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对埃塞俄比亚新冠病毒血清流行率和变异株的长期监测可为免疫和交叉免疫提供预测。

Long-term monitoring of SARS-CoV-2 seroprevalence and variants in Ethiopia provides prediction for immunity and cross-immunity.

作者信息

Merkt Simon, Ali Solomon, Gudina Esayas Kebede, Adissu Wondimagegn, Gize Addisu, Muenchhoff Maximilian, Graf Alexander, Krebs Stefan, Elsbernd Kira, Kisch Rebecca, Betizazu Sisay Sirgu, Fantahun Bereket, Bekele Delayehu, Rubio-Acero Raquel, Gashaw Mulatu, Girma Eyob, Yilma Daniel, Zeynudin Ahmed, Paunovic Ivana, Hoelscher Michael, Blum Helmut, Hasenauer Jan, Kroidl Arne, Wieser Andreas

机构信息

Life and Medical Sciences (LIMES), University of Bonn, Bonn, Germany.

Saint Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia.

出版信息

Nat Commun. 2024 Apr 24;15(1):3463. doi: 10.1038/s41467-024-47556-2.

Abstract

Under-reporting of COVID-19 and the limited information about circulating SARS-CoV-2 variants remain major challenges for many African countries. We analyzed SARS-CoV-2 infection dynamics in Addis Ababa and Jimma, Ethiopia, focusing on reinfection, immunity, and vaccination effects. We conducted an antibody serology study spanning August 2020 to July 2022 with five rounds of data collection across a population of 4723, sequenced PCR-test positive samples, used available test positivity rates, and constructed two mathematical models integrating this data. A multivariant model explores variant dynamics identifying wildtype, alpha, delta, and omicron BA.4/5 as key variants in the study population, and cross-immunity between variants, revealing risk reductions between 24% and 69%. An antibody-level model predicts slow decay leading to sustained high antibody levels. Retrospectively, increased early vaccination might have substantially reduced infections during the delta and omicron waves in the considered group of individuals, though further vaccination now seems less impactful.

摘要

对于许多非洲国家而言,新冠病毒病(COVID-19)报告不足以及有关正在传播的严重急性呼吸综合征冠状病毒2(SARS-CoV-2)变体的信息有限仍然是重大挑战。我们分析了埃塞俄比亚亚的斯亚贝巴和吉马的SARS-CoV-2感染动态,重点关注再感染、免疫力和疫苗接种效果。我们开展了一项从2020年8月至2022年7月的抗体血清学研究,在4723人的群体中进行了五轮数据收集,对聚合酶链反应(PCR)检测呈阳性的样本进行测序,利用可用的检测阳性率,并构建了两个整合这些数据的数学模型。一个多变量模型探索变体动态,确定野生型、阿尔法、德尔塔和奥密克戎BA.4/5为研究人群中的关键变体,以及变体之间的交叉免疫,显示风险降低24%至69%。一个抗体水平模型预测抗体水平下降缓慢,导致抗体水平持续处于高位。回顾来看,在考虑的个体群体中,早期增加疫苗接种可能会在德尔塔和奥密克戎疫情期间大幅减少感染,不过现在进一步接种疫苗似乎效果较小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34aa/11043357/faa49c880a88/41467_2024_47556_Fig1_HTML.jpg

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