Predicting age-related determinants of heterogeneous outcomes to COVID-19 mRNA vaccines through mathematical modelling

Source abstract

ABSTRACT Older adults tend to exhibit weaker vaccine-elicited responses to mRNA COVID-19 immunization than younger people. This is a public health concern, as older individuals are more likely to experience severe COVID-19. To better understand the mechanisms of this age-related disparity, we developed a mathematical model of the post-vaccination humoral immune response. Through calibration to clinical data from 32 healthcare workers (HCWs) and 27 seniors who received the primary vaccine series (two priming doses and one booster), our model predicted that repeated vaccinations consistently enhanced antibody responses in both groups. While seniors were estimated to experience an accelerated decay in T follicular helper cells compared to HCWs, a larger booster dose effectively compensated for this weakened antibody response. Furthermore, we linked antibody and neutralization levels and used this relationship to predict post-vaccination neutralization, thus serving as a proxy for vaccine efficacy. By studying various combinations of mixed doses sizes in the primary vaccination series, our model predicted that administering a full-dose booster significantly enhances immunization outcomes, irrespective of the initial vaccine dose size. Further, a biannual half booster strategy was found to be more effective than one with an annual full booster, especially for seniors. Overall, our findings highlight the importance of tailoring vaccination strategies to different age groups to provide robust and long-lasting immunity against SARS-CoV-2 infections.