Department of Mathematics, Virginia Polytechnic Institute and State University, 225 Stanger Street, Blacksburg, 24060, VA, USA; Virginia Tech Center for the Mathematics of Biosystems, Virginia Tech, Blacksburg, VA, USA.
Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, USA.
Math Biosci. 2024 Oct;376:109274. doi: 10.1016/j.mbs.2024.109274. Epub 2024 Aug 30.
Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in transient antibody response against the spike protein. The individual immune status at the time of vaccination influences the response. Using mathematical models of antibody decay, we determined the dynamics of serum immunoglobulin G (IgG) and serum immunoglobulin A (IgA) over time. Data fitting to longitudinal IgG and IgA titers was used to quantify differences in antibody magnitude and antibody duration among infection-naïve and infection-positive vaccinees. We found that prior infections result in more durable serum IgG and serum IgA responses, with prior symptomatic infections resulting in the most durable serum IgG response and prior asymptomatic infections resulting in the most durable serum IgA response. These findings can guide vaccine boosting schedules.
接种严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)疫苗会导致针对刺突蛋白的短暂抗体反应。接种疫苗时的个体免疫状态会影响反应。我们使用抗体衰减的数学模型来确定血清免疫球蛋白 G(IgG)和血清免疫球蛋白 A(IgA)随时间的变化。对纵向 IgG 和 IgA 滴度进行数据拟合,以量化感染前和感染后疫苗接种者之间抗体幅度和抗体持续时间的差异。我们发现先前的感染会导致更持久的血清 IgG 和血清 IgA 反应,其中有症状感染会导致最持久的血清 IgG 反应,无症状感染会导致最持久的血清 IgA 反应。这些发现可以指导疫苗加强免疫计划。