A descriptive study of syphilis testing in Manitoba, Canada, 2015–2019
Bibliographic record
Abstract
Background: In 2018, Manitoba had the highest reported rate of infectious syphilis in Canada, at over three times the national average. Infectious syphilis in Manitoba is centred on young, marginalized heterosexual couples in Winnipeg's inner-city. Subsequently, a public health crisis involving congenital syphilis emerged in Manitoba, just prior to the coronavirus disease 2019 pandemic. Testing and screening (in the case of pregnancy) for syphilis is thought to be an effective measure to reduce the incidence of syphilis and its sequelae. The aim of this study is to describe syphilis testing practices in the general population and amongst pregnant women, during a period of shifting syphilis epidemiology. Methods: We used population-based syphilis testing data from Cadham Provincial Laboratory (Winnipeg, Manitoba) for 2015 to 2019. Directly age-standardized rates are reported, and Poisson regression used to model the determinants of testing rates. Rates of prenatal screening are also reported. Results: From 2015 to 2019, a total of 386,350 individuals were tested for syphilis. The rate increased annually, from 462 per 10,000 population in 2015 to 704 per 100,000 in 2019, while the female-to-male ratio decreased from 1.8 to 1.6. Prior to 2019, the majority of pregnant women (approximately 60%) were screened once, during the first trimester; however, 2019 saw more women having more than two tests during the course of their pregnancy. Conclusion: An overall increase in the number of individuals tested was observed, reflecting the increased rate of syphilis in Manitoba. Prenatal screening patterns shifted in 2019, likely in response to rising congenital syphilis numbers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.004 | 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) | 0.003 | 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".