PT  - JOURNAL ARTICLE
AU  - Aziza Merzouki
AU  - Janne Estill
AU  - Erol Orel
AU  - Kali Tal
AU  - Olivia Keiser
TI  - Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence
AID  - 10.1101/620450
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 620450
4099  - http://biorxiv.org/content/early/2020/12/18/620450.short
4100  - http://biorxiv.org/content/early/2020/12/18/620450.full
AB  - 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 StatementThe authors have declared no competing interest.