Beyond HIV prevalence: identifying people living with HIV within underserved areas in South Africa.


Journal

BMJ global health
ISSN: 2059-7908
Titre abrégé: BMJ Glob Health
Pays: England
ID NLM: 101685275

Informations de publication

Date de publication:
04 2021
Historique:
received: 30 09 2020
revised: 10 03 2021
accepted: 12 03 2021
entrez: 22 4 2021
pubmed: 23 4 2021
medline: 25 6 2021
Statut: ppublish

Résumé

Despite progress towards the Joint United Nations Programme on HIV/AIDS 95-95-95 targets, South Africa is still suffering from one of the largest HIV epidemics globally. In this study, we generated high-resolution HIV prevalence maps and identified people living with HIV (PLHIV) in underserved areas to provide essential information for the optimal allocation of HIV-related services. The data come from the South Africa Demographic and Health Survey conducted in 2016 and spatial variables from other published literature. We produced high-resolution maps of HIV prevalence and underserved areas, defined as a greater than 30 min travel time to the nearest healthcare facility. Using these maps and the population density, we mapped PLHIV and the PLHIV within underserved areas for 30, 60 and 120 min thresholds. There was substantial geographic variation in HIV prevalence, ranging from 1.4% to 24.2%, with a median of 11.5% for men, and from 2.1% to 48.1%, with a median of 20.6% for women. Gauteng province showed the highest density for both HIV prevalence and PLHIV. 80% of all areas in the country were identified as underserved areas (30 min threshold), which contained more than 16% and 20% of the total men and women living with HIV, respectively. KwaZulu-Natal province had the largest number of PLHIV in underserved areas (30 min threshold) and showed less than one healthcare facility per 1000 PLHIV. Our study showed extensive spatial variation of HIV prevalence and significant numbers of PLHIV in underserved areas in South Africa. Moreover, we identified locations where HIV-related services need to be intensified to reach the ~1.5 million PLHIV in underserved areas, particularly in KwaZulu-Natal province, with less than one healthcare facility per 1000 PLHIV.

Identifiants

pubmed: 33883186
pii: bmjgh-2020-004089
doi: 10.1136/bmjgh-2020-004089
pmc: PMC8061852
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Medical Research Council
ID : MR/T029803/1
Pays : United Kingdom
Organisme : NIAID NIH HHS
ID : R01 AI124389
Pays : United States
Organisme : NICHD NIH HHS
ID : R01 HD084233
Pays : United States

Informations de copyright

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Hana Kim (H)

Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, Ohio, USA.
Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, Ohio, USA.

Frank Tanser (F)

Lincoln International Institute for Rural Health, University of Lincoln, Lincoln, UK.
Africa Health Research Institute, KwaZulu-Natal, South Africa.
School of Nursing and Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.
Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK.

Andrew Tomita (A)

Centre for Rural Health, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa.
KwaZulu-Natal Research Innovation and Sequencing Platform, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.

Alain Vandormael (A)

Heidelberg Institute of Global Health (HIGH), Medical Faculty, Heidelberg University, Heidelberg, Germany.

Diego F Cuadros (DF)

Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, Ohio, USA diego.cuadros@uc.edu.
Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, Ohio, USA.

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