ArticleThe Journal of infectious diseases2022
Human Immunodeficiency Virus (HIV) Genetic Diversity Informs Stage of HIV-1 Infection Among Patients Receiving Antiretroviral Therapy in Botswana.
Article in The Journal of infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Machine Learning in HIV Care and Antiretroviral Therapy: Systematic Review.Journal of medical Internet research · 2026Pooled it
- 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
- Evidence from HIV sequencing for blood-borne transmission in Africa.Journal of public health in Africa · 2025Review
- Natural Killer Cells Regulate Acute SIV Replication, Dissemination, and Inflammation, but Do Not Impact Independent Transmission Events.Journal of virology · 2023Article
- Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana.BMC infectious diseases · 2022Article
- Article
- Plasma Viral Load of 200 Copies/mL is a Suitable Threshold to Define Viral Suppression and HIV Drug Resistance Testing in Low- and Middle-Income Countries: Evidence From a Facility-Based Study in Cameroon.Journal of the International Association of Providers of AIDS CareArticle
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 3 countries.
Funding
Abstract
backgroundHuman immunodeficiency virus (HIV)-1 genetic diversity increases during infection and can help infer the time elapsed since infection. However, the effect of antiretroviral treatment (ART) on the inference remains unknown.
methodsParticipants with estimated duration of HIV-1 infection based on repeated testing were sourced from cohorts in Botswana (n = 1944). Full-length HIV genome sequencing was performed from proviral deoxyribonucleic acid. We optimized a machine learning model to classify infections as < or >1 year based on viral genetic diversity, demographic, and clinical data.
resultsThe best predictive model included variables for genetic diversity of HIV-1 gag, pol, and env, viral load, age, sex, and ART status. Most participants were on ART. Balanced accuracy was 90.6% (95% confidence interval, 86.7%-94.1%). We tested the algorithm among newly diagnosed participants with or without documented negative HIV tests. Among those without records, those who self-reported a negative HIV test within <1 year were more frequently classified as recent than those who reported a test >1 year previously. There was no difference in classification between those self-reporting a negative HIV test <1 year, whether or not they had a record.
conclusionsThese results indicate that recency of HIV-1 infection can be inferred from viral sequence diversity even among patients on suppressive ART.
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Registered trials
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