 8;76(3):e439-e449. (PMID: 35608504)
      PLoS Comput Biol. 2023 Aug 7;19(8):e1011282. (PMID: 37549192)
      Nat Commun. 2022 Oct 2;13(1):5780. (PMID: 36184633)
      Vaccine. 2021 Nov 16;39(47):6902-6906. (PMID: 34702617)
      BMC Med. 2024 Mar 8;22(1):103. (PMID: 38454385)
      N Engl J Med. 2021 Oct 14;385(16):1474-1484. (PMID: 34320281)
      N Engl J Med. 2021 Dec 9;385(24):e85. (PMID: 34706170)
      Nat Med. 2023 May;29(5):1146-1154. (PMID: 37169862)
      Nature. 2021 Aug;596(7872):417-422. (PMID: 34192737)
      N Engl J Med. 2021 Aug 19;385(8):759-760. (PMID: 34161702)
      Nat Med. 2021 Aug;27(8):1370-1378. (PMID: 34108716)
      EClinicalMedicine. 2020 Dec;29:100651. (PMID: 33235985)
      J Infect Dis. 2014 Oct 1;210(7):1115-22. (PMID: 24719471)
      Nat Commun. 2023 Nov 2;14(1):7015. (PMID: 37919289)
      Vaccine. 2021 Nov 26;39(48):6984-6989. (PMID: 34763949)
      J Infect Dis. 2021 Nov 16;224(9):1489-1499. (PMID: 34282461)
      Ann Rheum Dis. 2021 Oct;80(10):1322-1329. (PMID: 34362747)
      N Engl J Med. 2021 Dec 9;385(24):e84. (PMID: 34614326)
      Lancet Microbe. 2023 May;4(5):e309-e318. (PMID: 36963419)
      N Engl J Med. 2021 Nov 4;385(19):1761-1773. (PMID: 34525277)
      BMC Infect Dis. 2022 Mar 29;22(1):311. (PMID: 35351016)
      J Infect Dis. 2023 Feb 1;227(3):339-343. (PMID: 36197948)
      J Infect Dis. 2021 Sep 1;224(5):793-797. (PMID: 34117873)
      J Med Virol. 2023 Jan;95(1):e28164. (PMID: 36131356)
      Immunity. 1998 Mar;8(3):363-72. (PMID: 9529153)
      Nat Med. 2021 Jul;27(7):1205-1211. (PMID: 34002089)
      Lancet Diabetes Endocrinol. 2021 Jun;9(6):350-359. (PMID: 33932335)
      Nat Immunol. 2022 Jun;23(6):940-946. (PMID: 35534723)
      Sci Rep. 2024 Mar 27;14(1):7217. (PMID: 38538722)
      N Engl J Med. 2020 Dec 31;383(27):2603-2615. (PMID: 33301246)
      Lancet Respir Med. 2021 Sep;9(9):999-1009. (PMID: 34224675)
    • Grant Information:
      U01 CA261277 United States CA NCI NIH HHS
    • Accession Number:
      0 (Antibodies, Viral)
      0 (COVID-19 Vaccines)
      0 (BNT162 Vaccine)
      0 (Immunoglobulin G)
    • Publication Date:
      Date Created: 20250618 Date Completed: 20250625 Latest Revision: 20250628
    • Publication Date:
      20250630
    • Accession Number:
      PMC12193770
    • Accession Number:
      10.1371/journal.pcbi.1013192
    • Accession Number:
      40531962