Spatial Epidemiology of the Syphilis Epidemic in Toronto, Canada
Bibliographic record
Abstract
BACKGROUND: Urban centers across Canada and the United States have battled syphilis epidemics with high rates of human immunodeficiency virus (HIV) coinfection for over a decade. We examined the spatial epidemiology of syphilis over time for Toronto (Canada) with the intention of forming new insights and strategies for restoring low syphilis rates. METHODS: Syphilis incidence rates, HIV-syphilis coinfection, and sexual risk behavior prevalences were estimated and mapped from primary, secondary, early latent syphilis cases reported to Toronto Public Health between January 1, 2006, and December 31, 2010, using ArcGIS 9.0. Geographic clusters of significantly elevated syphilis incidence rates were identified using SaTScan 9.0. The relationship between syphilis incidence rates and sociocultural factors was modeled using the Besag, York, and Mollie model. RESULTS: Between 2006 and 2010, syphilis incidence rates were high in Toronto's downtown core area, intensified, and spread outward initiating 3 independent outbreak areas. HIV coinfection was high (47%); however, no spatial clustering was identified. Syphilis incidence rates, HIV coinfection, and behavioral risk factors promoting sexually transmitted infection transmission were high outside the core area, suggesting that peripheral sexual networks may be influencing high syphilis infection rates both inside and outside the core. CONCLUSIONS: Toronto's syphilis epidemic is mature. Response, resources, and intervention activities should target core and noncore areas.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".