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Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso

BACKGROUND: Previous research on determinants of malaria in Burkina Faso has largely focused on individual risk factors. Malaria risk, however, is also shaped by community, health system, and climatic/environmental characteristics. The aims of this study were: i) to identify such individual, househo...

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Autores principales: Samadoulougou, Sekou, Maheu-Giroux, Mathieu, Kirakoya-Samadoulougou, Fati, De Keukeleire, Mathilde, Castro, Marcia C, Robert, Annie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262087/
https://www.ncbi.nlm.nih.gov/pubmed/25074132
http://dx.doi.org/10.1186/1756-3305-7-350
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author Samadoulougou, Sekou
Maheu-Giroux, Mathieu
Kirakoya-Samadoulougou, Fati
De Keukeleire, Mathilde
Castro, Marcia C
Robert, Annie
author_facet Samadoulougou, Sekou
Maheu-Giroux, Mathieu
Kirakoya-Samadoulougou, Fati
De Keukeleire, Mathilde
Castro, Marcia C
Robert, Annie
author_sort Samadoulougou, Sekou
collection PubMed
description BACKGROUND: Previous research on determinants of malaria in Burkina Faso has largely focused on individual risk factors. Malaria risk, however, is also shaped by community, health system, and climatic/environmental characteristics. The aims of this study were: i) to identify such individual, household, community, and climatic/environmental risk factors for malaria in children under five years of age, and ii) to produce a parasitaemia risk map of Burkina Faso. METHODS: The 2010 Demographic and Health Survey (DHS) was the first in Burkina Faso that tested children for malaria parasitaemia. Multilevel and geo-statistical models were used to explore determinants of malaria using this nationally representative database. RESULTS: Parasitaemia was collected from 6,102 children, of which 66.0% (95% confidence interval (CI): 64.0-68.0%) were positive for Plasmodium spp. Older children (>23 months) were more likely to be parasitaemic than younger ones, while children from wealthier households and whose mother had higher education were at a lower risk. At the community level, living in a district with a rate of attendance to health facilities lower than 2 visits per year was significantly associated with greater odds of being infected. Malaria prevalence was also associated with higher normalized difference vegetation index, lower average monthly rainfall, and lower population densities. Predicted malaria parasitaemia was spatially variable with locations falling within an 11%-92% prevalence range. The number of parasitaemic children was nonetheless concentrated in areas of high population density, albeit malaria risk was notably higher in the sparsely populated rural areas. CONCLUSION: Malaria prevalence in Burkina Faso is considerably higher than in neighbouring countries. Our spatially-explicit population-based estimates of malaria risk and infected number of children could be used by local decision-makers to identify priority areas where control efforts should be enhanced. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1756-3305-7-350) contains supplementary material, which is available to authorized users.
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spelling pubmed-42620872014-12-11 Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso Samadoulougou, Sekou Maheu-Giroux, Mathieu Kirakoya-Samadoulougou, Fati De Keukeleire, Mathilde Castro, Marcia C Robert, Annie Parasit Vectors Research BACKGROUND: Previous research on determinants of malaria in Burkina Faso has largely focused on individual risk factors. Malaria risk, however, is also shaped by community, health system, and climatic/environmental characteristics. The aims of this study were: i) to identify such individual, household, community, and climatic/environmental risk factors for malaria in children under five years of age, and ii) to produce a parasitaemia risk map of Burkina Faso. METHODS: The 2010 Demographic and Health Survey (DHS) was the first in Burkina Faso that tested children for malaria parasitaemia. Multilevel and geo-statistical models were used to explore determinants of malaria using this nationally representative database. RESULTS: Parasitaemia was collected from 6,102 children, of which 66.0% (95% confidence interval (CI): 64.0-68.0%) were positive for Plasmodium spp. Older children (>23 months) were more likely to be parasitaemic than younger ones, while children from wealthier households and whose mother had higher education were at a lower risk. At the community level, living in a district with a rate of attendance to health facilities lower than 2 visits per year was significantly associated with greater odds of being infected. Malaria prevalence was also associated with higher normalized difference vegetation index, lower average monthly rainfall, and lower population densities. Predicted malaria parasitaemia was spatially variable with locations falling within an 11%-92% prevalence range. The number of parasitaemic children was nonetheless concentrated in areas of high population density, albeit malaria risk was notably higher in the sparsely populated rural areas. CONCLUSION: Malaria prevalence in Burkina Faso is considerably higher than in neighbouring countries. Our spatially-explicit population-based estimates of malaria risk and infected number of children could be used by local decision-makers to identify priority areas where control efforts should be enhanced. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1756-3305-7-350) contains supplementary material, which is available to authorized users. BioMed Central 2014-07-29 /pmc/articles/PMC4262087/ /pubmed/25074132 http://dx.doi.org/10.1186/1756-3305-7-350 Text en © Samadoulougou et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
Samadoulougou, Sekou
Maheu-Giroux, Mathieu
Kirakoya-Samadoulougou, Fati
De Keukeleire, Mathilde
Castro, Marcia C
Robert, Annie
Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso
title Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso
title_full Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso
title_fullStr Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso
title_full_unstemmed Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso
title_short Multilevel and geo-statistical modeling of malaria risk in children of Burkina Faso
title_sort multilevel and geo-statistical modeling of malaria risk in children of burkina faso
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262087/
https://www.ncbi.nlm.nih.gov/pubmed/25074132
http://dx.doi.org/10.1186/1756-3305-7-350
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