Saha Ananya, Ahmed Hasan, Hirst Cora, Koelle Katia, Handel Andreas, Teunis Peter, Antia Rustom
Department of Biology, Emory University, Atlanta, GA 30322, USA.
Department of Epidemiology and Biostatistics, University of Georgia, GA 30602, USA.
medRxiv. 2025 May 14:2025.05.13.25327542. doi: 10.1101/2025.05.13.25327542.
Immunological memory is a defining feature of immunity, yet surprisingly there is no consensus on how to quantitatively describe how antibody titers wane over time. A major problem is that the slow waning of antibody titers requires the collection of data for decades post-infection or vaccination. Our analysis of the largest existing dataset shows that a power-law model describes antibody waning better than other frequently used models. Our analysis suggests: (i) Protective levels of antibodies to many vaccine/virus antigens may be maintained for longer than previously estimated. (ii) The rate of waning of antibodies to protein toxoid vaccines such as tetanus may be similar to those elicited by live virus infections. (iii) The long-term waning of antibodies can be estimated from data for a much shorter time-frame of about 1-3 years following immunization, suggesting that using a power-law analysis could allow rapid estimation for the waning of immunity to new vaccines.
免疫记忆是免疫的一个决定性特征,但令人惊讶的是,对于如何定量描述抗体滴度随时间的下降,目前尚无共识。一个主要问题是,抗体滴度的缓慢下降需要在感染或接种疫苗后数十年收集数据。我们对现有最大数据集的分析表明,幂律模型比其他常用模型更能描述抗体的下降情况。我们的分析表明:(i)针对许多疫苗/病毒抗原的保护性抗体水平可能比先前估计的维持时间更长。(ii)针对破伤风等蛋白质类毒素疫苗的抗体下降速率可能与活病毒感染引发的抗体下降速率相似。(iii)抗体的长期下降情况可以根据免疫后约1至3年这一短得多的时间框架内的数据进行估计,这表明使用幂律分析可以快速估计对新疫苗免疫力的下降情况。