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2021/2022年秋冬德国基于全国人口的感染和疫苗诱导的新冠病毒抗体血清流行率

Nationwide population-based infection- and vaccine-induced SARS-CoV-2 antibody seroprevalence in Germany in autumn/winter 2021/2022.

作者信息

Mercuri Elisabetta, Schmid Lorenz, Poethko-Müller Christina, Schlaud Martin, Kußmaul Cânâ, Ordonez-Cruickshank Ana, Haller Sebastian, Rexroth Ute, Hamouda Osamah, Schaade Lars, Wieler Lothar H, Gößwald Antje, Schaffrath Rosario Angelika

机构信息

Robert Koch Institute (RKI), Berlin, Germany.

Max Planck Institute for Infection Biology, Berlin, Germany.

出版信息

Euro Surveill. 2025 Jan;30(1). doi: 10.2807/1560-7917.ES.2025.30.1.2400037.


DOI:10.2807/1560-7917.ES.2025.30.1.2400037
PMID:39790070
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11719803/
Abstract

BackgroundThe first Corona Monitoring Nationwide (RKI-SOEP) study (October 2020-February 2021) found a low pre-vaccine SARS-CoV-2 antibody seroprevalence (2.1%) in the German adult population (≥ 18 years).AimThe objective of this second RKI-SOEP (RKI-SOEP-2) study in November 2021-March 2022 was to estimate the prevalence of SARS-CoV-2-specific anti-spike and/or anti-nucleocapsid (anti-N) IgG antibodies (combined seroprevalence), past infection based on infection-induced seroprevalence (anti-N), and basic immunisation (at least two antigen contacts through vaccination or infection) in individuals aged ≥ 14 years. We also aimed to estimate under-reporting of infections.MethodsDried blood-spot specimens from a population-based sample embedded in a dynamic cohort, the Socio-Economic Panel (SOEP), were serologically analysed. Resulting serological data and self-reports via a questionnaire from the same individuals were used to estimate prevalences.ResultsCombined seroprevalence was 90.7% (95% CI: 89.7%-91.6%) without correction and 94.6% (95% CI: 93.6%-95.7%) with correction for sensitivity/specificity and antibody waning. While one in nine individuals had been infected (11.3%; 95% CI: 9.1%-13.5%), nine in 10 had a basic immunisation (90%; 95% CI: 88.9-90.9%), primarily due to vaccination. Population-weighted estimates differed by age, region, and socioeconomic deprivation. The under-reporting factor was estimated as 1.55 (95% CI: 1.3-1.8).ConclusionsWhen the SARS-CoV-2-Omicron wave was beginning, most people had been vaccinated, infected, or both. Large-scale vaccination, but not a high infection rate, was able to fill the immunity gap, especially in ≥ 65 year-olds who are known to be at higher risk of severe COVID-19. Our data point towards the need for targeted socioeconomically, demographically and regionally stratified mitigation strategies, including measures to enhance vaccine uptake.

摘要

背景 首次全国新冠监测(罗伯特·科赫研究所 - 社会经济面板研究)(2020年10月 - 2021年2月)发现德国成年人口(≥18岁)中疫苗接种前的新冠病毒抗体血清阳性率较低(2.1%)。 目的 这项于2021年11月至2022年3月开展的第二次罗伯特·科赫研究所 - 社会经济面板研究(RKI - SOEP - 2)的目的是估计14岁及以上个体中新冠病毒特异性抗刺突蛋白和/或抗核衣壳(抗N)IgG抗体的流行率(综合血清阳性率)、基于感染诱导血清阳性率(抗N)的既往感染情况以及基础免疫(通过疫苗接种或感染至少有两次抗原接触)情况。我们还旨在估计感染报告不足的情况。 方法 对嵌入动态队列社会经济面板(SOEP)中的基于人群样本的干血斑标本进行血清学分析。使用来自同一人群的血清学数据和通过问卷进行的自我报告来估计流行率。 结果 未经校正的综合血清阳性率为90.7%(95%置信区间:89.7% - 91.6%),经敏感性/特异性校正及抗体衰减校正后为94.6%(95%置信区间:93.6% - 95.7%)。虽然九分之一的个体曾被感染(11.3%;95%置信区间:9.1% - 13.5%),但十分之九的个体有基础免疫(90%;95%置信区间:88.9 - 90.9%),主要是由于接种疫苗。按人群加权的估计值因年龄、地区和社会经济贫困程度而异。感染报告不足因素估计为1.55(95%置信区间:1.3 - 1.8)。 结论 当新冠病毒奥密克戎毒株浪潮开始时,大多数人已接种疫苗、感染过或两者皆有。大规模疫苗接种而非高感染率能够填补免疫缺口,尤其是在已知感染新冠病毒严重风险较高的65岁及以上人群中。我们的数据表明需要制定有针对性的社会经济、人口和地区分层缓解策略,包括提高疫苗接种率的措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1d/11719803/4f40e18949e6/2400037-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1d/11719803/5b1d4df2db71/2400037-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1d/11719803/104cf5b677a4/2400037-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1d/11719803/4f40e18949e6/2400037-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1d/11719803/5b1d4df2db71/2400037-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1d/11719803/104cf5b677a4/2400037-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a1d/11719803/4f40e18949e6/2400037-f3.jpg

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本文引用的文献

[1]
Estimation of SARS-CoV-2 Seroprevalence in Central North Carolina: Accounting for Outcome Misclassification in Complex Sample Designs.

Epidemiology. 2023-9-1

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BMC Public Health. 2023-6-6

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