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Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana

BACKGROUND: Malaria remains a major challenge in sub-Saharan Africa and Ghana is not an exception. Effective malaria transmission control requires evidence-based targeting and utilization of resources. Disease risk mapping provides an effective and efficient tool for monitoring transmission and cont...

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Autores principales: Yankson, Robert, Anto, Evelyn Arthur, Chipeta, Michael Give
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419518/
https://www.ncbi.nlm.nih.gov/pubmed/30871551
http://dx.doi.org/10.1186/s12936-019-2709-y
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author Yankson, Robert
Anto, Evelyn Arthur
Chipeta, Michael Give
author_facet Yankson, Robert
Anto, Evelyn Arthur
Chipeta, Michael Give
author_sort Yankson, Robert
collection PubMed
description BACKGROUND: Malaria remains a major challenge in sub-Saharan Africa and Ghana is not an exception. Effective malaria transmission control requires evidence-based targeting and utilization of resources. Disease risk mapping provides an effective and efficient tool for monitoring transmission and control efforts. The aim of this study is to analyse and map malaria risk in children under 5 years old, with the ultimate goal of identifying areas where control efforts can be targeted. METHODS: Data collected from the 2016 Ghana demographic and health survey was analyzed. Binomial logistic regression was applied to examine the determinants of malaria risk among children. Model-based geostatistical methods were applied to analyze, predict and map malaria prevalence. RESULTS: There is a significant association of malaria prevalence with area of residence (rural/urban), age, indoor residual spray use, social economic status and mother’s education level. Overall, parasitaemia prevalence among children under 5 years old for the year 2016 is low albeit characterized by “hotspots” in specific areas. CONCLUSION: The risk maps indicate the spatial heterogeneity of malaria prevalence. The high resolution maps can serve as an effective tool in the identification of locations that require targeted interventions by programme implementers; this is key and relevant for reducing malaria burden in Ghana.
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spelling pubmed-64195182019-03-28 Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana Yankson, Robert Anto, Evelyn Arthur Chipeta, Michael Give Malar J Research BACKGROUND: Malaria remains a major challenge in sub-Saharan Africa and Ghana is not an exception. Effective malaria transmission control requires evidence-based targeting and utilization of resources. Disease risk mapping provides an effective and efficient tool for monitoring transmission and control efforts. The aim of this study is to analyse and map malaria risk in children under 5 years old, with the ultimate goal of identifying areas where control efforts can be targeted. METHODS: Data collected from the 2016 Ghana demographic and health survey was analyzed. Binomial logistic regression was applied to examine the determinants of malaria risk among children. Model-based geostatistical methods were applied to analyze, predict and map malaria prevalence. RESULTS: There is a significant association of malaria prevalence with area of residence (rural/urban), age, indoor residual spray use, social economic status and mother’s education level. Overall, parasitaemia prevalence among children under 5 years old for the year 2016 is low albeit characterized by “hotspots” in specific areas. CONCLUSION: The risk maps indicate the spatial heterogeneity of malaria prevalence. The high resolution maps can serve as an effective tool in the identification of locations that require targeted interventions by programme implementers; this is key and relevant for reducing malaria burden in Ghana. BioMed Central 2019-03-11 /pmc/articles/PMC6419518/ /pubmed/30871551 http://dx.doi.org/10.1186/s12936-019-2709-y Text en © 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.
spellingShingle Research
Yankson, Robert
Anto, Evelyn Arthur
Chipeta, Michael Give
Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana
title Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana
title_full Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana
title_fullStr Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana
title_full_unstemmed Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana
title_short Geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in Ghana
title_sort geostatistical analysis and mapping of malaria risk in children under 5 using point-referenced prevalence data in ghana
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6419518/
https://www.ncbi.nlm.nih.gov/pubmed/30871551
http://dx.doi.org/10.1186/s12936-019-2709-y
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