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. 2023 Jul 27;7(10):1729–1739. doi: 10.1038/s41562-023-01660-3

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© The Author(s) 2023

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. 4 — The ‘Before pandemic’ label corresponds to the period from April 2019 to February 2020, while the ‘During pandemic’ corresponds to the period between April 2020 and February 2021. a, The correlation between the NS-SEC classes and the population income (N = 316 English local authorities). The classes coloured in pink and purple have positive and negative correlations with the population income. The box plot consists of boxes that span from the 25th percentile (Q1) to the 75th percentile (Q3), with median values (50th percentile) represented by a central line. The minimum and maximum values are determined by subtracting 1.5 times the interquartile range (IQR) from Q1 and adding 1.5 times the IQR to Q3, respectively. Also shown is the radius of gyration/mobility synchronization of each NS-SEC class before and during the pandemic. b, The differences between the first and second lockdowns in the spatio-temporal metrics.