Evidence map›Paper›PMID 26230949›Full record

ArticlePloS one2015

A Comparison of South African National HIV Incidence Estimates: A Critical Appraisal of Different Methods.

Thomas Rehle, Leigh Johnson, Timothy Hallett, Mary Mahy, Andrea Kim, Helen Odido, Dorina Onoya, Sean Jooste, Olive Shisana, Adrian Puren and 2 more

Abstract readComparative Study
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

49 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  5. Observational
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  10. Review
  11. The HIV Epidemic in South Africa: Key Findings from 2017 National Population-Based Survey.International journal of environmental research and public health · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Modeling methods for estimating HIV incidence: a mathematical review.Theoretical biology & medical modelling · 2020
    Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Thomas RehleHuman Sciences Research Council, Cape Town, South Africa; Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa.
Leigh JohnsonCentre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa.
Timothy HallettDepartment of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom.
Mary MahyUNAIDS, Geneva, Switzerland.
Andrea KimCenters for Disease Control and Prevention, Center for Global Health, Division of Global HIV/AIDS, Atlanta, GA, United States of America.
Helen OdidoUNAIDS, Pretoria, South Africa.
Dorina OnoyaHuman Sciences Research Council, Cape Town, South Africa.
Sean JoosteHuman Sciences Research Council, Cape Town, South Africa.
Olive ShisanaHuman Sciences Research Council, Cape Town, South Africa; Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa.
Adrian PurenNational Institute for Communicable Diseases, Johannesburg, South Africa.
Bharat ParekhCenters for Disease Control and Prevention, Center for Global Health, Division of Global HIV/AIDS, Atlanta, GA, United States of America.
John StoverFutures Institute, Glastonbury, CT, United States of America.

Funding

CGH CDC HHS U2G GH000357Medical Research Council MR/K010174/1NCHHSTP CDC HHS U2G PS000570NCHHSTP CDC HHS U2G PS001328PEPFARPHS HHS 3U2GGH00357-02PHS HHS 5U2GPS000570-05PHS HHS U2GPS001328
6 · The paper itself

Abstract

backgroundThe interpretation of HIV prevalence trends is increasingly difficult as antiretroviral treatment programs expand. Reliable HIV incidence estimates are critical to monitoring transmission trends and guiding an effective national response to the epidemic. METHODS AND

findingsWe used a range of methods to estimate HIV incidence in South Africa: (i) an incidence testing algorithm applying the Limiting-Antigen Avidity Assay (LAg-Avidity EIA) in combination with antiretroviral drug and HIV viral load testing; (ii) a modelling technique based on the synthetic cohort principle; and (iii) two dynamic mathematical models, the EPP/Spectrum model package and the Thembisa model. Overall, the different incidence estimation methods were in broad agreement on HIV incidence estimates among persons aged 15-49 years in 2012. The assay-based method produced slightly higher estimates of incidence, 1.72% (95% CI 1.38 - 2.06), compared with the mathematical models, 1.47% (95% CI 1.23 - 1.72) in Thembisa and 1.52% (95% CI 1.43 - 1.62) in EPP/Spectrum, and slightly lower estimates of incidence compared to the synthetic cohort, 1.9% (95% CI 0.8 - 3.1) over the period from 2008 to 2012. Among youth aged 15-24 years, a declining trend in HIV incidence was estimated by all three mathematical estimation methods.

conclusionsThe multi-method comparison showed similar levels and trends in HIV incidence and validated the estimates provided by the assay-based incidence testing algorithm. Our results confirm that South Africa is the country with the largest number of new HIV infections in the world, with about 1 000 new infections occurring each day among adults aged 15-49 years in 2012.

Indexed as

AdolescentAdultAlgorithmsFemaleHIV InfectionsHumansIncidenceMaleMiddle AgedModels, TheoreticalSouth AfricaYoung Adult

Identifiers

PMID26230949
PMCPMC4521952

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