Sexually Transmitted Infection Trends Among Gay or Bisexual Men From a Clinic-Based Sentinel Surveillance System in British Columbia, Canada
Bibliographic record
Abstract
INTRODUCTION: We described trends for sexually transmitted infections (STI) among gay/bisexual men in British Columbia, Canada, using a sentinel site surveillance approach. METHODS: Using data from an electronic charting system, we included gay/bisexual men who visited high-volume STI clinics from 2000 to 2013. Diagnosis rates and incidence density were calculated for chlamydia, gonorrhea, syphilis, HIV, hepatitis C, genital herpes, and genital warts. Incidence density was estimated among repeat testers who converted from a negative to positive test result. We also conducted Poisson regression analysis to determine factors that were associated with increased incidence rates. RESULTS: A total of 47,170 visits were identified for gay/bisexual men during our time frame. The median age was 34 years (interquartile range, 27-43 years), and most clients were seen in Vancouver. Although trends for most STI were stable, diagnoses of gonorrhea and syphilis have risen steadily in recent years. Coinfection with HIV was associated with higher gonorrhea and syphilis rates in the Poisson regression model. In addition, visiting a Vancouver clinic and younger age were associated with increased incidence. CONCLUSIONS: Our clinic-based sentinel surveillance system found increasing trends for gonorrhea and syphilis among gay/bisexual men but not for other STI in British Columbia. Further investigation is required to explore the syndemic effects of syphilis, gonorrhea, and HIV. This new platform will be a valuable tool for ongoing monitoring of STI and targeting prevention efforts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".