Evidence map›Paper›PMID 32562353›Full record

ArticleJournal of the International AIDS Society2020

Integrated screening and treatment services for HIV, hypertension and diabetes in Kenya: assessing the epidemiological impact and cost-effectiveness from a national and regional perspective.

Parastu Kasaie, Brian Weir, Melissa Schnure, Chen Dun, Jeff Pennington, Yu Teng, Richard Wamai, Kipkoech Mutai, David Dowdy, Chris Beyrer

Abstract read
In one paragraph

Article in Journal of the International AIDS Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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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

10 authors.

Parastu KasaieDepartment of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-3744-9501
Brian WeirDepartment of Health, Behavior and Society, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Melissa SchnureDepartment of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Chen DunDepartment of Health, Behavior and Society, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Jeff PenningtonDepartment of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Yu TengAvenir Health, Glastonbury, CT, USA.
Richard WamaiDepartment of Cultures, Societies and Global Studies, Integrated Initiative for Global Health, Northeastern University, Boston, MA, USA.
Kipkoech MutaiNational AIDS Control Council, Nairobi, Kenya.
David DowdyDepartment of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Chris BeyrerDepartment of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0003-0665-9124

Funding

Projecting the Epidemiologic and Economic Impact of HIV Prevention Efforts in the Context of Other Sexually Transmitted InfectionsK01AI138853 · NIAID · JOHNS HOPKINS UNIVERSITY · PI KASAIE, PARASTU · 2019 to 2023
$591k
NIAID NIH HHS K01 AI138853NIAID NIH HHS K01AI138853
6 · The paper itself

Abstract

introductionAs people with HIV age, prevention and management of other communicable and non-communicable diseases (NCDs) will become increasingly important. Integration of screening and treatment for HIV and NCDs is a promising approach for addressing the dual burden of these diseases. The aim of this study was to assess the epidemiological impact and cost-effectiveness of a community-wide integrated programme for screening and treatment of HIV, hypertension and diabetes in Kenya.

methodsCoupling a microsimulation of cardiovascular diseases (CVDs) with a population-based model of HIV dynamics (the Spectrum), we created a hybrid HIV/CVD model. Interventions were modelled from year 2019 (baseline) to 2023, and population was followed to 2033. Analyses were carried at a national level and for three selected regions (Nairobi, Coast and Central).

resultsAt a national level, the model projected 7.62 million individuals living with untreated hypertension, 692,000 with untreated diabetes and 592,000 individuals in need of ART in year 2018. Improving ART coverage from 68% at baseline to 88% in 2033 reduced HIV incidence by an estimated 64%. Providing NCD treatment to 50% of diagnosed cases from 2019 to 2023 and maintaining them on treatment afterwards could avert 116,000 CVD events and 43,600 CVD deaths in Kenya over the next 15 years. At a regional level, the estimated impact of expanded HIV services was highest in Nairobi region (averting 42,100 HIV infections compared to baseline) while Central region experienced the highest impact of expanded NCD treatment (with a reduction of 22,200 CVD events). The integrated HIV/NCD intervention could avert 7.76 million disability-adjusted-life-years (DALYs) over 15 years at an estimated cost of $6.68 billion ($445.27 million per year), or $860.30 per DALY averted. At a cost-effectiveness threshold of $2,010 per DALY averted, the probability of cost-effectiveness was 0.92, ranging from 0.71 in Central to 0.92 in Nairobi region.

conclusionsIntegrated screening and treatment of HIV and NCDs can be a cost-effective and impactful approach to save lives of people with HIV in Kenya, although important variation exists at the regional level. Containing the substantial costs required for scale-up will be critical for management of HIV and NCDs on a national scale.

Indexed as

Mass ScreeningAdultCardiovascular DiseasesCost-Benefit AnalysisDiabetes MellitusFemaleHealth ServicesHIV InfectionsHumansHypertensionKenyaMaleNoncommunicable DiseasesQuality-Adjusted Life Yearscomputer simulationcost-benefit analysisdiabetes mellitusHIVhypertensionKenya

Identifiers

PMID32562353
PMCPMC7305418

What OpenQuestion holds

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LicenceCC BY
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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.