Evidence map›Paper›PMID 42467705›Full record

ArticlePloS one2026

Geographic inequalities in HIV testing uptake among young women in sub-Saharan Africa: A hierarchical bayesian spatial analysis.

Bewuketu Terefe, Nebiyu Mekonnen Derseh, Tadesse Awoke Ayele

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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3 authors.

Bewuketu TerefeCollege of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.ORCID https://orcid.org/0000-0002-0063-0999
Nebiyu Mekonnen DersehDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.ORCID https://orcid.org/0000-0003-1355-2763
Tadesse Awoke AyeleDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the high prevalence of HIV infection among young women in sub-Saharan Africa (SSA), the adoption of HIV testing and counseling remains low. The uptake of HIV testing among young women in SSA remains poorly understood. Consequently, identifying the spatial distributions, prevalence, and factors that influence HIV testing among these marginalized groups of the population is crucial for policymakers, implementers, and researchers to achieve the 2030 Sustainable Development Goal plans to tackle the progress of the disease. Hence, the aim of this study was to assess HIV testing uptake, its spatial variation, and associated factors among young women in SSA from 2016 to 2023.

methodsA community-based cross-sectional study was conducted among a weighted sample of 140,054 young women in SSA using recent demographic and health survey data. Statistical analyses were performed using R version 4.3.2, incorporating spatial analysis techniques (autocorrelation, interpolation, and SaTScan) and Bayesian hierarchical logistic regression to identify the factors associated with HIV testing uptake. Model parameters were estimated using Markov Chain Monte Carlo methods, and the results are reported as adjusted odds ratios (ORs) with 95% credible intervals.

resultsSpatial analyses showed that HIV testing uptake was distributed unevenly; hotspots of high HIV testing uptake were found in Eastern and Southern Africa, and low uptake areas were found in Western Africa. The overall pooled prevalence of HIV testing was 38.9%. Primary education, secondary/higher education, employment, mass media, being married, widowed/divorced, modern contraceptive use, age, middle income, rich, risky sexual behaviors, poor attitude towards HIV patients, literacy rates, alcohol consumption, pregnant women, female households, rural residents, and distance to a health facility were statistically significant outcome variables.

conclusionsThe study revealed that HIV testing uptake among young women in SSA is significantly below the 95%-95%-95% target, with notable spatial clustering and variation across countries. Key factors influencing uptake included age, education, HIV knowledge, employment, media exposure, marital status, pregnancy status, and socioeconomic conditions. To improve testing rates, it is critical to implement targeted policy interventions, such as enhancing educational programs, addressing sociocultural barriers, and expanding access to healthcare, particularly in underrepresented regions. These actions are essential not only to increase HIV testing coverage but also to move closer to achieving the 95-95-95 targets and reducing new HIV infections in SSA.

Indexed as

HIV InfectionsHIV TestingAdolescentAdultAfrica South of the SaharaBayes TheoremCross-Sectional StudiesFemaleHumansMass ScreeningPrevalenceSocioeconomic FactorsSpatial AnalysisYoung Adult

Identifiers

PMID42467705
PMCPMC13379148

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