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COVID-19 疫苗接种后 SARS-CoV-2 中和抗体的宿主内动力学的数学模型。

A mathematical model of the within-host kinetics of SARS-CoV-2 neutralizing antibodies following COVID-19 vaccination.

机构信息

Department of Mathematics, Harvey Mudd College, 301 Platt Blvd., Claremont, CA 91711, United States.

Aditxt, Inc. 737 N. Fifth Street, Suite 200, Richmond, VA 23219, United States.

出版信息

J Theor Biol. 2023 Jan 7;556:111280. doi: 10.1016/j.jtbi.2022.111280. Epub 2022 Oct 4.

Abstract

Compelling evidence continues to build to support the idea that SARS-CoV-2 Neutralizing Antibody (NAb) levels in an individual can serve as an important indicator of the strength of protective immunity against infection. It is not well understood why NAb levels in some individuals remain high over time, while in others levels decline rapidly. In this work, we present a two-state mathematical model of within-host NAb dynamics in response to vaccination. By fitting only four host-specific parameters, the model is able to capture individual-specific NAb levels over time as measured by the AditxtScore™ for NAbs. The model can serve as a foundation for predicting NAb levels in the long-term, understanding connections between NAb levels, protective immunity, and breakthrough infections, and potentially guiding decisions about whether and when a booster vaccination may be warranted.

摘要

越来越多的有力证据支持这样一种观点,即个体中的 SARS-CoV-2 中和抗体 (NAb) 水平可以作为对感染的保护免疫强度的重要指标。目前尚不清楚为什么有些人的 NAb 水平会随着时间的推移而持续升高,而另一些人的水平则迅速下降。在这项工作中,我们提出了一个针对疫苗接种的宿主内 NAb 动力学的两状态数学模型。通过仅拟合四个宿主特异性参数,该模型能够捕获个体特异性 NAb 水平,这些水平是通过 AditxtScore™ 对 NAb 进行测量的。该模型可以作为预测长期 NAb 水平的基础,帮助理解 NAb 水平、保护免疫和突破性感染之间的联系,并可能指导关于是否以及何时需要加强接种的决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/901b/9529354/13e2440d7d92/ga1_lrg.jpg

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