Constructing the cascade of HIV care
Bibliographic record
Abstract
PURPOSE OF REVIEW: Although the concept of the HIV treatment cascade has reached nearly ubiquitous acceptance in international HIV policy and research, methods for estimating it vary drastically. These variations become increasingly important as the focus of the HIV response shifts from emergency response to long-term outcomes and financial and organizational sustainability. We review the history of the cascade and the current literature and develop the first comprehensive typology of cascade scope and methods. RECENT FINDINGS: We define the cascade scope in terms of both breadth (range from first to final event) and depth (given breadth, number of cascade stages that analyzed). We distinguish cascade measurement according to four dimensions: denominator-denominator linkage (data used for cascade construction are linked at the individual level across stages); denominator-numerator linkage (data are linked at the individual level within each stage); single vs. multiple populations from which data sources are drawn; and longitudinal vs. cross-sectional design. SUMMARY: Everything else equal, we would prefer broader and deeper cascades, denominator-denominator linkage, denominator-numerator linkage, single population, and longitudinal data over their respective alternatives. Increased investments in population-based cohorts and data linkage are required to complement clinical cohorts for 'broad' longitudinal cascade analyses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".