Evidence map›Paper›PMID 37075002›Full record

ArticlePLOS global public health2023

Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa.

Adam Howes, Kathryn A Risher, Van Kính Nguyen, Oliver Stevens, Katherine M Jia, Timothy M Wolock, Rachel T Esra, Lycias Zembe, Ian Wanyeki, Mary Mahy and 3 more

Open access · goldAbstract read
In one paragraph

Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 13 citations in OpenAlex.

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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

13 authors at 6 institutions in 4 countries.

Adam HowesDepartment of Mathematics, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-2386-4031
Kathryn A RisherMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-9588-1693
Van Kính NguyenMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-8912-5288
Oliver StevensMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Katherine M JiaCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.
Timothy M WolockDepartment of Mathematics, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-5898-1014
Rachel T EsraMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Lycias ZembeJoint United Nations Programme on HIV/AIDS, Geneva, Switzerland.ORCID https://orcid.org/0000-0002-2239-4296
Ian WanyekiJoint United Nations Programme on HIV/AIDS, Geneva, Switzerland.
Mary MahyJoint United Nations Programme on HIV/AIDS, Geneva, Switzerland.ORCID https://orcid.org/0000-0001-6023-3023
Clemens BenediktJoint United Nations Programme on HIV/AIDS, Geneva, Switzerland.
Seth R FlaxmanDepartment of Computer Science, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-2477-4217
Jeffrey W EatonMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Imperial College London · GBJoint United Nations Programme on HIV/AIDS · CHCenter for Disease Dynamics, Economics & Policy · USHeidelberg University · DEPennsylvania State University · USUniversity of Oxford · GB

Funding

Statistical Models for Estimating and Projecting HIV/AIDS EpidemicsR01AI136664 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI BAO, LE · 2017 to 2021
$3.6M
Medical Research Council MR/R015600/1NIAID NIH HHS R01 AI136664
6 · The paper itself

Abstract

The Global AIDS Strategy 2021-2026 identifies adolescent girls and young women (AGYW) as a priority population for HIV prevention, and recommends differentiating intervention portfolios geographically based on local HIV incidence and individual risk behaviours. We estimated prevalence of HIV risk behaviours and associated HIV incidence at health district level among AGYW living in 13 countries in sub-Saharan Africa. We analysed 46 geospatially-referenced national household surveys conducted between 1999-2018 across 13 high HIV burden countries in sub-Saharan Africa. Female survey respondents aged 15-29 years were classified into four risk groups (not sexually active, cohabiting, non-regular or multiple partner[s] and female sex workers [FSW]) based on reported sexual behaviour. We used a Bayesian spatio-temporal multinomial regression model to estimate the proportion of AGYW in each risk group stratified by district, year, and five-year age group. Using subnational estimates of HIV prevalence and incidence produced by countries with support from UNAIDS, we estimated new HIV infections in each risk group by district and age group. We then assessed the efficiency of prioritising interventions according to risk group. Data consisted of 274,970 female survey respondents aged 15-29. Among women aged 20-29, cohabiting (63.1%) was more common in eastern Africa than non-regular or multiple partner(s) (21.3%), while in southern countries non-regular or multiple partner(s) (58.9%) were more common than cohabiting (23.4%). Risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%. FSW were 1.3% of the population but 10.6% of all expected new infections. Our risk group estimates provide data for HIV programmes to set targets and implement differentiated prevention strategies outlined in the Global AIDS Strategy. Successfully implementing this approach would result in more efficiently reaching substantially more of those at risk for infections.

Identifiers

PMID37075002
PMCPMC10115274
OpenAlexW4366351150

What OpenQuestion holds

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LicenceCC BY
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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.