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Abstract
The lipid nanoparticle (LNP)-formulated mRNA vaccines BNT162b2 and mRNA-1273 are a widely adopted multi vaccination public health strategy to manage the COVID-19 pandemic. Clinical trial data has described the immunogenicity of the vaccine, albeit within a limited study time frame. Here, we use a within-host mathematical model for LNP-formulated mRNA vaccines, informed by available clinical trial data from 2020 to September 2021, to project a longer term understanding of immunity as a function of vaccine type, dosage amount, age, and sex. We estimate that two standard doses of either mRNA-1273 or BNT162b2, with dosage times separated by the company-mandated intervals, results in individuals losing more than 99% humoral immunity relative to peak immunity by 8 months following the second dose. We predict that within an 8 month period following dose two (corresponding to the original CDC time-frame for administration of a third dose), there exists a period of time longer than 1 month where an individual has lost more than 99% humoral immunity relative to peak immunity, regardless of which vaccine was administered. We further find that age has a strong influence in maintaining humoral immunity; by 8 months following dose two we predict that individuals aged 18–55 have a four-fold humoral advantage compared to aged 56–70 and 70+ individuals. We find that sex has little effect on the immune response and long-term IgG counts. Finally, we find that humoral immunity generated from two low doses of mRNA-1273 decays at a substantially slower rate relative to peak immunity gained compared to two standard doses of either mRNA-1273 or BNT162b2. Our predictions highlight the importance of the recommended third booster dose in order to maintain elevated levels of antibodies.
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Details
1 York University, Modelling Infection and Immunity Lab, Mathematics and Statistics, Toronto, Canada (GRID:grid.21100.32) (ISNI:0000 0004 1936 9430); York University, Centre for Disease Modelling, Mathematics and Statistics, Toronto, Canada (GRID:grid.21100.32) (ISNI:0000 0004 1936 9430)
2 York University, Centre for Disease Modelling, Mathematics and Statistics, Toronto, Canada (GRID:grid.21100.32) (ISNI:0000 0004 1936 9430); University of Manitoba, Department of Mathematics, Winnipeg, Canada (GRID:grid.21613.37) (ISNI:0000 0004 1936 9609)
3 National Research Council Canada, Digital Technologies Research Centre, Toronto, Canada (GRID:grid.24433.32) (ISNI:0000 0004 0449 7958)
4 Université de Montréal & Sainte-Justine University Hospital Research Centre, Department of Mathematics and Statistics, Montréal, Canada (GRID:grid.14848.31) (ISNI:0000 0001 2292 3357)