Evidence map›Paper›PMID 29652100›Full record

ReviewJournal of the International AIDS Society2018

How should HIV resources be allocated? Lessons learnt from applying Optima HIV in 23 countries.

Robyn M Stuart, Laura Grobicki, Hassan Haghparast-Bidgoli, Jasmina Panovska-Griffiths, Jolene Skordis, Olivia Keiser, Janne Estill, Zofia Baranczuk, Sherrie L Kelly, Iyanoosh Reporter and 18 more

Open access · goldAbstract readReview
In one paragraph

Review in Journal of the International AIDS Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
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  7. A qualitative model of the HIV care continuum in Vancouver, Canada.Health systems (Basingstoke, England) · 2022
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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

28 authors at 9 institutions in 5 countries.

Robyn M StuartDepartment of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-5482-9584
Laura GrobickiInstitute for Global Health, University College London, London, UK.
Hassan Haghparast-BidgoliInstitute for Global Health, University College London, London, UK.
Jasmina Panovska-GriffithsClinical Operational Research Unit, Department of Mathematics, University College London, London, UK.
Jolene SkordisInstitute for Global Health, University College London, London, UK.
Olivia KeiserInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Janne EstillInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Zofia BaranczukInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Sherrie L KellyBurnet Institute, Melbourne, VIC, Australia.ORCID 0000-0002-6232-5586
Iyanoosh ReporterBurnet Institute, Melbourne, VIC, Australia.
David J KedzioraBurnet Institute, Melbourne, VIC, Australia.
Andrew J ShattockThe Kirby Institute, UNSW Sydney, Sydney, NSW, Australia.
Janka PetravicBurnet Institute, Melbourne, VIC, Australia.
S Azfar HussainBurnet Institute, Melbourne, VIC, Australia.
Kelsey L GranthamSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Richard T GrayThe Kirby Institute, UNSW Sydney, Sydney, NSW, Australia.
Xiao F YapBurnet Institute, Melbourne, VIC, Australia.
Rowan Martin-HughesBurnet Institute, Melbourne, VIC, Australia.
Clemens J BenediktThe World Bank Group, Washington, DC, USA.
Nicole Fraser-HurtThe World Bank Group, Washington, DC, USA.ORCID 0000-0003-3065-8666
Emiko MasakiThe World Bank Group, Washington, DC, USA.
David J WilsonThe World Bank Group, Washington, DC, USA.
Marelize GorgensThe World Bank Group, Washington, DC, USA.
Elizabeth MzirayThe World Bank Group, Washington, DC, USA.
Nejma CheikhThe World Bank Group, Washington, DC, USA.
Zara ShubberThe World Bank Group, Washington, DC, USA.
Cliff C KerrBurnet Institute, Melbourne, VIC, Australia.ORCID 0000-0003-2517-2354
David P WilsonBurnet Institute, Melbourne, VIC, Australia.
Burnet Institute · AUWorld Bank Group · USUniversity College London · GBUniversity of Geneva · CHThe University of Sydney · AUUNSW Sydney · AULondon School of Hygiene & Tropical Medicine · GBMonash University · AUUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWith limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources.

methodsEach study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required.

conclusionsGreater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

Indexed as

Health ResourcesGlobal HealthHIV InfectionsHumansIncidenceResource Allocationallocative efficiencycost-effectivenessHIV modelingoptimal HIV investmentresource allocationresource needs

Identifiers

PMID29652100
PMCPMC5898225
OpenAlexW2796552832

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.