Healthcare and treatment experiences among people diagnosed with HIV before and after a province-wide treatment as prevention initiative in British Columbia, Canada
Bibliographic record
Abstract
INTRODUCTION: In 2010, the Canadian province of British Columbia (BC) initiated the Seek and Treat for Optimal Prevention of HIV/AIDS (STOP HIV/AIDS) program to improve HIV testing, linkage to care, and treatment uptake, thereby operationalizing the HIV Treatment as Prevention (TasP) framework at the population-level. In this analysis, we evaluated self-reported HIV care experiences and therapeutic outcomes among people diagnosed with HIV prior to and after implementation of this provincial program. METHODS: A cross-sectional analysis was performed on the baseline data of a cohort of people living with HIV (PLWH) (19 years and older) in the province of BC sampled from July 2016 to September 2018. All participants consented to linking their survey data to the provincial HIV treatment registry. Individuals diagnosed with HIV from January 1 2000-December 31 2009 were classified as pre-intervention and those diagnosed January 1 2010-December 31 2018 as post-intervention cohorts. Bivariate analyses were run using Chi-square and Wilcoxon Rank Sum tests. Cox proportional hazards regression model demonstrates time to antiretroviral therapy (ART) initiation (from HIV baseline) and virological suppression (2 consecutive plasma viral load measurements < 200 copies/ml). RESULTS: Of the 325 participants included in this analysis, 198 (61%) were diagnosed with HIV in the pre-intervention era and 127 (39%) in the post-intervention era. A higher proportion of participants in post-intervention era were diagnosed at walk-in clinics (45% vs. 39%) and hospitals (21% vs. 11%) (vs pre-intervention) (p = 0.042). Post-intervention participants had initiated ART with less advanced HIV disease (CD4 count 410 vs. 270 cells/ul; p = 0.001) and were less likely to experience treatment interruptions at any point in the 5 years after HIV diagnosis (17% vs. 48%; p < 0.001). The post-intervention cohort had significantly more timely ART initiation (aHR: 5.97, 95%CI 4.47, 7.97) and virologic suppression (aHR: 2.03, 95%CI 1.58, 2.60) following diagnosis, after controlling for confounders. CONCLUSIONS: We found favourable treatment experiences and more timely ART initiation and virologic suppression after a targeted TasP provincial program. Our results illustrate the importance of accessible low-barrier HIV testing and treatment in tackling the HIV epidemic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".