[2A1-GS-10] AI application: Medicine / Healthcare

[2A1-GS-10-03] Modeling and prediction of individual differences in antibody dynamics following COVID-19 vaccination

〇Naotoshi Nakamura¹, Hyeongki Park¹, Masaharu Tsubokura², Shingo Iwami¹ (1. Nagoya University, 2. Fukushima Medical University)

Keywords:COVID-19 vaccine, Mathematical model, Time series analysis, Scoring

In the COVID-19 pandemic, vaccination was an important countermeasure. It is now known that after a person is vaccinated, antibody titers decline over time and efficacy declines, which can lead to breakthrough infections. Thus, it is important to identify immunocompromised populations with persistently low antibody titers in order to develop an effective vaccination strategy. In this study, we used a cohort in Fukushima prefecture vaccinated with COVID-19 vaccine and followed antibody titers over time. We reconstructed the individual-level dynamics of antibody titers using a mathematical model and identified individual variability. We also developed an antibody score that can predict individual antibody titers to some degree through simple calculations based on information such as underlying diseases and adverse reactions.