ArticleVox sanguinis2024
The impact of non-disclosure of HIV status and antiretroviral therapy on HIV recency testing and incidence algorithms.
Article in Vox sanguinis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Discordance Between Biomarker-Confirmed Antiretroviral Therapy and Self-Reported HIV Status Among People Living with HIV in Zambia and South Africa: A Secondary Analysis of HPTN 071 (PopART).medRxiv : the preprint server for health sciences · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
BACKGROUND AND
objectivesAccurate HIV incidence estimates among blood donors are necessary to assess the effectiveness of programs aimed at limiting transfusion-transmitted HIV. We assessed the impact of undisclosed HIV status and antiretroviral (ARV) use on HIV recency and incidence estimates using increasingly comprehensive recent infection testing algorithms. MATERIALS AND
methodsUsing 2017 donation data from first-time and lapsed donors, we populated four HIV recency algorithms: (1) serology and limiting-antigen avidity testing, (2) with individual donation nucleic amplification testing (ID-NAT) added to Algorithm 1, (3) with viral load added to Algorithm 2 and (4) with ARV testing added to Algorithm 3. Algorithm-specific mean durations of recent infection (MDRI) and false recency rates (FRR) were calculated and used to derive and compare incidence estimates.
resultsCompared with Algorithm 4, progressive algorithms misclassified fewer donors as recent: Algorithm 1: 61 (12.1%); Algorithm 2: 14 (2.8%) and Algorithm 3: 3 (0.6%). Algorithm-specific MDRI and FRR values resulted in marginally lower incidence estimates: Algorithm 1: 0.19% per annum (p.a.) (95% confidence interval [CI]: 0.13%-0.26%); Algorithm 2: 0.18% p.a. (95% CI: 0.13%-0.22%); Algorithm 3: 0.17% p.a. (95% CI: 0.13%-0.22%) and Algorithm 4: 0.17% p.a. (95% CI: 0.13%-0.21%).
conclusionWe confirmed significant misclassification of recent HIV cases when not including viral load and ARV testing. Context-specific MDRI and FRR resulted in progressively lower incidence estimates but did not fully account for the context-specific variability in incidence modelling. The inclusion of ARV testing, in addition to viral load and ID-NAT testing, did not have a significant impact on incidence estimates.
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