Assessing the uptake and implementation of index testing among adolescents and young people in Sub-Saharan Africa- a systematic review
Bibliographic record
Abstract
Abstract Adolescents and young people in Sub-Saharan Africa (SSA) face high mortality rates due to the Human Immunodeficiency Virus (HIV), highlighting the need for effective case identification strategies. The index testing strategy has shown promise, but its implementation and potential for use among this population remain poorly understood. We conducted a systematic review of the literature, searching multiple databases and repositories for studies conducted in SSA since 2010, involving individuals aged 10 to 24 years. Out of 1,448 studies initially identified, only three met the inclusion criteria. The implementation of the index testing strategy primarily involved recruiting index clients at healthcare facilities and testing points, followed by community-based testing. The involvement of community health workers and peer mentors proved valuable in achieving high yields. However, the legal age for consent poses a barrier to utilizing this strategy among adolescents and young people. By addressing barriers and improving facilitators, the index testing strategy holds great potential for effective case identification in this age group in SSA.
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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 | 0.016 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".