ArticleJournal of the International AIDS Society2025
Cost and effectiveness of differentiated ART service delivery strategies in Zambia: a modelling analysis using routine data.
Article in Journal of the International AIDS Society, 2025. 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
14 authors.
Funding
Abstract
introductionDifferentiated service delivery (DSD) models for antiretroviral treatment (ART) have been scaled up in many settings in sub-Saharan Africa to improve client-centred care and increase service delivery efficiency. However, given the multitude of models of care currently available, identifying cost-effective combinations of DSD models that maximize benefits and minimize costs remains critical for guiding their expansion.
methodsWe developed an Excel-based mathematical model using retrospective retention and viral suppression data from a national cohort of ART clients (≥15 years) in Zambia between January 2018 and March 2022 stratified by age, sex, setting (urban/rural) and model of ART delivery. Outcomes (viral suppression and retention in care), provider costs and costs to clients were estimated from the cohort and published data. The base case reflects the outcomes observed in 2022 for all DSD models for each population sub-group. For different combinations of nine DSD models and over 1-year time horizon from the provider perspective, we evaluated the incremental cost-effectiveness ratio (ICER) per additional client virally suppressed compared to the 2022 base case. Deterministic sensitivity analyses were conducted on key input parameters.
resultsAmong 125 scenarios evaluated, six were on the cost-effectiveness frontier: (1) 6-month dispensing (6MMD)-only; (2) 6MMD and adherence groups (AGs); (3) AGs-only; (4) fast track refills (FTRs) and AGs; (5) FTRs-only; and 6) AGs and home ART delivery. 6MMD-only was cost-saving compared to the base case, increasing retention by 1.2% (95% CI: 0.7-1.8), viral suppression by 1.6% (95% CI: 1.0-2.7) and reducing client costs by 12.0% (95% CI: 10.8-12.4). The next cost-effective scenarios, 6MMD + AGs and AGs-only, cost $245 per additional person virally suppressed, increased viral suppression by 2.8% (95% CI: 2.2-3.3) and 4.0% (95% CI: 3.5-4.0) and increased client costs by 20.1% (95% CI: 9.5-28.1) and 52.3% (95% CI: 29.868.7), respectively. ART cost and laboratory test costs were the most influential parameters on provider costs and the ICERs.
conclusionsMathematical modelling using existing data can identify cost-effective DSD model mixes while ensuring all client sub-populations are considered. In Zambia, scaling up 6MMD to all eligible clients is likely cost-saving, with further health gains achievable by targeting sub-populations with selected DSD models.
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.