Curbing the Epidemic: Evolving Public Health Practices and Implications of Prenatal Syphilis Screening Patterns in Ontario, Canada
Bibliographic record
Abstract
Background: Congenital syphilis rates increased significantly between 2018 and 2023 in Ontario, Canada. Timely prenatal syphilis screening is essential for preventing congenital syphilis. We examined the adoption and impact of universal rescreening recommendations on prenatal screening rates and described universal prenatal syphilis screening patterns and factors associated with no or late screening. Methods: First, we surveyed Ontario public health units (PHUs) to identify changes to local prenatal syphilis screening recommendations between 2018 and 2023. Then, using provincial public health laboratory data from nine PHUs for 2019 to 2023, we examined the impact of rescreening adoption on prenatal screening rates, using a difference-in-differences analysis. Next, we described Ontario’s prenatal syphilis screening patterns by conducting a retrospective cohort study with linked provincial administrative health data. Modified Poisson regression was used to assess factors associated with no or late (third trimester or at delivery) initial screening. Results: Twenty-eight of 34 PHUs responded to the survey; by December 2023, 10 PHUs (36%) had recommended universal prenatal syphilis rescreening. In the difference-in-differences analysis, adoption of universal rescreening recommendations was associated with 392 more monthly tests performed per 1,000 pregnancies (95% confidence interval (CI): 205–579), with effect size varying by PHU. Among 551,733 pregnancies included in the retrospective cohort, 507,193 (92%) received any prenatal syphilis screening and 435,176 (79%) received first-trimester screening. Different maternal phenotypes described individuals receiving no or late prenatal syphilis screening. Syphilis screening within one year before conception (adjusted relative risk, 2.11; 95% CI, 2.07–2.15) was associated with receipt of no screening in pregnancy. Younger age at conception (ages 15–19 vs. 30–34) (4.37; 3.62–5.28), recent injection drug use (3.58; 2.95–4.34), and living in the lowest-income neighbourhood (1.51; 1.33–1.72) were associated with being initially screened at delivery. Discussion: During a period of rapidly evolving syphilis epidemiology, we observed sub-optimal and inequitable uptake of universal prenatal syphilis screening. Universal rescreening recommendations increased prenatal syphilis screening rates at the population-level; however, PHU-level variability highlighted the importance of implementation strategies and local contexts. Targeted and coordinated public health interventions are required to improve prenatal syphilis screening coverage and timeliness.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".