Cargando…

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

INTRODUCTION: HIV incidence varies widely between sub-Saharan African (SSA) countries. This variation coincides with a substantial sociobehavioural heterogeneity, which complicates the design of effective interventions. In this study, we investigated how sociobehavioural heterogeneity in sub-Saharan...

Descripción completa

Detalles Bibliográficos
Autores principales: Merzouki, Aziza, Estill, Janne, Orel, Erol, Tal, Kali, Keiser, Olivia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
HIV
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812934/
https://www.ncbi.nlm.nih.gov/pubmed/33520455
http://dx.doi.org/10.7717/peerj.10660
_version_ 1783637754383433728
author Merzouki, Aziza
Estill, Janne
Orel, Erol
Tal, Kali
Keiser, Olivia
author_facet Merzouki, Aziza
Estill, Janne
Orel, Erol
Tal, Kali
Keiser, Olivia
author_sort Merzouki, Aziza
collection PubMed
description INTRODUCTION: HIV incidence varies widely between sub-Saharan African (SSA) countries. This variation coincides with a substantial sociobehavioural heterogeneity, which complicates the design of effective interventions. In this study, we investigated how sociobehavioural heterogeneity in sub-Saharan Africa could account for the variance of HIV incidence between countries. METHODS: We analysed aggregated data, at the national-level, from the most recent Demographic and Health Surveys of 29 SSA countries (2010–2017), which included 594,644 persons (183,310 men and 411,334 women). We preselected 48 demographic, socio-economic, behavioural and HIV-related attributes to describe each country. We used Principal Component Analysis to visualize sociobehavioural similarity between countries, and to identify the variables that accounted for most sociobehavioural variance in SSA. We used hierarchical clustering to identify groups of countries with similar sociobehavioural profiles, and we compared the distribution of HIV incidence (estimates from UNAIDS) and sociobehavioural variables within each cluster. RESULTS: The most important characteristics, which explained 69% of sociobehavioural variance across SSA among the variables we assessed were: religion; male circumcision; number of sexual partners; literacy; uptake of HIV testing; women’s empowerment; accepting attitude toward people living with HIV/AIDS; rurality; ART coverage; and, knowledge about AIDS. Our model revealed three groups of countries, each with characteristic sociobehavioural profiles. HIV incidence was mostly similar within each cluster and different between clusters (median (IQR); 0.5/1000 (0.6/1000), 1.8/1000 (1.3/1000) and 5.0/1000 (4.2/1000)). CONCLUSIONS: Our findings suggest that the combination of sociobehavioural factors play a key role in determining the course of the HIV epidemic, and that similar techniques can help to predict the effects of behavioural change on the HIV epidemic and to design targeted interventions to impede HIV transmission in SSA.
format Online
Article
Text
id pubmed-7812934
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher PeerJ Inc.
record_format MEDLINE/PubMed
spelling pubmed-78129342021-01-28 Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence Merzouki, Aziza Estill, Janne Orel, Erol Tal, Kali Keiser, Olivia PeerJ HIV INTRODUCTION: HIV incidence varies widely between sub-Saharan African (SSA) countries. This variation coincides with a substantial sociobehavioural heterogeneity, which complicates the design of effective interventions. In this study, we investigated how sociobehavioural heterogeneity in sub-Saharan Africa could account for the variance of HIV incidence between countries. METHODS: We analysed aggregated data, at the national-level, from the most recent Demographic and Health Surveys of 29 SSA countries (2010–2017), which included 594,644 persons (183,310 men and 411,334 women). We preselected 48 demographic, socio-economic, behavioural and HIV-related attributes to describe each country. We used Principal Component Analysis to visualize sociobehavioural similarity between countries, and to identify the variables that accounted for most sociobehavioural variance in SSA. We used hierarchical clustering to identify groups of countries with similar sociobehavioural profiles, and we compared the distribution of HIV incidence (estimates from UNAIDS) and sociobehavioural variables within each cluster. RESULTS: The most important characteristics, which explained 69% of sociobehavioural variance across SSA among the variables we assessed were: religion; male circumcision; number of sexual partners; literacy; uptake of HIV testing; women’s empowerment; accepting attitude toward people living with HIV/AIDS; rurality; ART coverage; and, knowledge about AIDS. Our model revealed three groups of countries, each with characteristic sociobehavioural profiles. HIV incidence was mostly similar within each cluster and different between clusters (median (IQR); 0.5/1000 (0.6/1000), 1.8/1000 (1.3/1000) and 5.0/1000 (4.2/1000)). CONCLUSIONS: Our findings suggest that the combination of sociobehavioural factors play a key role in determining the course of the HIV epidemic, and that similar techniques can help to predict the effects of behavioural change on the HIV epidemic and to design targeted interventions to impede HIV transmission in SSA. PeerJ Inc. 2021-01-15 /pmc/articles/PMC7812934/ /pubmed/33520455 http://dx.doi.org/10.7717/peerj.10660 Text en ©2021 Merzouki et al. https://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by-nc/4.0) , which permits using, remixing, and building upon the work non-commercially, as long as it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle HIV
Merzouki, Aziza
Estill, Janne
Orel, Erol
Tal, Kali
Keiser, Olivia
Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
title Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
title_full Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
title_fullStr Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
title_full_unstemmed Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
title_short Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
title_sort clusters of sub-saharan african countries based on sociobehavioural characteristics and associated hiv incidence
topic HIV
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7812934/
https://www.ncbi.nlm.nih.gov/pubmed/33520455
http://dx.doi.org/10.7717/peerj.10660
work_keys_str_mv AT merzoukiaziza clustersofsubsaharanafricancountriesbasedonsociobehaviouralcharacteristicsandassociatedhivincidence
AT estilljanne clustersofsubsaharanafricancountriesbasedonsociobehaviouralcharacteristicsandassociatedhivincidence
AT orelerol clustersofsubsaharanafricancountriesbasedonsociobehaviouralcharacteristicsandassociatedhivincidence
AT talkali clustersofsubsaharanafricancountriesbasedonsociobehaviouralcharacteristicsandassociatedhivincidence
AT keiserolivia clustersofsubsaharanafricancountriesbasedonsociobehaviouralcharacteristicsandassociatedhivincidence