Applying core theory and spatial analysis to identify hepatitis C virus infection “core areas” in British Columbia, Canada
Bibliographic record
Abstract
"Core areas" of transmission for bacterial sexually transmitted infections have been identified. However, it is unclear whether core areas apply to viral infections, such as hepatitis C virus (HCV). We used geographic mapping and spatial analysis to identify distinct core areas of HCV infection in British Columbia (BC) using the BC Hepatitis Testers Cohort (BC-HTC), 1990-2013. The BC-HTC includes all BC residents tested for HCV (~1.5 million; 1990-2013). Core HCV infection areas were identified spatially and temporally for five time periods (1990-1993, 1994-1998, 1999-2003, 2004-2008 and 2009-2013) through thematic mapping, Kernel Density Estimation, Hotspot analysis and cluster analysis at the Census dissemination area level in ArcGIS and SatScan. HCV infection core areas were consistently identified. HCV core areas expanded from the downtown of major cities in different regions of BC (Metro Vancouver, Vancouver Island, and Northern BC; 1990-1998), to smaller cities in Metro Vancouver and Interior BC (2000 onwards). Statistically significant clusters, or hotspots, were also observed for downtown Vancouver, Northern BC (Prince George) and Vancouver Island from 1990 to 2008 with expansion to other urban areas in Metro Vancouver from 1990-2013. Statistically significant clusters persisted after adjustment for injection drug use, number of HCV tests, age, sex, material and social deprivation. Persistence of areas with high HCV diagnoses rates in Vancouver and Prince George supports the theory of core areas of HCV transmission. Identification of core areas can inform prevention, care and treatment programme interventions and evaluate their impact over time.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".