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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. 7 — a, b Malaria incidence conditional on basic education and (a) employment-to-population ratio (b) no/other religion where districts with relatively high rates due to co-location of the two risk factors were indicated in the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. c, d Malaria incidence conditioned on urban and (c) employment-to-population ratio, and (d) no/other religion where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. e, f, g Malaria rate conditional on intermigration and (e) intramigration, (f) no/other religion (g) agric households where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. h, i Malaria rate conditional on Intramigration and (h) No/other religion and (i) Agric households where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. j, k Malaria rate conditional on no/other religion and (j) Employment-to-population ratio (k) Agric household where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12