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A decade of sustained geographic spread of HIV infections among women in Durban, South Africa

BACKGROUND: Fine scale geospatial analysis of HIV infection patterns can be used to facilitate geographically targeted interventions. Our objective was to use the geospatial technology to map age and time standardized HIV incidence rates over a period of 10 years to identify communities at high risk...

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Autores principales: Ramjee, Gita, Sartorius, Benn, Morris, Natashia, Wand, Handan, Reddy, Tarylee, Yssel, Justin D., Tanser, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555962/
https://www.ncbi.nlm.nih.gov/pubmed/31174475
http://dx.doi.org/10.1186/s12879-019-4080-6
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author Ramjee, Gita
Sartorius, Benn
Morris, Natashia
Wand, Handan
Reddy, Tarylee
Yssel, Justin D.
Tanser, Frank
author_facet Ramjee, Gita
Sartorius, Benn
Morris, Natashia
Wand, Handan
Reddy, Tarylee
Yssel, Justin D.
Tanser, Frank
author_sort Ramjee, Gita
collection PubMed
description BACKGROUND: Fine scale geospatial analysis of HIV infection patterns can be used to facilitate geographically targeted interventions. Our objective was to use the geospatial technology to map age and time standardized HIV incidence rates over a period of 10 years to identify communities at high risk of HIV in the greater Durban area. METHODS: HIV incidence rates from 7557 South African women enrolled in five community-based HIV prevention trials (2002–2012) were mapped using participant household global positioning system (GPS) coordinates. Age and period standardized HIV incidence rates were calculated for 43 recruitment clusters across greater Durban. Bayesian conditional autoregressive areal spatial regression (CAR) was used to identify significant patterns and clustering of new HIV infections in recruitment communities. RESULTS: The total person-time in the cohort was 9093.93 years and 613 seroconversions were observed. The overall crude HIV incidence rate across all communities was 6·74 per 100PY (95% CI: 6·22–7·30). 95% of the clusters had HIV incidence rates greater than 3 per 100PY. The CAR analysis identified six communities with significantly high HIV incidence. Estimated relative risks for these clusters ranged from 1.34 to 1.70. Consistent with these results, age standardized HIV incidence rates were also highest in these clusters and estimated to be 10 or more per 100 PY. Compared to women 35+ years old younger women were more likely to reside in the highest incidence areas (aOR: 1·51, 95% CI: 1·06–2·15; aOR: 1.59, 95% CI: 1·19–2·14 and aOR: 1·62, 95% CI: 1·2–2·18 for < 20, 20–24, 25–29 years old respectively). Partnership factors (2+ sex partners and being unmarried/not cohabiting) were also more common in the highest incidence clusters (aOR 1.48, 95% CI: 1.25–1.75 and aOR 1.54, 95% CI: 1.28–1.84 respectively). CONCLUSION: Fine geospatial analysis showed a continuous, unrelenting, hyper HIV epidemic in most of the greater Durban region with six communities characterised by particularly high levels of HIV incidence. The results motivate for comprehensive community-based HIV prevention approaches including expanded access to PrEP. In addition, a higher concentration of HIV related services is required in the highest risk communities to effectively reach the most vulnerable populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-4080-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-65559622019-06-10 A decade of sustained geographic spread of HIV infections among women in Durban, South Africa Ramjee, Gita Sartorius, Benn Morris, Natashia Wand, Handan Reddy, Tarylee Yssel, Justin D. Tanser, Frank BMC Infect Dis Research Article BACKGROUND: Fine scale geospatial analysis of HIV infection patterns can be used to facilitate geographically targeted interventions. Our objective was to use the geospatial technology to map age and time standardized HIV incidence rates over a period of 10 years to identify communities at high risk of HIV in the greater Durban area. METHODS: HIV incidence rates from 7557 South African women enrolled in five community-based HIV prevention trials (2002–2012) were mapped using participant household global positioning system (GPS) coordinates. Age and period standardized HIV incidence rates were calculated for 43 recruitment clusters across greater Durban. Bayesian conditional autoregressive areal spatial regression (CAR) was used to identify significant patterns and clustering of new HIV infections in recruitment communities. RESULTS: The total person-time in the cohort was 9093.93 years and 613 seroconversions were observed. The overall crude HIV incidence rate across all communities was 6·74 per 100PY (95% CI: 6·22–7·30). 95% of the clusters had HIV incidence rates greater than 3 per 100PY. The CAR analysis identified six communities with significantly high HIV incidence. Estimated relative risks for these clusters ranged from 1.34 to 1.70. Consistent with these results, age standardized HIV incidence rates were also highest in these clusters and estimated to be 10 or more per 100 PY. Compared to women 35+ years old younger women were more likely to reside in the highest incidence areas (aOR: 1·51, 95% CI: 1·06–2·15; aOR: 1.59, 95% CI: 1·19–2·14 and aOR: 1·62, 95% CI: 1·2–2·18 for < 20, 20–24, 25–29 years old respectively). Partnership factors (2+ sex partners and being unmarried/not cohabiting) were also more common in the highest incidence clusters (aOR 1.48, 95% CI: 1.25–1.75 and aOR 1.54, 95% CI: 1.28–1.84 respectively). CONCLUSION: Fine geospatial analysis showed a continuous, unrelenting, hyper HIV epidemic in most of the greater Durban region with six communities characterised by particularly high levels of HIV incidence. The results motivate for comprehensive community-based HIV prevention approaches including expanded access to PrEP. In addition, a higher concentration of HIV related services is required in the highest risk communities to effectively reach the most vulnerable populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-4080-6) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-07 /pmc/articles/PMC6555962/ /pubmed/31174475 http://dx.doi.org/10.1186/s12879-019-4080-6 Text en © The Author(s). 2019 Open Access This 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
Ramjee, Gita
Sartorius, Benn
Morris, Natashia
Wand, Handan
Reddy, Tarylee
Yssel, Justin D.
Tanser, Frank
A decade of sustained geographic spread of HIV infections among women in Durban, South Africa
title A decade of sustained geographic spread of HIV infections among women in Durban, South Africa
title_full A decade of sustained geographic spread of HIV infections among women in Durban, South Africa
title_fullStr A decade of sustained geographic spread of HIV infections among women in Durban, South Africa
title_full_unstemmed A decade of sustained geographic spread of HIV infections among women in Durban, South Africa
title_short A decade of sustained geographic spread of HIV infections among women in Durban, South Africa
title_sort decade of sustained geographic spread of hiv infections among women in durban, south africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555962/
https://www.ncbi.nlm.nih.gov/pubmed/31174475
http://dx.doi.org/10.1186/s12879-019-4080-6
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