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. 2020 Nov 26;3:711. doi: 10.1038/s42003-020-01439-6

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© The Author(s) 2020

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 — Proportion of clinical resistant invasive E. coli isolates to aminopenicillins a, fluoroquinolones b, third-generation cephalosporins c, and aminoglycosides d against relative intI1 integrase gene abundance in sewage. Proportion of urban population is shown with different shades of blue and size of point corresponds to basic sanitation index. The blue lines show the fitted clinical resistance from the beta regression model with socioeconomical factors and relative intI1 abundance (see text for details). Three different socioeconomical scenarios (blue lines) have been fitted to the model to shown how sewage data correlates with clinical resistance. Dark blue line: lower quartile (25%), blue: mean quantile (50%) and light blue: upper quantile (75%) of socioeconomical factors fitted to the model. Note that GDP is not shown in the plots, but is included in all models and fitted lines.