ArticlePloS one2014
A comparison of two measures of HIV diversity in multi-assay algorithms for HIV incidence estimation.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.
- Use of HIV Recency Assays for HIV Incidence Estimation and Other Surveillance Use Cases: Systematic Review.JMIR public health and surveillance · 2022Pooled it
- Development of a multiassay algorithm (MAA) to identify recent HIV infection in newly diagnosed individuals in Indonesia.iScience · 2023Article
- A systematic review of limiting antigen avidity enzyme immunoassay for detection of recent HIV-1 infection to expand supported applications.Journal of virus eradication · 2022Review
- Diagnosis of Human Immunodeficiency Virus Infection.Clinical microbiology reviews · 2019Review
- Decision tree for accurate infection timing in individuals newly diagnosed with HIV-1 infection.BMC infectious diseases · 2017Article
- Observational
- Performance characteristics of an antibody-based multiplex kit for determining recent HIV-1 infection.PloS one · 2017Article
- Viral and Host Characteristics of Recent and Established HIV-1 Infections in Kisumu based on a Multiassay Approach.Scientific reports · 2016Observational
- Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana.PloS one · 2016Article
- Review
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Authors and funding
22 authors at 12 institutions in 1 country.
Funding
Abstract
backgroundMulti-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence.
methodsBoth MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies.
resultsThe proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion.
conclusionsMAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation.
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