Community Pop‐Up Clinic: Cascade of Care and <scp>HCV</scp> Treatment of Vancouver's Inner‐City <scp>PWID</scp> Populations
Bibliographic record
Abstract
Elimination of HCV infection as a public health concern by the end of this decade will require a concerted effort in all target populations, including drug-users in the inner-city. Several strategies have been proposed to identify, engage and provide HCV-infected residents with antiviral therapy and maximise treatment and cure achievement. This study aims to assess the effectiveness of a multidisciplinary approach in delivering HCV treatment to people who inject drugs (PWID) within Vancouver's inner city. We have evaluated a novel approach, the Community Pop-Up Clinic, for its ability to promote access to care and uptake of HCV therapy, with additional analyses of HCV reinfection and opioid-related mortality. From January 2021 to August 2023, we evaluated 1968 individuals. 620 (31.5%) were found to carry HCV antibodies and of these, 474 (76.5%) were found to be viremic. Treatment engagement has been secured in 387 (81.6%). 326 (84.2%) have started treatment, 60 in the pre-treatment phase and 1 died of an overdose in pre-treatment. Of 326, 302 completed treatments, 18 are currently on treatment and 1 died of an overdose. Of 302 who completed treatment, 286 confirmed as cured (SVR 12), 16 are awaiting SVR 4, 2 had documented virologic relapse and 1 was reinfected. Three patients withdrew from treatment. By mITT, the cure rate is 286/288 (99.3%). We documented 2 overdose deaths over 326 PY. The data presented validates multidisciplinary programs such as ours aimed at treating HCV in inner-cities and highlights societal benefits that could be achieved including lower overdose death rates.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".