Evidence map›Paper›PMID 22802729›Full record

ArticlePLoS medicine2012

HIV treatment as prevention: principles of good HIV epidemiology modelling for public health decision-making in all modes of prevention and evaluation.

Wim Delva, David P Wilson, Laith Abu-Raddad, Marelize Gorgens, David Wilson, Timothy B Hallett, Alex Welte

Abstract read
In one paragraph

Article in PLoS medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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  8. Article
  9. Article
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  11. Review
  12. Article
  13. Article
  14. PrEP Implementation Science: State-of-the-Art and Research Agenda.Journal of the International AIDS Society · 2015
    Article
  15. Article
  16. Review
  17. Review
  18. Future of phylogeny in HIV prevention.Journal of acquired immune deficiency syndromes (1999) · 2013
    Article
  19. Test-and-treat in Los Angeles: a mathematical model of the effects of test-and-treat for the population of men who have sex with men in Los Angeles County.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2013
    Article
  20. Review
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

7 authors.

Wim DelvaSouth African Department of Science and Technology/National Research Foundation Centre for Excellence in Epidemiological Modelling and Analysis, University of Stellenbosch, Stellenbosch, South Africa.
David P Wilson
Laith Abu-Raddad
Marelize Gorgens
David Wilson
Timothy B Hallett
Alex Welte

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Public health responses to HIV epidemics have long relied on epidemiological modelling analyses to help prospectively project and retrospectively estimate the impact, cost-effectiveness, affordability, and investment returns of interventions, and to help plan the design of evaluations. But translating model output into policy decisions and implementation on the ground is challenged by the differences in background and expectations of modellers and decision-makers. As part of the PLoS Medicine Collection "Investigating the Impact of Treatment on New HIV Infections"--which focuses on the contribution of modelling to current issues in HIV prevention--we present here principles of "best practice" for the construction, reporting, and interpretation of HIV epidemiological models for public health decision-making on all aspects of HIV. Aimed at both those who conduct modelling research and those who use modelling results, we hope that the principles described here will become a shared resource that facilitates constructive discussions about the policy implications that emerge from HIV epidemiology modelling results, and that promotes joint understanding between modellers and decision-makers about when modelling is useful as a tool in quantifying HIV epidemiological outcomes and improving prevention programming.

Indexed as

Decision MakingEvaluation Studies as TopicModels, BiologicalPublic HealthHIVHIV InfectionsHumansUncertainty

Identifiers

PMID22802729
PMCPMC3393657

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.