ReviewViruses2015
Identifying Recent HIV Infections: From Serological Assays to Genomics.
Review in Viruses, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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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.
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Who cites it
21 citing papers in PubMed.
- 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
- Trial
- Recent HIV infection among women and men enrolling to care in urban clinics in Ethiopia.BMC infectious diseases · 2026Article
- Article
- Prevalence and associated factors of recent HIV-1 infection among newly identified HIV-positive individuals tested with the Asante Rapid Recency assay in Harari region, Eastern Ethiopia.Frontiers in epidemiology · 2025Article
- Use of Next-Generation Sequencing in a State-Wide Strategy of HIV-1 Surveillance: Impact of the SARS-COV-2 Pandemic on HIV-1 Diagnosis and Transmission.The Journal of infectious diseases · 2023Observational
- Article
- Near Real-Time Identification of Recent Human Immunodeficiency Virus Transmissions, Transmitted Drug Resistance Mutations, and Transmission Networks by Multiplexed Primer ID-Next-Generation Sequencing in North Carolina.The Journal of infectious diseases · 2021Article
- Case Report:Frontiers in immunology · 2021Article
- Article
- Recent HIV infection testing algorithms.The Indian journal of medical research · 2020Article
- Discrimination between recent and non-recent HIV infections using routine diagnostic serological assays.Medical microbiology and immunology · 2019Article
- Article
- Detection of IgG3 antibodies specific to the human immunodeficiency virus type 1 (HIV-1) p24 protein as marker for recently acquired infection.Epidemiology and infection · 2018Article
- Observational
- Performance characteristics of an antibody-based multiplex kit for determining recent HIV-1 infection.PloS one · 2017Article
- Short Communication: Low False Recent Rate of Limiting Antigen-Avidity Assay Combined with HIV-1 RNA Data in Botswana.AIDS research and human retroviruses · 2017Article
- Article
- Strengthening HIV surveillance: measurements to track the epidemic in real time.African journal of AIDS research : AJAR · 2016Article
- Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
In this paper, we review serological and molecular based methods to identify HIV infection recency. The accurate identification of recent HIV infection continues to be an important research area and has implications for HIV prevention and treatment interventions. Longitudinal cohorts that follow HIV negative individuals over time are the current gold standard approach, but they are logistically challenging, time consuming and an expensive enterprise. Methods that utilize cross-sectional testing and biomarker information have become an affordable alternative to the longitudinal approach. These methods use well-characterized biological makers to differentiate between recent and established HIV infections. However, recent results have identified a number of limitations in serological based assays that are sensitive to the variability in immune responses modulated by HIV subtypes, viral load and antiretroviral therapy. Molecular methods that explore the dynamics between the timing of infection and viral evolution are now emerging as a promising approach. The combination of serological and molecular methods may provide a good solution to identify recent HIV infection in cross-sectional data. As part of this review, we present the advantages and limitations of serological and molecular based methods and their potential complementary role for the identification of HIV infection recency.
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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.