Journal article
Capturing the spatial variability of HIV epidemics in South Africa and Tanzania using routine healthcare facility data
- Abstract:
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Background
Large geographical variations in the intensity of the HIV epidemic in sub-Saharan Africa call for geographically targeted resource allocation where burdens are greatest. However, data available for mapping the geographic variability of HIV prevalence and detecting HIV ‘hotspots’ is scarce, and population-based surveillance data are not always available. Here, we evaluated the viability of using clinic-based HIV prevalence data to measure the spatial variability of HIV in South Africa and Tanzania.
Methods
Population-based and clinic-based HIV data from a small HIV hyper-endemic rural community in South Africa as well as for the country of Tanzania were used to map smoothed HIV prevalence using kernel interpolation techniques. Spatial variables were included in clinic-based models using co-kriging methods to assess whether cofactors improve clinic-based spatial HIV prevalence predictions. Clinic- and population-based smoothed prevalence maps were compared using partial rank correlation coefficients and residual local indicators of spatial autocorrelation.
Results
Routinely-collected clinic-based data captured most of the geographical heterogeneity described by population-based data but failed to detect some pockets of high prevalence. Analyses indicated that clinic-based data could accurately predict the spatial location of so-called HIV ‘hotspots’ in > 50% of the high HIV burden areas.
Conclusion
Clinic-based data can be used to accurately map the broad spatial structure of HIV prevalence and to identify most of the areas where the burden of the infection is concentrated (HIV ‘hotspots’). Where population-based data are not available, HIV data collected from health facilities may provide a second-best option to generate valid spatial prevalence estimates for geographical targeting and resource allocation.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, 2.2MB, Terms of use)
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- Publisher copy:
- 10.1186/s12942-018-0146-8
Authors
- Publisher:
- BioMed Central
- Journal:
- International Journal of Health Geographics More from this journal
- Volume:
- 17
- Issue:
- 1
- Article number:
- 27
- Publication date:
- 2018-07-11
- Acceptance date:
- 2018-07-02
- DOI:
- EISSN:
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1476-072X
- Pmid:
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29996876
- Language:
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English
- Keywords:
- Pubs id:
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1160746
- Local pid:
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pubs:1160746
- Deposit date:
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2021-02-10
Terms of use
- Copyright holder:
- Cuadros et al.
- Copyright date:
- 2018
- Rights statement:
- ©2018 The Authors. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Licence:
- CC Attribution (CC BY)
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