ArticleJournal of clinical microbiology2014
HIV diversity as a biomarker for HIV incidence estimation: including a high-resolution melting diversity assay in a multiassay algorithm.
Article in Journal of clinical microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 23 citations in OpenAlex.
- Molecular dating and viral load growth rates suggested that the eclipse phase lasted about a week in HIV-1 infected adults in East Africa and Thailand.PLoS pathogens · 2020Trial
- Estimating HIV-1 Viremic Time From Reservoir Sequence Diversity With Uncertainty Quantification.The Journal of infectious diseases · 2026Article
- HIV-phyloTSI: subtype-independent estimation of time since HIV-1 infection for cross-sectional measures of population incidence using deep sequence data.BMC bioinformatics · 2025Article
- Using viral sequence diversity to estimate time of HIV infection in infants.PLoS pathogens · 2023Article
- Multiple Infection and Human Immunodeficiency Virus Superinfection Among Persons who Inject Drugs in Indonesia and Ukraine.The Journal of infectious diseases · 2022Article
- Modeling methods for estimating HIV incidence: a mathematical review.Theoretical biology & medical modelling · 2020Review
- 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
- Estimating time of HIV-1 infection from next-generation sequence diversity.PLoS computational biology · 2017Article
- Observational
- Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana.PloS one · 2016Article
- Review
- A Generalized Entropy Measure of Within-Host Viral Diversity for Identifying Recent HIV-1 Infections.Medicine · 2015Article
- Assessing Biases in the Evaluation of Classification Assays for HIV Infection Recency.PloS one · 2015Article
- How can we better identify early HIV infections?Current opinion in HIV and AIDS · 2015Review
- Assessment of ambiguous base calls in HIV-1 pol population sequences as a biomarker for identification of recent infections in HIV-1 incidence studies.Journal of clinical microbiology · 2014Article
- Incorrect identification of recent HIV infection in adults in the United States using a limiting-antigen avidity assay.AIDS (London, England) · 2014Article
- Dynamics of viremia in primary HIV-1 infection in Africans: insights from analyses of host and viral correlates.Virology · 2014Article
- A comparison of two measures of HIV diversity in multi-assay algorithms for HIV incidence estimation.PloS one · 2014Article
Corrections and comments
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Authors and funding
19 authors at 12 institutions in 1 country.
Funding
Abstract
Multiassay algorithms (MAAs) can be used to estimate cross-sectional HIV incidence. We previously identified a robust MAA that includes the BED capture enzyme immunoassay (BED-CEIA), the Bio-Rad Avidity assay, viral load, and CD4 cell count. In this report, we evaluated MAAs that include a high-resolution melting (HRM) diversity assay that does not require sequencing. HRM scores were determined for eight regions of the HIV genome (2 in gag, 1 in pol, and 5 in env). The MAAs that were evaluated included the BED-CEIA, the Bio-Rad Avidity assay, viral load, and the HRM diversity assay, using HRM scores from different regions and a range of region-specific HRM diversity assay cutoffs. The performance characteristics based on the proportion of samples that were classified as MAA positive by duration of infection were determined for each MAA, including the mean window period. The cross-sectional incidence estimates obtained using optimized MAAs were compared to longitudinal incidence estimates for three cohorts in the United States. The performance of the HRM-based MAA was nearly identical to that of the MAA that included CD4 cell count. The HRM-based MAA had a mean window period of 154 days and provided cross-sectional incidence estimates that were similar to those based on cohort follow-up. HIV diversity is a useful biomarker for estimating HIV incidence. MAAs that include the HRM diversity assay can provide accurate HIV incidence estimates using stored blood plasma or serum samples without a requirement for CD4 cell count data.
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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.