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. 2022 Oct 29;13:6484. doi: 10.1038/s41467-022-34186-9

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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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 6 — Left: Estimated Omicron arrivals (into the community) and recorded passenger arrivals (into the country). The black curve is equal to a smoothed sum of the five black curves in Fig. 5. The Omicron arrival rate appears to drop off at the start of June, but this is simply due to a lag between lineages arriving at the border and then being detected in the community by genomic surveillance. Right: Omicron arrivals can be explained by passenger arrivals into New Zealand. This linear model was built from the two curves in the left panel, restricted from after the border opened (3 Mar) until available genomic data starts to lag (30 May).