Examining <i>Chlamydia trachomatis</i> and <i>Neisseria gonorrhoeae</i> rates between 2010 and 2015: a population-based observational study
Bibliographic record
Abstract
Bacterial sexually transmitted infections including Chlamydia trachomatis and Neisseria gonorrhoeae remain an important public health concern. We aimed to assess the population-based incidence of C. trachomatis and N. gonorrhoeae in an age-standardized cohort over time. A retrospective study of a large Canadian health region was undertaken between 2010 and 2015 using linked census and digital laboratory data. C. trachomatis and N. gonorrhoeae tests were linked to patient data. Sex and age-standardized incidence rates (IR) and ratios (IRR) were calculated for cases and testing rates. The annual mean population was 1,150,556 individuals (50.1% female). A total of 15,109 cases of chlamydia and 981 cases of gonorrhoea occurred. The overall IR for chlamydia ranged from 18.81 to 25.63 cases per 10,000 person-years. The IRR was 1.27 (95% CI 1.20-1.34, p < 0.001) for the comparison of 2015 and 2010 rates. For gonorrhoea, overall rates ranged from 0.92 to 1.86 cases per 10,000 person-years. The IRR for gonorrhoea was 2.02 (95% CI 1.56-2.59, p < 0.001) for 2015 and 2010 rates. In our large population-based study spanning six years, we observed increasing rates of C. trachomatis and N. gonorrhoeae with low testing rates.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".