Impact of the COVID-19 Pandemic on Hepatitis C Treatment Initiation in British Columbia, Canada: An Interrupted Time Series Study
Bibliographic record
Abstract
We investigated the impacts of the COVID-19 pandemic on hepatitis C (HCV) treatment initiation, including by birth cohort and injection drug use status, in British Columbia (BC), Canada. Using population data from the BC COVID-19 Cohort, we conducted interrupted time series analyses, estimating changes in HCV treatment initiation following the introduction of pandemic-related policies in March 2020. The study included a pre-policy period (April 2018 to March 2020) and three follow-up periods (April to December 2020, January to December 2021, and January to December 2022). The level of HCV treatment initiation decreased by 26% in April 2020 (rate ratio 0.74, 95% confidence interval [CI] 0.60 to 0.91). Overall, no statistically significant difference in HCV treatment initiation occurred over the 2020 and 2021 post-policy periods, and an increase of 34.4% (95% CI 0.6 to 75.8) occurred in 2022 (equating to 321 additional people initiating treatment), relative to expectation. Decreases in HCV treatment initiation occurred in 2020 for people born between 1965 and 1974 (25.5%) and people who inject drugs (24.5%), relative to expectation. In summary, the pandemic was associated with short-term disruptions in HCV treatment initiation in BC, which were greater for people born 1965 to 1974 and people who inject drugs.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".