Assessing the spatial nonstationarity in relationship between local patterns of HIV infections and the covariates in South Africa: A geographically weighted regression analysis. (February 2016)

• Record Type: Journal Article
• Authors: Wabiri, Njeri; Shisana, Olive; Zuma, Khangelani; Freeman, Jeffrey
• Is Part Of: Spatial and spatio-temporal epidemiology. Volume 16(2016)
• Page Start: 88
• Page End: 99
• Publication Date: 2016-02
• Subjects: HIV prevalence -- Spatial nonstationarity -- South Africa -- Social covariates -- National household survey -- Geographically weighted regression; Epidemiology -- Statistical methods -- Periodicals; Epidemiology -- Periodicals; 614.4072
• DOI: 10.1016/j.sste.2015.12.003
• Languages: English
• ISSNs: 1877-5845

Abstract

Highlights: Social drivers of HIV vary from district to district. High prevalence districts have high multiple sex partnerships; intergeneration sex. High number of blacks, females, and high levels of singlehood. Intergenerational sex compounds the risk of HIV infection in poor districts. Study provides a basis to focus intervention to areas of need. Abstract: Beyond the structural drivers such as distance from the road, rural/urban divide or demographic profiles, not much is known about the spatial relationship between HIV and social covariates. Spatial relations between social covariates and HIV infection of persons above 15 years were explored and mapped using geographically weighted regression model using data from a national HIV household survey conducted in 2008 and comprising 23 369 individuals from approximately 1000 enumeration areas that were randomly selected from the national census. The maps show spatial non-stationarity in relationship between local patterns of HIV prevalence and the social covariates across South Africa. The high prevalence districts have very homogeneous population defined by the following characteristics: Black origin, unfavorable sex ratio (high proportion of females), low socioeconomic status, being single or low marriage rates, multiple sexual partners and intergenerational sex. Markedly, intergenerational sex compounds the risk of acquiring HIV infection for females in poor districts. Identification of key social drivers of HIV and how they vary from location to location can help to effectively guide and focus intervention programs to areas of particular need.