Intersecting Risk Factors Associated With High Syphilis Seroprevalence Among a Street-Involved Population in Canada
Bibliographic record
Abstract
Background: Syphilis has reemerged as a global public health concern. In Ontario, Canada's most populous province, a 340% increase in infectious syphilis cases was observed between 2013 and 2023. This surge was accompanied by a demographic shift, with women emerging as the fastest-growing at-risk group. We examined intersecting risk factors associated with syphilis seropositivity among a street-involved population. Methods: Data were collected from the Syphilis Point of Care Rapid Test and Immediate Treatment Evaluation (SPRITE) study-an outreach model of care implemented by 8 public health units (PHUs) across Ontario between 2023 and 2024. Reactive treponemal antibodies defined syphilis seroprevalence. A mixed-effects regression with a log-binomial distribution was used to evaluate the association between risk factors and seropositivity. Adjusted prevalence ratio (aPR) controlled for age and sex and clustering by PHUs. Results: A total of 630 participants, 42% women, with a median age of 38, were included; 19.1% of participants reported having sexual risk factors, using illicit drugs, and being un(der)housed. Overall, syphilis seroprevalence was 7.6% (95% confidence interval 5.5-9.7), with significant heterogeneity across the province and higher among those reporting 3 risk factors (19.2% [11.2-29.7]) compared with 1 risk factor (4.8% [1.8-10.1]). Seropositivity was higher among women (aPR 1.62 [.94-2.80]) and people who use illicit drugs (aPR 2.30 [.93-5.50]), particularly those who use crystal methamphetamine (aPR 2.88 [1.31-6.33]). Conclusions: Syphilis is heightened at the intersection of sexual risk factors, illicit drug use, and housing instability among equity-deserving populations. Targeted outreach models of care are necessary to reach this emerging at-risk population.
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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 | 0.001 |
| 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".