ArticlePloS one2013
How much demand for New HIV prevention technologies can we really expect? Results from a discrete choice experiment in South Africa.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06803316 (Optimizing Care Delivery to Support Reengagement in PLWH Returning to HIV Care After Treatment Lapses in Zambia), which is not on this map. Cited by 44 papers, 3 of them syntheses that pooled it.
What it found
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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.
Optimizing Care Delivery to Support Reengagement in PLWH Returning to HIV Care After Treatment Lapses in Zambia
Who cites it
44 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Pooled it
- Discrete Choice Experiments in Health Economics: Past, Present and Future.PharmacoEconomics · 2019Pooled it
- How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of external validity.The European journal of health economics : HEPAC : health economics in prevention and care · 2018Pooled it
- Uptake of a patient-centred dynamic choice model for HIV prevention in rural Kenya and Uganda: SEARCH SAPPHIRE study.Journal of the International AIDS Society · 2023Trial
- Acceptability of multiple modalities of pre-exposure prophylaxis (PrEP) among female sex workers in Tanzania: a mixed-methods study.BMJ open · 2022Trial
- Efficacy is Not Everything: Eliciting Women's Preferences for a Vaginal HIV Prevention Product Using a Discrete-Choice Experiment.AIDS and behavior · 2020Trial
- Young Women's Stated Preferences for Biomedical HIV Prevention: Results of a Discrete Choice Experiment in Kenya and South Africa.Journal of acquired immune deficiency syndromes (1999) · 2019Trial
- The Tablets, Ring, Injections as Options (TRIO) study: what young African women chose and used for future HIV and pregnancy prevention.Journal of the International AIDS Society · 2018Trial
- Why Engage Communities in Biomedical Research?Bioethics · 2026Article
- A Break from the Norm? Parametric Representations of Preference Heterogeneity for Discrete Choice Models in Health.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Article
- Article
- An Overview of Data Collection in Health Preference Research.The patient · 2025Review
- Identifying preferred program delivery attributes for long-acting injectable cabotegravir-rilpvirine in three U.S. HIV clinics: A discrete choice experiment.Journal of acquired immune deficiency syndromes (1999) · 2025Article
- Health Economics Research on Non-surgical Biomedical HIV Prevention: Identifying Gaps and Proposing a Way Forward.PharmacoEconomics · 2023Article
- Optimizing the pipeline of multipurpose prevention technologies: opportunities across women's reproductive lifespans.Frontiers in reproductive health · 2023Review
- Cost-effectiveness of the dual prevention pill for contraception and HIV pre-exposure prophylaxis.Frontiers in reproductive health · 2023Article
- Article
- Synthesis of end-user research to inform future multipurpose prevention technologies in sub-Saharan Africa: a scoping review.Frontiers in reproductive health · 2023Article
- Making the Case for Joint Decision-Making in Future Multipurpose Prevention Technology (MPT) Choice: Qualitative Findings on MPT Attribute Preferences from the CUPID Study (MTN-045).Journal of the International AIDS Society · 2022Article
- Preferences regarding emerging HIV prevention technologies among Toronto men who have sex with men: a discrete choice experiment.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundFor the first time in the history of HIV, new bio-medical interventions have been shown to be effective in preventing HIV transmission. For these new HIV prevention technologies (NPTs) to have an impact on the epidemic, they must be widely used. This study uses a discrete choice experiment (DCE) to: understand the relative strength of women's preferences for product characteristics, understand the implications for substitution away from male condoms, and inform realistic modelling of their potential impact and cost-effectiveness.
methodsA DCE was conducted among 1017 women in urban South Africa. Women were presented with choices between potential women's NPTs (microbicides, diaphragm, female condom) and 'what I did last time' (use or not use a condom) with different HIV and pregnancy prevention effectiveness' and prices. Choice probabilities are estimated using the nested logit model and used to predict uptake.
resultsIn this high HIV prevalence setting, HIV prevention effectiveness is the main driver of uptake followed by pregnancy prevention effectiveness. For example a microbicide with poor effectiveness would have niche appeal at just 11% predicted uptake, while a highly effective microbicide (95% effective against HIV and pregnancy) would have far wider appeal (56% predicted uptake). Though women who reported not using condoms were more likely to choose the NPTs, at current very high rates of male condom use in South Africa (60%), about half of microbicide uptake is projected to be among those currently not using condoms.
conclusionsWomen are very interested in NPTs, especially if highly effective in preventing HIV and pregnancy. Women in greatest need were also most likely to switch to the new products. Where products are not yet available for distribution, proxy data, such as that generated by DCEs, can bring realism to overly optimistic uptake scenarios found in many current impact models.
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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.