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Publications

Journal Article Research Support, Non-U.S. Gov't Ppublish 10 citations

PubMed: 36773843 DOI: 10.1016/j.mbs.2023.108970

A mathematical model of protein subunits COVID-19 vaccines.

Math Biosci 358:108970

Authors: Samaneh Gholami, Chapin S Korosec, Suzan Farhang-Sardroodi, David W Dick, Morgan Craig, Mohammad Sajjad Ghaemi, Hsu Kiang Ooi, Jane M Heffernan

Affiliations

  • Modelling Infection & Immunity Lab, Centre for Disease Modelling, Mathematics & Statistics, York University, Toronto, Ontario, Canada.
  • Modelling Infection & Immunity Lab, Centre for Disease Modelling, Mathematics & Statistics, York University, Toronto, Ontario, Canada.
  • Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada; Modelling Infection & Immunity Lab, Centre for Disease Modelling, Mathematics & Statistics, York University, Toronto, Ontario, Canada.
  • Sainte-Justine University Hospital Research Centre and Department of Mathematics and Statistics, Université de Montréal, Montreal, Quebec, Canada.
  • Digital Technologies Research Centre, National Research Council Canada, Toronto, ON, Canada.

Abstract

We consider a general mathematical model for protein subunit vaccine with a focus on the MF59-adjuvanted spike glycoprotein-clamp vaccine for SARS-CoV-2, and use the model to study immunological outcomes in the humoral and cell-mediated arms of the immune response from vaccination. The mathematical model is fit to vaccine clinical trial data. We elucidate the role of Interferon-γ and Interleukin-4 in stimulating the immune response of the host. Model results, and results from a sensitivity analysis, show that a balance between the T1 and T2 arms of the immune response is struck, with the T1 response being dominant. The model predicts that two-doses of the vaccine at 28 days apart will result in approximately 85% humoral immunity loss relative to peak immunity approximately 6 months post dose 1.

MeSH

Vaccines, Covid-19 Vaccines, Biometry, Protein Subunits, Covid-19, Immunity, Mathematics

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