Impact of COVID-19 Pandemic on Testing for Hepatitis B in British Columbia, Canada: An Interrupted Time Series Analysis
Bibliographic record
Abstract
Background: Previous research suggests the COVID-19 pandemic was associated with reductions in HBV testing early in the pandemic. However, impacts of the pandemic on HBV testing in the longer-term and among people who inject drugs (PWID) are unclear. We investigated the impact of the pandemic and related policies on HBV testing from 2020 to 2022, including among PWID, in British Columbia (BC), Canada. Methods: Using population data from the BC COVID-19 Cohort, we conducted interrupted time series analyses of HBV surface antigen (HBsAg), HBV DNA, and HBV e-antigen (HBeAg) testing. The study included a prepandemic period (January 2017-February 2020), a transition period (March-May 2020), and pandemic periods in 2020 (June-December), 2021, and 2022. Results: HBsAg testing decreased by 16.5% (95% CI 13.9-18.9) and HBV DNA testing decreased by 11.6% (95% CI 9.5-13.6) in June-December 2020 relative to predicted levels, and testing remained lower than predicted throughout 2021 and 2022. Percentage reductions in HBV DNA testing were greater for PWID compared with non-PWID in 2020 (30.0% vs 11.2%) and thereafter. Changes in HBeAg testing overall were less pronounced but varied by sex and age. Conclusions: The pandemic and related policies were associated with decreases in HBsAg and HBV DNA testing in 2020, and testing remained lower than predicted throughout 2021 and 2022. Additional efforts to increase HBV testing are needed, including strategies to ensure linkage to care for PWID.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".