Mechanistic models of humoral kinetics following COVID-19 vaccination

Introduction: Future COVID-19 vaccine programmes need to take into account the variable responses elicited by different vaccines and their waning protection over time. Existing descriptions of antibody response to COVID-19 vaccination convey limited information about the mechanisms of antibody production and maintenance. Methods: We describe the antibody dynamics elicited by COVID-19 vaccination with two biologically-motivated mathematical models of antibody production by plasma cells and subsequent decay. We fit the models using Markov Chain Monte Carlo to seroprevalence data from 14,602 uninfected individuals collected via the primary care network in England between May 2020 and September 2022. We ensure our models are structurally and practically identifiable when using anti- body data alone. We analyse the effect of age, vaccine type, number of doses, and the interval between doses on antibody production and longevity of response. Results: We find evidence that individuals over 35 years of age who received a second dose of ChAdOx1-S generate a persistent antibody response suggestive of long-lived plasma cell induction, while individuals that receive two doses of BNT162b2, or one dose of either vaccine do not. We also find that plasamblast productive capacity, the likely driver of short-term antibody responses, is greater in younger people than older people (≤ 4.5 fold change in point estimates), people vaccinated with two doses than people vaccinated with one dose (≤ 12 fold change), and people vaccinated with BNT162b2 than people vaccinated with ChAdOx1-S (≤ 440 fold change). The effect of age on antibody dynamics is more pronounced in people vaccinated with BNT162b2 than people vaccinated with ChAdOx1-S. We find the half-life of an antibody to be between 23 - 106 days. Conclusion: Routinely-collected seroprevalence data are a valuable source of information for characterising within-host mechanisms of antibody production and persistence. Extended sampling and linking seroprevalence data to outcomes would allow for powerful conclusions about how humoral kinetics protect against disease. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement DS is supported by Engineering and Physical Sciences Research council (EPSRC) PhD studentship (grant number EP/W524414/1). We would like to acknowledge the help and support of the JUNIPER partnership (MRC grant no MR/X018598/1) which EBP, LD and DS are affiliated with. EBP receives funding from the NIHR Health Protection Research Unit in Behavioural Science and Evaluation at University of Bristol. LD is further supported by Pfizer through investigator-led grants on respiratory tract infections. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The United Kingdom Health and Security Agency (UKHSA) dataset can be accessed by researchers; approval is on a project-by-project basis (https://orchid. phc.ox.ac.uk/index.php/orchid-data/). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The United Kingdom Health and Security Agency (UKHSA) dataset can be accessed by researchers; approval is on a project-by-project basis (https://orchid. phc.ox.ac.uk/index.php/orchid-data/).