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. 2018 Dec 7;8:17722. doi: 10.1038/s41598-018-36116-6

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© The Author(s) 2018

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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The network of close proximity interactions. (a) The full network contains interactions with signal strength used as a proxy for a proximity. In this illustration the dynamic network is integrated over time; edges represent single interactions between participants, and line-width indicates physical proximity. From this full network, corresponding to all edges that support full-range transmission, we create the short-range network by only considering interactions with γ_ijt ≥ −75 dBm. The sampled long-range network contains the same number of interactions but chosen at random. (b) The link weights (i, j) are broadly distributed. The dashed line is a power-law p(x) ~ x^−α with α = 1.19 inserted as a guide to the eye. The sampled long-range network (orange) has the same number of interactions γ_ijt as the short-range network (blue), but maintains 62% of links, compared to only 31% of links remaining in the short-range network (inset).