Evidence map›Paper›PMID 39800385›Full record

ArticleBMJ global health2025

Health and economic impact of oral PrEP provision across subgroups in western Kenya: a modelling analysis.

Rachel Wittenauer, Linxuan Wu, Sarah Cox, Brian Pfau, Monisha Sharma

Abstract read
In one paragraph

Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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.

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Rachel WittenauerDepartment of Pharmacy, University of Washington, Seattle, Washington, USA rwitten1@uw.edu.ORCID http://orcid.org/0000-0002-6606-8708
Linxuan WuDepartment of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA.ORCID http://orcid.org/0009-0006-7240-5412
Sarah CoxDepartment of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA.ORCID http://orcid.org/0000-0002-2447-0504
Brian PfauDepartment of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA.
Monisha SharmaDepartment of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA.

Funding

Gates Foundation INV-038274
6 · The paper itself

Abstract

introductionOral pre-exposure prophylaxis (PrEP) is a priority intervention for scale-up in countries with high HIV prevalence. Policymakers must decide how to optimise PrEP allocation to maximise health benefits within limited budgets. We assessed the health and economic impact of PrEP scale-up among different subgroups and regions in western Kenya.

methodsWe adapted an agent-based network model, EMOD-HIV, to simulate PrEP uptake in six counties of western Kenya across seven subgroups including serodiscordant couples (SDCs), adolescent girls and young women (AGYW), adolescent boys and young men, women with multiple partners and men with multiple partners. We modelled 5 years of PrEP provision assuming 90% PrEP uptake in the prioritised subgroups and evaluated outcomes over 20 years compared with a no PrEP scenario. All results are presented in 2021 USD$.

resultsPopulation PrEP coverage was highest in the broad AGYW scenario (8.3%, ~2 fold higher than the next highest coverage scenario) and lowest in the SDC scenario (0.37%). Across scenarios, PrEP averted 4.5%-21.3% of infections over the 5-year implementation. PrEP provision to SDCs was associated with the lowest incremental cost-effectiveness ratio (ICER), $245 per disability-adjusted life year (DALY) averted (CI $179 to $435), followed by women and men with multiple partners ($1898 (CI $1002 to $6771) and $2351 (CI $1 831 to $3494) per DALY averted, respectively). Targeted strategies were more efficient than broad provision even in high HIV prevalence counties; PrEP scale-up for AGYW with multiple partners had an ICER per DALY averted of $4745 (CI $2059 to $22 515) compared with $12 351 for broad AGYW (CI $7 050 to $33,955). In general, ICERs were lower in counties with higher HIV prevalence.

conclusionsPrEP scale-up can avert substantial HIV infections and increasing PrEP demand for subgroups at higher risk can increase efficiency of PrEP programmes. Our results on health and cost impact of PrEP across geographic regions in western Kenya can be used for budgetary planning and priority setting.

Indexed as

Anti-HIV AgentsHIV InfectionsPre-Exposure ProphylaxisAdministration, OralAdolescentAdultCost-Benefit AnalysisFemaleHumansKenyaMaleYoung AdultAnti-HIV AgentsDecision MakingHealth economicsHIVKenyaPrevention strategies

Identifiers

PMID39800385
PMCPMC11749867

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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.