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. 2019 May 7;18:9. doi: 10.1186/s12942-019-0173-0

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© The Author(s) 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 5 — Performance of CS based model predictions compared to actual CDC reported Lyme disease cases in 2016. Four elements have been included to improve interpretation: (1) 1:1 black line indicating a perfect model; (2) grey ribbon indicating one standard deviation of the reported Lyme disease cases from the 1:1 line; and (3) points colored based on U.S. Census Division (New England = blue, Middle Atlantic = red)