ArticleGeospatial health2022
Assessing spatial patterns of HIV prevalence and interventions in semi-urban settings in South Africa. Implications for spatially targeted interventions.
Article in Geospatial health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Geostatistical point process modelling of HIV prevalence using disease progression and CD4 cell count dynamics.iScience · 2026Article
- Article
- Spatial modeling of HIV prevalence in Malawi using generalized additive models.Frontiers in epidemiology · 2026Article
- Trends and spatial patterns of human immunodeficiency virus prevalence among men and women aged 15-49 in Sierra Leone: evidence from the 2008, 2013 and 2019 Demographic and Health Surveys.BMJ global health · 2025Article
- A surge in female condom distribution during the COVID-19 pandemic in Gauteng province, South Africa.Contraception and reproductive medicine · 2025Article
- Spatial analysis and associated risk factors of HIV prevalence in Botswana: insights from the 2021 Botswana AIDS Impact Survey (BAIS V).BMC infectious diseases · 2025Article
- Syndemic mapping of HIV and other STIs in KwaZulu-Natal: a Bayesian spatio-temporal modeling approach using latent constructs.Frontiers in public health · 2025Article
- Spatial mapping and predictors of ever-tested for HIV in adolescent girls and young women in Ethiopia.Frontiers in public health · 2024Article
- Exploring Determinants of HIV/AIDS Self-Testing Uptake in South Africa Using Generalised Linear Poisson and Geographically Weighted Poisson Regression.Healthcare (Basel, Switzerland) · 2023Article
- Spatial disparities of HIV prevalence in South Africa. Do sociodemographic, behavioral, and biological factors explain this spatial variability?Frontiers in public health · 2022Article
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6 authors.
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Abstract
Equitable allocation of resources targeting the human immunodeficiency virus (HIV) at the local level requires focusing interventions in areas of the greatest need. Understanding the geographical variation in the HIV epidemic and uptake of selected HIV prevention and treatment programmes are necessary to identify such areas. Individual-level HIV data were obtained from a 2012 national HIV survey in South Africa. Spatial regression models on each outcome measure (HIV infection, sub-optimal condom use or non-anti-retroviral treatment (ART) adjusted for spatial random effects at the ward level were fitted using WINBUGS software. In addition, ward-level data was utilized to estimate condom use coverage and ART initiation rates which were obtained from routinely collected data in 2012. Ordinary Kriging was used to produce smoothed maps of HIV infection, condom use coverage and ART initiation rates. HIV infection was associated with individuals undertaking tertiary education [posterior odds ratio (POR): 19.53; 95% credible intervals (CrI): 3.22- 84.93]. Sub-optimal condom use increased with age (POR: 1.09; 95%CrI: 1.06-1.11) and was associated with being married (POR: 4.14; 95%CrI: 1.23-4.28). Non-ART use was associated with being married (POR: 6.79; 95%CrI: 1.43-22.43). There were clusters with high HIV infection, sub-optimal condom use, and non- ART use in Ekurhuleni, an urban and semi-urban district in Gauteng province, South Africa. Findings show the need for expanding condom programmes and/or strengthening other HIV prevention programmes such as pre-exposure prophylaxis and encouraging sustained engagement in HIV care and treatment in the identified areas with the greatest need in Ekurhuleni Metropolitan Municipality.
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