ArticleJournal of acquired immune deficiency syndromes (1999)2026
Validating HIV Viral Suppression Threshold Adjustments for Comparable Estimates Using Data From Nationally Representative Household Surveys in Sub-Saharan Africa.
Article in Journal of acquired immune deficiency syndromes (1999), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
introductionTo enable comparable global assessments of viral load suppression (VLS) among people living with HIV on antiretroviral therapy, the Joint United Nations Programme on HIV/AIDS applies a model to adjust VLS estimates reported at different thresholds to a common viral load ≤1000 copies/mL definition. We assessed performance of the current reverse Weibull model and alternatives using survey data from sub-Saharan Africa.
methodsUsing data from 21 Population-based HIV Impact Assessment surveys in 16 sub-Saharan African countries (2015-2022), we assessed 6 models (Weibull, reverse Weibull, Pareto, Fréchet, gamma, and lognormal) in adjusting VLS reported at viral load <50, <200, <400 copies/mL to ≤1000. We compared predictions using parameters from Johnson et al and recalibrated using Population-based HIV Impact Assessment surveys, assessing whether new shape parameters improved adjustments and varied by sex and age.
resultsIn adjustments from all thresholds, the Weibull model had the lowest prediction errors (root-mean-squared error for <200 to ≤1000: Weibull: 1.9%; reverse Weibull: 3.1%; Pareto: 2.5%). Prediction errors for reverse Weibull and Pareto models were higher in subgroups with low VLS compared with Weibull. Across 21 surveys, in adjustments from <200 to ≤1000, reverse Weibull overestimated VLS by 2.3%, compared with 1.5% by Weibull and Pareto. The Fréchet, gamma, and lognormal models performed similarly to Weibull. Shape parameter estimates for the Weibull and reverse Weibull were slightly higher after recalibration and varied by sex and age.
conclusionsThe Weibull, Fréchet, gamma, and lognormal models provided more reliable VLS adjustments across thresholds than the previously recommended reverse Weibull model, avoiding inflated VLS estimates that could obscure gaps in HIV treatment programs and underestimate HIV transmission risks.
Indexed as
Identifiers
What OpenQuestion holds
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.