Evaluating the Impact of Implementing and Scaling-Up the Use of Syphilis Rapid/Point-of-Care Tests: An Interrupted Time Series Analysis of New Syphilis Positivity Rates in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: In July 2019, a syphilis outbreak was declared in Alberta, Canada, affecting key populations. Syphilis rapid/point-of-care testing (RPOCT) provides opportunities to test individuals in nontraditional settings and provide same-day treatment. This study aimed to evaluate whether RPOCT resulted in a decline in new syphilis positivity rates. METHODS: Starting August 2020, syphilis RPOCTs were implemented in a single (Edmonton) health zone (EDM phase) and in March 2022 were scaled up across the province of Alberta (ProvScaleUp phase). To evaluate the impact of RPOCTs on new syphilis positivity rates, interrupted time-series analyses were used to analyze population-standardized new syphilis positivity rates before, during, and after RPOCT implementation. Generalized linear models assessed percentage declines in new syphilis positivity rates after RPOCT implementation. RESULTS: In the preintervention period, monthly new syphilis positivity rates significantly increased across Alberta. After RPOCTs were implemented regionally (EDM phase), syphilis positivity rates decreased by an average of 15% (0.25 per 100 000 population). After wider distribution (ProvScaleUp phase), provincial rates decreased by 25% (0.22 per 100 000 population). Rates decreased more in the general versus prenatal population (15.9% vs 12.2%), among males versus females (16.0% vs 14.5%), among those in metropolitan versus urban and rural areas (15.2%, 14.0%, and 12.2%, respectively) and decreased the least among those aged 24-29 (12.5%). CONCLUSIONS: Syphilis RPOCT implementation was associated with a significant decrease in new syphilis positivity rates in a province of a high-income country experiencing a resurgence of heterosexual syphilis among key populations facing barriers to testing and treatment.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".