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Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention

BACKGROUND: Adequate resource allocation is critical in the battle against HIV/AIDS, especially in Africa. The determination of the location and nature of HIV services to implement must comply with the geographic, social and behavioral characteristics of patients. We therefore investigated the spati...

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Autores principales: Barankanira, Emmanuel, Molinari, Nicolas, Niyongabo, Théodore, Laurent, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4743168/
https://www.ncbi.nlm.nih.gov/pubmed/26847711
http://dx.doi.org/10.1186/s12889-016-2760-3
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author Barankanira, Emmanuel
Molinari, Nicolas
Niyongabo, Théodore
Laurent, Christian
author_facet Barankanira, Emmanuel
Molinari, Nicolas
Niyongabo, Théodore
Laurent, Christian
author_sort Barankanira, Emmanuel
collection PubMed
description BACKGROUND: Adequate resource allocation is critical in the battle against HIV/AIDS, especially in Africa. The determination of the location and nature of HIV services to implement must comply with the geographic, social and behavioral characteristics of patients. We therefore investigated the spatial heterogeneity of HIV prevalence in Burundi and then assessed the association of social and behavioral characteristics with HIV infection accounting for the spatial heterogeneity. METHODS: We used data from the 2010 Demographic and Health Survey. We analyzed these data with a geostatistical approach (which takes into account spatial autocorrelation) by i) interpolating HIV data using the kernel density estimation, ii) identifying the spatial clusters with high and low HIV prevalence using the Kulldorff spatial scan statistics, and then iii) performing a multivariate spatial logistic regression. RESULTS: Overall HIV prevalence was 1.4 %. The interpolated data showed the great spatial heterogeneity of HIV prevalence (from 0 to 10 %), independently of administrative boundaries. A cluster with high HIV prevalence was found in the capital city and adjacent areas (3.9 %; relative risk 3.7, p < 0.001) whereas a cluster with low prevalence straddled two southern provinces (0 %; p = 0.02). By multivariate spatial analysis, HIV infection was significantly associated with the female sex (posterior odds ratio [POR] 1.36, 95 % credible interval [CrI] 1.13-1.64), an older age (POR 1.97, 95 % CrI 1.26-3.08), the level of education (POR 1.50, 95 % CrI 1.22-1.84), the marital status (POR 1.86, 95 % CrI 1.23-2.80), a higher wealth index (POR 2.11, 95 % CrI 1.77-2.51), the sexual activity (POR 1.76, 95 % CrI 1.04-2.96), and a history of sexually transmitted infection (POR 2.03, 95 % CrI 1.56-2.64). CONCLUSIONS: Our study, which shows where and towards which populations HIV resources should be allocated, could help national health policy makers develop an effective HIV intervention in Burundi. Our findings support the strategy of the Joint United Nations Programme on HIV/AIDS (UNAIDS) for country-specific, in-depth analyses of HIV epidemics to tailor national prevention responses.
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spelling pubmed-47431682016-02-06 Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention Barankanira, Emmanuel Molinari, Nicolas Niyongabo, Théodore Laurent, Christian BMC Public Health Research Article BACKGROUND: Adequate resource allocation is critical in the battle against HIV/AIDS, especially in Africa. The determination of the location and nature of HIV services to implement must comply with the geographic, social and behavioral characteristics of patients. We therefore investigated the spatial heterogeneity of HIV prevalence in Burundi and then assessed the association of social and behavioral characteristics with HIV infection accounting for the spatial heterogeneity. METHODS: We used data from the 2010 Demographic and Health Survey. We analyzed these data with a geostatistical approach (which takes into account spatial autocorrelation) by i) interpolating HIV data using the kernel density estimation, ii) identifying the spatial clusters with high and low HIV prevalence using the Kulldorff spatial scan statistics, and then iii) performing a multivariate spatial logistic regression. RESULTS: Overall HIV prevalence was 1.4 %. The interpolated data showed the great spatial heterogeneity of HIV prevalence (from 0 to 10 %), independently of administrative boundaries. A cluster with high HIV prevalence was found in the capital city and adjacent areas (3.9 %; relative risk 3.7, p < 0.001) whereas a cluster with low prevalence straddled two southern provinces (0 %; p = 0.02). By multivariate spatial analysis, HIV infection was significantly associated with the female sex (posterior odds ratio [POR] 1.36, 95 % credible interval [CrI] 1.13-1.64), an older age (POR 1.97, 95 % CrI 1.26-3.08), the level of education (POR 1.50, 95 % CrI 1.22-1.84), the marital status (POR 1.86, 95 % CrI 1.23-2.80), a higher wealth index (POR 2.11, 95 % CrI 1.77-2.51), the sexual activity (POR 1.76, 95 % CrI 1.04-2.96), and a history of sexually transmitted infection (POR 2.03, 95 % CrI 1.56-2.64). CONCLUSIONS: Our study, which shows where and towards which populations HIV resources should be allocated, could help national health policy makers develop an effective HIV intervention in Burundi. Our findings support the strategy of the Joint United Nations Programme on HIV/AIDS (UNAIDS) for country-specific, in-depth analyses of HIV epidemics to tailor national prevention responses. BioMed Central 2016-02-04 /pmc/articles/PMC4743168/ /pubmed/26847711 http://dx.doi.org/10.1186/s12889-016-2760-3 Text en © Barankanira et al. 2016 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 Article
Barankanira, Emmanuel
Molinari, Nicolas
Niyongabo, Théodore
Laurent, Christian
Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention
title Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention
title_full Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention
title_fullStr Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention
title_full_unstemmed Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention
title_short Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention
title_sort spatial analysis of hiv infection and associated individual characteristics in burundi: indications for effective prevention
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4743168/
https://www.ncbi.nlm.nih.gov/pubmed/26847711
http://dx.doi.org/10.1186/s12889-016-2760-3
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