Evidence map›Paper›PMID 25271808›Full record

ArticlePloS one2014

Optimal allocation of resources in female sex worker targeted HIV prevention interventions: model insights from Avahan in South India.

Jasmina Panovska-Griffiths, Anna Vassall, Holly J Prudden, Aurélia Lépine, Marie-Claude Boily, Sudha Chandrashekar, Kate M Mitchell, Tara S Beattie, Michel Alary, Natasha K Martin and 1 more

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

  1. Trial
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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

11 authors.

Jasmina Panovska-GriffithsSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom; Department of Mathematics, University College London, London, United Kingdom.
Anna VassallSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Holly J PruddenSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Aurélia LépineSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Marie-Claude BoilySchool of Public Health, Imperial College, London, United Kingdom; Centre de recherche du CHU de Québec, Québec, Canada.
Sudha ChandrashekarSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom; St. John's Research Institute, Bangalore, India.
Kate M MitchellSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Tara S BeattieSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Michel AlaryCentre de recherche du CHU de Québec, Québec, Canada; Département de médecine sociale et préventive, Université Laval, Québec, Canada.
Natasha K MartinSchool of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
Peter VickermanSocial and Mathematical Epidemiology Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, United Kingdom; School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.

Funding

Department of Health PDF-2011-04-049Medical Research Council MR/L012057/1
6 · The paper itself

Abstract

backgroundThe Avahan programme has provided HIV prevention activities, including condom promotion, to female sex workers (FSWs) in southern India since 2004. Evidence suggests Avahan averted 202,000 HIV infections over 4 years. For replicating this intervention elsewhere, it is essential to understand how the intervention's impact could have been optimised for different budget levels.

methodsBehavioural data were used to determine how condom use varied for FSWs with different levels of intervention intensity. Cost data from 64 Avahan districts quantified how district-level costs related to intervention scale and intensity. A deterministic model for HIV transmission amongst FSWs and clients projected the impact and cost of intervention strategies for different scale and intensity, and identified the optimal strategies that maximise impact for different budget levels.

resultsAs budget levels increase, the optimal intervention strategy is to first increase intervention intensity which achieves little impact, then scale-up coverage to high levels for large increases in impact, and lastly increase intensity further for small additional gains. The cost-effectiveness of these optimal strategies generally improves with increasing resources, while straying from these strategies can triple costs for the same impact. Projections suggest Avahan was close to being optimal, and moderate budget reductions (≥ 20%) would have reduced impact considerably (>40%). DISCUSSION: Our analysis suggests that tailoring the design of HIV prevention programmes for FSWs can improve impact, and that a certain level of resources are required to achieve demonstrable impact. These insights are critical for optimising the use of limited resources for preventing HIV.

Indexed as

Health ResourcesResource AllocationSex WorkersCost-Benefit AnalysisFemaleHIV InfectionsHumansIndiaMaleModels, TheoreticalPublic Health Surveillance

Identifiers

PMID25271808
PMCPMC4182672

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Registered trials

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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.