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. 2019 May 6;19:514. doi: 10.1186/s12889-019-6816-z

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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. 6 — Local Moran’s I cluster-outlier maps of malaria incidence for the years 2010 to 2014 and the average incidence with statistical inference based on Monte Carlo randomisation test at 999 permutations, showing significant pseudo p < 0.05 clusters of High-High (hotspot) and Low-Low (colspot); and outliers High-Low and Low-High. LISA: Local Indicator of Spatial Association. The maps were generated using GeoDa statistical software version 1.12