Estimating decay curves of neutralizing antibodies to SARS-CoV-2 infection.

IF 0.8 4区 数学 Q4 BIOLOGY Mathematical Medicine and Biology-A Journal of the Ima Pub Date : 2022-12-02 DOI:10.1093/imammb/dqac008
Elliot Poehler, Liam Gibson, Audrey Lustig, Nicole J Moreland, Reuben McGregor, Alex James
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引用次数: 4

Abstract

Estimating the longevity of an individual's immune response to the SARS-Cov-2 virus is vital for future planning, particularly of vaccine requirements. Neutralizing antibodies (Nabs) are increasingly being recognized as a correlate of protection and while there are many studies that follow the response of a cohort of people, each study alone is not enough to predict the long-term response. Studies use different assays to measure Nabs, making them hard to combine. We present a modelling method that can combine multiple datasets and can be updated as more detailed data becomes available. Combining data from seven published datasets we predict that the NAb decay has two phases, an initial fast but short-lived decay period followed by a longer term and slower decay period.

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估计SARS-CoV-2感染中和抗体的衰减曲线。
估计个体对SARS-Cov-2病毒免疫反应的持续时间对于未来规划,特别是疫苗需求至关重要。中和抗体(nab)越来越被认为是一种相关的保护,尽管有许多研究跟踪了一群人的反应,但每项研究都不足以预测长期反应。研究使用不同的分析方法来测量nab,这使得它们很难结合起来。我们提出了一种建模方法,可以结合多个数据集,并可以随着更详细的数据变得可用而更新。结合七个已发表的数据集的数据,我们预测NAb衰变有两个阶段,一个最初的快速但短暂的衰变期,然后是一个较长且较慢的衰变期。
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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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