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. 2020 Sep 2;101(3):1901–1919. doi: 10.1007/s11071-020-05854-6

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© The Author(s) 2020

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. 7 — A zoomed section of the graph of lead–lag relationships between internal mobility (origin) and cumulative excess deaths (destination). Full network is shown in Fig. 8. The graph is zoomed on Haut-Rhin. This cluster shows that the internal mobility of Haut-Rhin correlates maximally with the cumulative excess deaths of several other departments at different lags. The width of the edges is inversely proportional to the estimated lag: the smaller the lag, the thicker the edge. Red edges connect two different clusters. No causality effect should be read from this graph. (Color figure online)