Factors associated with unsuppressed HIV viral load among children under 15 years in sub-Saharan africa: a systematic review
Bibliographic record
Abstract
BACKGROUND: Viral suppression among children living with HIV remains suboptimal in sub-Saharan Africa. The marked heterogeneity in suppression rates across countries underscores the need for comparative analyses to elucidate context-specific determinants. This systematic review aims to synthesize existing evidence on factors associated with unsuppressed viral loads in paediatric populations. METHODS: A systematic review was conducted to examine viral load suppression among children under 15 years in sub-Saharan Africa. Comprehensive searches were performed across four major databases: PubMed, Google Scholar, Embase, and Web of Science. Eligible studies were published in English between 2010 and 2024, focused exclusively on paediatric populations in Africa, and available in full text. Relevant data were systematically extracted and compiled in a structured Excel database to prevent duplication and facilitate rigorous, methodologically sound analysis. RESULTS: Of the 161 articles initially identified, 16 met the predefined inclusion criteria for this review. These studies were conducted across multiple sub-Saharan African countries and used various methodological designs. The most frequently reported factors associated with an unsuppressed viral load among children receiving antiretroviral therapy (ART) were suboptimal treatment adherence, malnutrition, low maternal educational attainment, a high baseline viral load, and missed clinical appointments. Adherence to ART was the most extensively analysed variable, and poor adherence was consistently and strongly associated with virological failure. CONCLUSION: Viral suppression among children living with HIV in sub-Saharan Africa remains unacceptably low. This review emphasized key preventable factors mostly poor adherence. Targeted, urgent interventions are needed to improve outcomes for this vulnerable population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".