Quantifying age-associated differences in the durability of Shingrix-induced immunity using mathematical modelling
- 1Universite de Montreal/Centre de recherche Azrieli du CHU Sainte-Justine
Abstract
Understanding the durability of vaccine-induced immunity is critical for evaluating long-term protection and vaccine scheduling, particularly in aging populations where immunosenescence may alter immune response dynamics. In this study, we used a novel mathematical modelling pipeline to quantify age-related differences in the contraction and persistence phases of gE-specific CD4+ T cell and anti-gE antibody responses following Shingrix vaccination. Specifically, we developed a semi-mechanistic model to expand virtual populations that captured inter-individual variability in peak concentrations and waning dynamics. To compare immune responses across age groups, we introduced a time varying, age-related immune advantage metric that measures the probability of a randomly selected younger individual exhibiting a stronger immune response than one from an older group. By evaluating this metric across multiple simulated virtual populations, our results demonstrate clear and sustained age-related differences in both gE-specific CD4+ T cells and anti-gE antibody responses, with younger age groups consistently exhibiting higher responses. Given these age-related differences, we used our model to explore alternative vaccine schedules in older age groups. These exploratory simulations suggest that booster doses administered between 6 and 12 months following the second dose may mitigate age-related differences in antibody dynamics. This work highlights the use of mechanistic mathematical modelling to disentangle age-associated differences in vaccine outcomes and lead to designing of plausible improvement in age-specific vaccine schedules.
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BibTeX
@misc{easlick2026quantifying,
title = {{Quantifying age-associated differences in the durability of Shingrix-induced immunity using mathematical modelling}},
author = {T. Easlick and G. De La Rosa and S. Gantt and H. Qin and L. R. Shelton and D. Skibinski and M. Craig},
howpublished = {medRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.10.26367539},
url = {https://www.medrxiv.org/content/10.64898/2026.11.10.26367539v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Quantifying age-associated differences in the durability of Shingrix-induced immunity using mathematical modelling
AU - T. Easlick
AU - G. De La Rosa
AU - S. Gantt
AU - H. Qin
AU - L. R. Shelton
AU - D. Skibinski
AU - M. Craig
PY - 2026
DA - 2026/11/10
PB - medRxiv
DO - 10.64898/2026.11.10.26367539
UR - https://www.medrxiv.org/content/10.64898/2026.11.10.26367539v1
AB - Understanding the durability of vaccine-induced immunity is critical for evaluating long-term protection and vaccine scheduling, particularly in aging populations where immunosenescence may alter immune response dynamics. In this study, we used a novel mathematical modelling pipeline to quantify age-related differences in the contraction and persistence phases of gE-specific CD4+ T cell and anti-gE antibody responses following Shingrix vaccination. Specifically, we developed a semi-mechanistic model to expand virtual populations that captured inter-individual variability in peak concentrations and waning dynamics. To compare immune responses across age groups, we introduced a time varying, age-related immune advantage metric that measures the probability of a randomly selected younger individual exhibiting a stronger immune response than one from an older group. By evaluating this metric across multiple simulated virtual populations, our results demonstrate clear and sustained age-related differences in both gE-specific CD4+ T cells and anti-gE antibody responses, with younger age groups consistently exhibiting higher responses. Given these age-related differences, we used our model to explore alternative vaccine schedules in older age groups. These exploratory simulations suggest that booster doses administered between 6 and 12 months following the second dose may mitigate age-related differences in antibody dynamics. This work highlights the use of mechanistic mathematical modelling to disentangle age-associated differences in vaccine outcomes and lead to designing of plausible improvement in age-specific vaccine schedules.
ER -