ArticleJournal of acquired immune deficiency syndromes (1999)2013
Cross-sectional HIV incidence estimation in HIV prevention research.
Article in Journal of acquired immune deficiency syndromes (1999), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
What it found
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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.
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.
Who cites it
39 citing papers in PubMed, 47 citations in OpenAlex.
- Evaluation of multi-assay algorithms for identifying individuals with recent HIV infection: HPTN 071 (PopART).PloS one · 2021Trial
- Cross-sectional estimates revealed high HIV incidence in Botswana rural communities in the era of successful ART scale-up in 2013-2015.PloS one · 2018Trial
- Brief Report: Impact of Early Antiretroviral Therapy on the Performance of HIV Rapid Tests and HIV Incidence Assays.Journal of acquired immune deficiency syndromes (1999) · 2017Trial
- Characterization of HIV Seroconverters in a TDF/FTC PrEP Study: HPTN 067/ADAPT.Journal of acquired immune deficiency syndromes (1999) · 2017Trial
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- Study design approaches for future active-controlled HIV prevention trials.Statistical communications in infectious diseases · 2024Article
- Evaluation of multi-assay algorithms for cross-sectional HIV incidence estimation in settings with universal antiretroviral treatment.BMC infectious diseases · 2022Article
- Building an integrated serosurveillance platform to inform public health interventions: Insights from an experts' meeting on serum biomarkers.PLoS neglected tropical diseases · 2022Article
- A top scoring pairs classifier for recent HIV infections.Statistics in medicine · 2021Article
- Antibody avidity-based approach to estimate population-level incidence of hepatitis C.Journal of hepatology · 2020Article
- Modeling methods for estimating HIV incidence: a mathematical review.Theoretical biology & medical modelling · 2020Review
- Cross-sectional human immunodeficiency virus incidence estimation accounting for heterogeneity across communities.Biometrics · 2019Article
- Comprehensive Profiling of HIV Antibody Evolution.Cell reports · 2019Article
- Development of a Multiplex Assay for Concurrent Diagnoses and Detection of HIV-1, HIV-2, and Recent HIV-1 Infection in a Single Test.AIDS research and human retroviruses · 2018Article
- Cross-Sectional HIV Incidence Estimation with Missing Biomarkers.Statistical communications in infectious diseases · 2018Article
- A comparison of two biological markers of recent hepatitis C virus (HCV) infection: implications for the monitoring of interventions and strategies to reduce HCV transmission among people who inject drugs.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2018Article
- HIV-1 Transmissions Among Recently Infected Individuals in Southwest China are Predominantly Derived from Circulating Local Strains.Scientific reports · 2018Article
- Identification and validation of a multi-assay algorithm for cross-sectional HIV incidence estimation in populations with subtype C infection.Journal of the International AIDS Society · 2018Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 1 country.
Funding
Abstract
Accurate methods for estimating HIV incidence from cross-sectional samples would have great utility in prevention research. This report describes recent improvements in cross-sectional methods that significantly improve their accuracy. These improvements are based on the use of multiple biomarkers to identify recent HIV infections. These multiassay algorithms (MAAs) use assays in a hierarchical approach for testing that minimizes the effort and cost of incidence estimation. These MAAs do not require mathematical adjustments for accurate estimation of the incidence rates in study populations in the year before sample collection. MAAs provide a practical, accurate, and cost-effective approach for cross-sectional HIV incidence estimation that can be used for HIV prevention research and global epidemic monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.