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. 2022 Nov 12;212(1):13–23. doi: 10.1007/s00430-022-00752-7

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© The Author(s) 2022

Open AccessThis 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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Fig. 1 — SARS-CoV-2 viral load distribution of respiratory samples included in the study. A Shown is the log10 viral load (Geq/ml) of 70 SARS-CoV-2-positive Omicron-BA.1 (blue) and 70 SARS-CoV-2-positive Omicron-BA.2 (red) patient samples, sorted by ascending magnitude of the viral load from left to right. Each dot indicates one patient and the sample’s ID is indicated. B Shown is the correlation of the viral loads (Geq/ml) for both Omicron-BA.1 and -BA.2 to the Ct-values, which were obtained with the Cobas 6800 system. C Depicted is the histogram of the viral load distribution for Omicron-BA.1 by categorization of samples into defined log10 viral load ranges. Each histogram bar indicates the number of samples in the respective viral load range. D Depicted is the histogram of the viral load distribution for Omicron-BA.2 by categorization of samples into defined log10 viral load ranges. Each bar indicates the number of samples in the respective viral load range