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. 2021 Oct 30;21:1119. doi: 10.1186/s12879-021-06810-4

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© The Author(s) 2021

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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — A, B Multiple Correspondence Analysis of 1125 cases, 349 probable cases and 4750 non-cases presenting for SARS-CoV-2 PCR testing during the first wave of COVID-19 in New Zealand, showing the correlation between symptom variables A and supplementary variables B with the first two dimensions, which accounted for ~ 30% of the variation. Supplementary variables were age category (magenta), priority ethnicity (blue), sex (black), disease status (grey) and month of year (green). The blue box is expanded in (C, D). C, D Multiple Correspondence Analysis showing the correlation between symptom variables C and supplementary variables D with the first two dimensions, with the axes cropped as indicated by the blue boxes in (A, B)