Evidence map›Paper›PMID 23527217›Full record

ArticlePloS one2013

Cost-effectiveness of pre-exposure prophylaxis (PrEP) in preventing HIV-1 infections in rural Zambia: a modeling study.

Brooke E Nichols, Charles A B Boucher, Janneke H van Dijk, Phil E Thuma, Jan L Nouwen, Rob Baltussen, Janneke van de Wijgert, Peter M A Sloot, David A M C van de Vijver

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 5 pooled it
3.0field-weighted citation impact, top 8% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 5 syntheses or guidelines pooled it, 43 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Cost-effectiveness and budget effect of pre-exposure prophylaxis for HIV-1 prevention in Germany from 2018 to 2058.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2019
    Article
  19. Modeling HIV Pre-Exposure Prophylaxis.Frontiers in pharmacology · 2019
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 3 countries.

Brooke E NicholsDepartment of Virology, Erasmus Medical Centre, Rotterdam, The Netherlands. b.nichols@erasmusmc.nl
Charles A B Boucher
Janneke H van Dijk
Phil E Thuma
Jan L Nouwen
Rob Baltussen
Janneke van de Wijgert
Peter M A Sloot
David A M C van de Vijver
Erasmus University Rotterdam · NLGolden Valley Agricultural Research Trust · ZMRadboud University Nijmegen · NLUniversity of Amsterdam · NLUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPre-exposure prophylaxis (PrEP) with tenofovir and emtricitabine effectively prevents new HIV infections. The optimal scenario for implementing PrEP where most infections are averted at the lowest cost is unknown. We determined the impact of different PrEP strategies on averting new infections, prevalence, drug resistance and cost-effectiveness in Macha, a rural setting in Zambia.

methodsA deterministic mathematical model of HIV transmission was constructed using data from the Macha epidemic (antenatal prevalence 7.7%). Antiretroviral therapy is started at CD4<350 cells/mm(3). We compared the number of infections averted, cost-effectiveness, and potential emergence of drug resistance of two ends of the prioritization spectrum: prioritizing PrEP to half of the most sexually active individuals (5-15% of the total population), versus randomly putting 40-60% of the total population on PrEP.

resultsPrioritizing PrEP to individuals with the highest sexual activity resulted in more infections averted than a non-prioritized strategy over ten years (31% and 23% reduction in new infections respectively), and also a lower HIV prevalence after ten years (5.7%, 6.4% respectively). The strategy was very cost-effective at $323 per quality adjusted life year gained and appeared to be both less costly and more effective than the non-prioritized strategy. The prevalence of drug resistance due to PrEP was as high as 11.6% when all assumed breakthrough infections resulted in resistance, and as low as 1.3% when 10% of breakthrough infections resulted in resistance in both our prioritized and non-prioritized scenarios.

conclusionsEven in settings with low test rates and treatment retention, the use of PrEP can still be a useful strategy in averting infections. Our model has shown that PrEP is a cost-effective strategy for reducing HIV incidence, even when adherence is suboptimal and prioritization is imperfect.

Indexed as

HIV-1AdenineAnti-HIV AgentsCost-Benefit AnalysisDeoxycytidineEmtricitabineHIV InfectionsHumansModels, BiologicalOrganophosphonatesPrevalencePrimary PreventionRural PopulationSensitivity and SpecificitySexual BehaviorTenofovirAdenineAnti-HIV AgentsDeoxycytidineEmtricitabineOrganophosphonatesTenofovir

Identifiers

PMID23527217
PMCPMC3601101
OpenAlexW2163912123

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.