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

Aziza Merzouki, Janne Estill, Erol Orel, Kali Tal, Olivia Keiser
doi: https://doi.org/10.1101/620450
Aziza Merzouki
aInstitute of Global Health, University of Geneva, Geneva, Switzerland
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  • For correspondence: fatmaaziza.merzouki@unige.ch
Janne Estill
aInstitute of Global Health, University of Geneva, Geneva, Switzerland
bInstitute of Mathematical Statistics and Actuarial Science, University of Bern, Bern, Switzerland
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Erol Orel
aInstitute of Global Health, University of Geneva, Geneva, Switzerland
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Kali Tal
cInstitute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
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Olivia Keiser
aInstitute of Global Health, University of Geneva, Geneva, Switzerland
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Abstract

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)).

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Conflicts of interest and source of funding: Authors declare no competing interest. This study was funded by the Swiss National Science Foundation (SNF professorship grant n° 163878 to O Keiser).

  • Revised main text and figures (after peer-review), accepted version by PeerJ

  • https://gitlab.com/AzizaM/dhs_ssa_countries_clustering

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 18, 2020.
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Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
Aziza Merzouki, Janne Estill, Erol Orel, Kali Tal, Olivia Keiser
bioRxiv 620450; doi: https://doi.org/10.1101/620450
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Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
Aziza Merzouki, Janne Estill, Erol Orel, Kali Tal, Olivia Keiser
bioRxiv 620450; doi: https://doi.org/10.1101/620450

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