ArticleAIDS (London, England)2016
Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning.
Article in AIDS (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Article
- The role of high-risk geographies in the perpetuation of the HIV epidemic in rural South Africa: A spatial molecular epidemiology study.PLOS global public health · 2022Article
- A Comparison of Bayesian Spatial Models for HIV Mapping in South Africa.International journal of environmental research and public health · 2021Article
- Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub-Saharan Africa.Journal of the International AIDS Society · 2021Article
- Geographical Disparities in HIV Seroprevalence Among Men Who Have Sex with Men and People Who Inject Drugs in Nigeria: Exploratory Spatial Data Analysis.JMIR public health and surveillance · 2021Article
- A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa.International journal of environmental research and public health · 2020Article
- Availability, access, analysis and dissemination of small-area data.International journal of epidemiology · 2020Article
- Article
- Updates to the Spectrum/AIM model for estimating key HIV indicators at national and subnational levels.AIDS (London, England) · 2019Review
- Estimating under-five mortality in space and time in a developing world context.Statistical methods in medical research · 2019Article
- Geographic Information Systems, spatial analysis, and HIV in Africa: A scoping review.PloS one · 2019Article
- Impact of a borderless sample transport network for scaling up viral load monitoring: results of a geospatial optimization model for Zambia.Journal of the International AIDS Society · 2018Article
- Capturing the spatial variability of HIV epidemics in South Africa and Tanzania using routine healthcare facility data.International journal of health geographics · 2018Article
- Targeting the right interventions to the right people and places: the role of geospatial analysis in HIV program planning.AIDS (London, England) · 2018Article
- Identifying 'corridors of HIV transmission' in a severely affected rural South African population: a case for a shift toward targeted prevention strategies.International journal of epidemiology · 2018Article
- Appraising the value of evidence generation activities: an HIV modelling study.BMJ global health · 2018Article
- Article
- Mapping the spatial variability of HIV infection in Sub-Saharan Africa: Effective information for localized HIV prevention and control.Scientific reports · 2017Article
- Using geospatial mapping to design HIV elimination strategies for sub-Saharan Africa.Science translational medicine · 2017Article
- Spatial patterns of HIV prevalence and service use in East Zimbabwe: implications for future targeting of interventions.Journal of the International AIDS Society · 2017Article
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Abstract
objectiveThere is evidence of substantial subnational variation in the HIV epidemic. However, robust spatial HIV data are often only available at high levels of geographic aggregation and not at the finer resolution needed for decision making. Therefore, spatial analysis methods that leverage available data to provide local estimates of HIV prevalence may be useful. Such methods exist but have not been formally compared when applied to HIV. DESIGN/
methodsSix candidate methods - including those used by the Joint United Nations Programme on HIV/AIDS to generate maps and a Bayesian geostatistical approach applied to other diseases - were used to generate maps and subnational estimates of HIV prevalence across three countries using cluster level data from household surveys. Two approaches were used to assess the accuracy of predictions: internal validation, whereby a proportion of input data is held back (test dataset) to challenge predictions; and comparison with location-specific data from household surveys in earlier years.
resultsEach of the methods can generate usefully accurate predictions of prevalence at unsampled locations, with the magnitude of the error in predictions similar across approaches. However, the Bayesian geostatistical approach consistently gave marginally the strongest statistical performance across countries and validation procedures.
conclusionsAvailable methods may be able to furnish estimates of HIV prevalence at finer spatial scales than the data currently allow. The subnational variation revealed can be integrated into planning to ensure responsiveness to the spatial features of the epidemic. The Bayesian geostatistical approach is a promising strategy for integrating HIV data to generate robust local estimates.
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