Mechanistic models of humoral kinetics following COVID-19 vaccination.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 39876790.
- Also identified by DOI 10.1098/rsif.2024.0445 and PMC identifier 11775660.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
COVID-19 vaccine programmes must account for variable immune responses and waning protection. Existing descriptions of antibody responses to COVID-19 vaccination convey limited information about the mechanisms of antibody production and maintenance. We describe antibody dynamics after COVID-19 vaccination with two biologically motivated mathematical models. We fit the models using Markov chain Monte Carlo to seroprevalence data from 14 602 uninfected individuals in England between May 2020 and September 2022. We analyse the effect of age, vaccine type, number of doses and the interval between doses on antibody production and longevity. We find evidence that individuals over 35 years old twice vaccinated with ChAdOx1-S generate a persistent antibody response suggestive of long-lived plasma cell induction. We also find that plasmablast productive capacity is greater in: younger people than older people (≤4.5-fold change in point estimates); people vaccinated with two doses than one dose (≤12-fold change); and people vaccinated with BNT162b2 than ChAdOx1-S (≤440-fold change). We find the half-life of an antibody to be 23-106 days. Routinely collected seroprevalence data are invaluable for characterizing within-host mechanisms of antibody production and persistence. Extended sampling and linking seroprevalence data to outcomes would enable conclusions about how humoral kinetics protect against disease.
Medical subject headings
- COVID-19
- Antibodies, Viral
- SARS-CoV-2
- COVID-19 Vaccines
- Immunity, Humoral
- Models, Immunological