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通过核衣壳抗体轨迹聚类识别未检测到的新冠病毒感染

Identification of undetected SARS-CoV-2 infections by clustering of Nucleocapsid antibody trajectories.

作者信息

Zwerwer Leslie R, Peto Tim E A, Pouwels Koen B, Walker Ann Sarah

机构信息

Nuffield Department of Medicine, University of Oxford, Oxford, UK.

Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

出版信息

Nat Commun. 2025 May 14;16(1):4466. doi: 10.1038/s41467-025-57370-z.

Abstract

During the COVID-19 pandemic, numerous SARS-CoV-2 infections remained undetected. We combined results from routine monthly nose and throat swabs, and self-reported positive swab tests, from a UK household survey, linked to national swab testing programme data from England and Wales, together with Nucleocapsid (N-)antibody trajectories clustered using a longitudinal variation of K-means (N = 185,646) to estimate the number of infections undetected by either approach. Using N-antibody (hypothetical) infections and swab-positivity, we estimated that 7.4% (95%CI: 7.0-7.8%) of all true infections (detected and undetected) were undetected by both approaches, 25.8% (25.5-26.1%) by swab-positivity-only and 28.6% (28.4-28.9%) by trajectory-based N-antibody-classifications-only. Congruence with swab-positivity was respectively much poorer and slightly better with N-antibody classifications based on fixed thresholds or fourfold increases. Using multivariable logistic regression N-antibody seroconversion was more likely as age increased between 30-60 years, in non-white participants, those less (recently/frequently) vaccinated, for lower cycle threshold values in the range above 30, and in symptomatic and Delta (vs. BA.1) infections. Comparing swab-positivity data sources showed that routine monthly swabs were insufficient to detect infections and incorporating national testing programme/self-reported data substantially increased detection. Overall, whilst N-antibody serosurveillance can identify infections undetected by swab-positivity, optimal use requires fourfold-increase-based or trajectory-based analysis.

摘要

在新冠疫情期间,大量的新冠病毒感染未被发现。我们将英国家庭调查中每月例行的鼻拭子和咽拭子检测结果以及自我报告的阳性拭子检测结果与英格兰和威尔士的国家拭子检测计划数据相结合,并使用K均值纵向变化对核衣壳(N-)抗体轨迹进行聚类分析(N = 185,646),以估计两种方法均未检测到的感染数量。利用N抗体(假设的)感染情况和拭子检测阳性结果,我们估计,在所有真实感染(已检测到和未检测到的)中,两种方法均未检测到的占7.4%(95%置信区间:7.0 - 7.8%),仅通过拭子检测阳性未检测到的占25.8%(25.5 - 26.1%),仅通过基于轨迹的N抗体分类未检测到的占28.6%(28.4 - 28.9%)。基于固定阈值或四倍增长的N抗体分类与拭子检测阳性的一致性分别差得多和稍好一些。使用多变量逻辑回归分析发现,在30至60岁之间,非白人参与者、疫苗接种较少(近期/频繁)者、循环阈值在30以上范围内较低者以及有症状和感染德尔塔毒株(与BA.1毒株相比)的人群中,N抗体血清转化的可能性更大。比较拭子检测阳性数据来源表明,每月例行拭子检测不足以检测到感染,纳入国家检测计划/自我报告数据可大幅提高检测率。总体而言,虽然N抗体血清学监测可以识别拭子检测阳性未检测到的感染,但最佳使用需要基于四倍增长或基于轨迹的分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b85/12078723/a1ad7f944e93/41467_2025_57370_Fig1_HTML.jpg

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