HIV care cascade for women living with HIV in the Greater Toronto Area versus the rest of Ontario and Canada
Bibliographic record
Abstract
BACKGROUND: The Greater Toronto Area (GTA) is home to 39% of Canada's population living with HIV. To identify gaps in access and engagement in care and treatment, we assessed the care cascade of women living with HIV (WLWH) in the GTA versus the rest of Ontario and Canada (in this case: Quebec and British Columbia). METHODS: We analyzed 2013-2015 self-reported baseline data from the Canadian HIV Women's Sexual and Reproductive Health Cohort Study for six care cascade stages: linked to care, retained in care, initiated antiretroviral therapy (ART), currently on ART, ART adherence (≥90%), and undetectable (<50 copies/mL). Multivariable logistic regression was used to reveal associations with being undetectable. RESULTS: Comparing the GTA to the rest of Ontario and Canada, respectively: 96%, 98%, 100% were linked to care; 92%, 94%, 98% retained in care; 72%, 89%, 96% initiated ART; 67%, 81%, 90% were currently using ART; 53%, 66%, 77% were adherent; 59%, 69%, 81% were undetectable. Factors associated with viral suppression in the multivariable model included: living outside of the GTA (Ontario: aOR = 1.72, 95% CI: 1.09-2.72; Canada: aOR = 2.42, 95% CI: 1.62-3.62), non-Canadian citizenship (landed immigrant/permanent resident: aOR = 3.23, 95% CI: 1.66-6.26; refugee/protected person/other status: aOR = 4.77, 95% CI: 1.96-11.64), completed high school (aOR = 1.77, 95% CI: 1.15-2.73), stable housing (aOR = 2.13, 95% CI: 1.33-3.39), income of ≥$20,000 (aOR = 1.52, 95% CI: 1.00-2.31), HIV diagnosis <6 years (6-14 years: aOR = 1.75, 95% CI: 1.16-2.63; >14 years: aOR = 1.87, 95% CI: 1.19-2.96), and higher resilience (aOR = 1.02, 95% CI: 1.00-1.04). CONCLUSION: WLWH living in the GTA had lower rates of viral suppression compared to the rest of Ontario and Canada even after adjustment of age, ethnicity, and HIV diagnosis duration. High-impact programming for WLWH in the GTA to improve HIV outcomes are greatly needed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".