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. 2021 Jul 23;11:15121. doi: 10.1038/s41598-021-94601-x

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© The Author(s) 2021

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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Local spatial autocorrelation of malaria inequality as Local Getis-Ord Gi* at the Primary Sampling Unit (PSU) level. Malaria inequality relative to wealth index (WI) in the (A) absolute and (B) relative scales, and relative to mothers’ highest educational level (MHEL) in the (C) absolute and (D) relative scales. The maps were generated using R software v.4.0.1 (R: A language and environment for statistical computing, R Core Team, R Foundation for Statistical Computing, Vienna, Australia (2021) http://www.R-project.org/) with ggplot2 3.3.2 (H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.) and country boundaries from Natural Earth (https://www.naturalearthdata.com/) using the package spData 0.3.1 (https://nowosad.github.io/spData).