Temporal and spatial monitoring of HIV prevalence and incidence rates using geospatial models: Results from South African women. (June 2021)

• Record Type: Journal Article
• Authors: Wand, Handan; Morris, Natashia; Reddy, Tarylee
• Is Part Of: Spatial and spatio-temporal epidemiology. Volume 37(2021)
• Publication Date: 2021-06
• Subjects: Generalized additive models -- Non-linear association -- HIV prevalence and incidence; Epidemiology -- Statistical methods -- Periodicals; Epidemiology -- Periodicals; 614.4072
• DOI: 10.1016/j.sste.2021.100413
• Languages: English
• ISSNs: 1877-5845

Abstract

Highlights: The generalized additive models (GAMs) revealed substantial temporal and geographical diversities in HIV prevalence(2002–2017) and incidence rates(2002–2016) among South African women. This quantitative evidence was further supported by continuous-scale intensity maps which revealed a non-linear associations between the geographical-level data and infections . Our findings provided strong empirical and visual evidence for the changing face of the epidemic in South Africa using geospatial methods. Abstract: Generalized additive models (GAMs) were used to predict non-linear distributions of HIV prevalence and incidence based on semiparametric methods. The GAMs also provide smooth intensity maps by projecting the predicted HIV prevalence (or incidence) into the contour maps. Two sets of geo-coded data sources were used: (1) population-based cross-sectional data from 10, 928 women who participated in four HIV behavioral surveys (2002–2017), (2) clinic-based longitudinal data from 7, 557 women who resided in KwaZulu-Natal (2002–2016). Model estimated degrees of freedoms were 15.84, 12.17, 7.64 and 15.08 (2002-2012), indicating substantial spatial variations in HIV prevalence overtime. At localized-level these HIV incidence ranged from 15 to 18 per 100 person-year and scattered across the relatively homogeneous area within less than 100 km radius. These significant quantitative evidence were further supported by continuous-scale intensity maps. Our findings provided empirical and visual evidence for the changing face of the epidemic in South Africa using geospatial methods.