Evidence map›Paper›PMID 29220115›Full record

ArticleJournal of the International AIDS Society2017

HIV prevention where it is needed most: comparison of strategies for the geographical allocation of interventions.

Sarah-Jane Anderson, Peter D Ghys, Regina Ombam, Timothy B Hallett

Abstract readComparative Study
In one paragraph

Article in Journal of the International AIDS Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Trial
  2. Observational
  3. Article
  4. Improving the Efficiency of Geographic Target Regions for Healthcare Interventions.International journal of environmental research and public health · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Age-Specific Risk Scores Do Not Improve HIV-1 Prediction Among Women in South Africa.Journal of acquired immune deficiency syndromes (1999) · 2020
    Article
  9. Article
  10. Article
  11. Hotspots of Transmission Driving the Local Human Immunodeficiency Virus Epidemic in the Cologne-Bonn Region, Germany.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2019
    Article
  12. Article
  13. 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

4 authors.

Sarah-Jane AndersonDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK.ORCID 0000-0002-5945-2285
Peter D GhysUNAIDS, Geneva, Switzerland.
Regina OmbamNational AIDS Control Council, Nairobi, Kenya.
Timothy B HallettDepartment of Infectious Disease Epidemiology, Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionA strategic approach to the application of HIV prevention interventions is a core component of the UNAIDS Fast Track strategy to end the HIV epidemic by 2030. Central to these plans is a focus on high-prevalence geographies, in a bid to target resources to those in greatest need and maximize the reduction in new infections. Whilst this idea of geographical prioritization has the potential to improve efficiency, it is unclear how it should be implemented in practice. There are a range of prevention interventions which can be applied differentially across risk groups and locations, making allocation decisions complex. Here, we use mathematical modelling to compare the impact (infections averted) of a number of different approaches to the implementation of geographical prioritization of prevention interventions, similar to those emerging in policy and practice, across a range of prevention budgets.

methodsWe use geographically specific mathematical models of the epidemic and response in 48 counties and major cities of Kenya to project the impact of the different geographical prioritization approaches. We compare the geographical allocation strategies with a nationally uniform approach under which the same interventions must be applied across all modelled locations.

resultsWe find that the most extreme geographical prioritization strategy, which focuses resources exclusively to high-prevalence locations, may substantially restrict impact (41% fewer infections averted) compared to a nationally uniform approach, as opportunities for highly effective interventions for high-risk populations in lower-prevalence areas are missed. Other geographical allocation approaches, which intensify efforts in higher-prevalence areas whilst maintaining a minimum package of cost-effective interventions everywhere, consistently improve impact at all budget levels. Such strategies balance the need for greater investment in locations with the largest epidemics whilst ensuring higher-risk groups in lower-priority locations are provided with cost-effective interventions.

conclusionsOur findings serve as a warning to not be too selective in the application of prevention strategies. Further research is needed to understand how decision-makers can find the right balance between the choice of interventions, focus on high-risk populations, and geographical targeting to ensure the greatest impact of HIV prevention.

Indexed as

Resource AllocationCost-Benefit AnalysisEpidemicsHealth PolicyHealth ResourcesHIV InfectionsHumansKenyaModels, BiologicalPrevalenceRisk Factorsepidemiologygeographical prioritizationhealth policyHIV preventionmathematical modellingresource allocation

Identifiers

PMID29220115
PMCPMC5810320

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.