LBP-1.06 Infectious syphilis in New Brunswick: using data for action in a small Canadian province
Bibliographic record
Abstract
Background New Brunswick (NB) has experienced a resurgence of infectious syphilis with a 10-fold increase in the incidence rate between 2007 and 2010. In response to this increase in cases, an outbreak control team was convened and enhanced surveillance of syphilis was implemented to better understand the epidemiology of infectious syphilis in NB and to inform public health action. Methods A standardised enhanced surveillance investigation form was developed to collect detailed information about syphilis cases, their sexual contacts, and risk factors. Since December 2010, all new cases of infectious syphilis reported in NB are followed up by regional Public Health staff using the standardised form, where completed forms are faxed to the provincial office for entry into a central database. Results are disseminated regularly to stakeholders through descriptive epidemiologic reports. Social network analysis (SNA) of cases, contacts, and meeting places for sexual partners (ie, venues) is also occurring to identify routes of transmission and points of intervention. Results Fifty-six cases of infectious syphilis have been reported in NB since November 2009, corresponding to annual incidence rates of 5.0 per 100 000 in 2010 and a projected 6.1 per 100 000 in 2011. The majority of cases are located in the small urban centers of Moncton and Fredericton with sporadic cases located in Saint John and rural NB. Ninety-three per cent of cases are male with the highest incidence rate among males aged 20–24 years (58.8 per 100 000 population from November 2009 to April 2011). Five male cases are co-infected with HIV. Eighty-eight per cent of male cases are men who have sex with men, most of whom reported having multiple casual or anonymous sex partners in the months preceding diagnosis. Venues for meeting sex partners include websites, bars, and bathhouses. The epidemiologic reports and SNA informed the first phase of a province-wide social media campaign launched in February 2011. The campaign targets men aged 18–55 years and includes distribution of posters, condom matchbooks, and online advertisements at venues identified by cases. Conclusions NB is currently experiencing an outbreak of infectious syphilis. Enhanced surveillance activities, regular epidemiologic reporting, and SNA have informed the development of public health interventions targeting adult males, primarily men who have sex with men in Moncton and Fredericton.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| 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".