High Levels of Heterogeneity in the HIV Cascade of Care across Different Population Subgroups in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: The HIV cascade of care (cascade) is a comprehensive tool which identifies attrition along the HIV care continuum. We executed analyses to explicate heterogeneity in the cascade across key strata, as well as identify predictors of attrition across stages of the cascade. METHODS: Using linked individual-level data for the population of HIV-positive individuals in BC, we considered the 2011 calendar year, including individuals diagnosed at least 6 months prior, and excluding individuals that died or were lost to follow-up before January 1st, 2011. We defined five stages in the cascade framework: HIV 'diagnosed', 'linked' to care, 'retained' in care, 'on HAART' and virologically 'suppressed'. We stratified the cascade by sex, age, risk category, and regional health authority. Finally, multiple logistic regression models were built to predict attrition across each stage of the cascade, adjusting for stratification variables. RESULTS: We identified 7621 HIV diagnosed individuals during the study period; 80% were male and 5% were <30, 17% 30-39, 37% 40-49 and 40% were ≥ 50 years. Of these, 32% were MSM, 28% IDU, 8% MSM/IDU, 12% heterosexual, and 20% other. Overall, 85% of individuals 'on HAART' were 'suppressed'; however, this proportion ranged from 60%-93% in our various stratifications. Most individuals, in all subgroups, were lost between the stages: 'linked' to 'retained' and 'on HAART' to 'suppressed'. Subgroups with the highest attrition between these stages included females and individuals <30 years (regardless of transmission risk group). IDUs experienced the greatest attrition of all subgroups. Logistic regression results found extensive statistically significant heterogeneity in attrition across the cascade between subgroups and regional health authorities. CONCLUSIONS: We found that extensive heterogeneity in attrition existed across subgroups and regional health authorities along the HIV cascade of care in B.C., Canada. Our results provide critical information to optimize engagement in care and health service delivery.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 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".