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. 2022 Nov 8;12:19020. doi: 10.1038/s41598-022-21317-x

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Empirical receiving operating characteristic (ROC) curve analysis for estimating optimal thresholds for sVNT assays targeting nAbs against SARS-CoV-2. (A) GenScript sVNT ROC curve in SARS-CoV-2 infected patients (n = 105). (B) GenScript sVNT ROC curve in COVID-19 vaccinated individuals (n = 24). (C) Dynamiker sVNT ROC curve in SARS-CoV-2 infected patients (n = 127). (D) Dynamiker sVNT ROC curve in COVID-19 vaccinated individuals (n = 156). (E) Mindray sVNT ROC curve in SARS-CoV-2 infected patients (n = 52). (F) Mindray sVNT ROC curve in COVID-19 vaccinated individuals (n = 155). The sensitivity and specificity values correspond to the plotted points which were used to estimate the area under the curve (AUC) and p-value for each curve.