Investigation of a Gonorrhea Outbreak in an Isolated Northern Alberta Community, 2015
Bibliographic record
Abstract
Background. In 2014, the rate of Neisseria gonorrhea (NG) in the North-Northwest subzone of Alberta (191/100,000) was four times higher than the provincial rate (46/100,000). Nearly one-third of cases in the subzone were reported from a small isolated community (population estimate: 2000–2500). An investigation of cases was undertaken to determine transmission networks. Methods. A descriptive summary of all NG cases reported in 2015 from the community was conducted using routinely collected surveillance and partner data. During a two-week period in the fall of 2015, cases and contacts were contacted to be re-interviewed to identify local exposure details. NG multiantigen sequence typing was determined and susceptibility to cephalosporins and ciprofloxacin was predicted by RT-PCR using the NAAT specimens. A social network analysis was completed using partner information. Results. In 2015, there were 84 NG cases reported in the community. All cases were heterosexual, 47.6% (n = 40) were female, and 20% (n = 8) were pregnant. The median age was 24 years (IQR: 20–30). Twenty-one clients were re-interviewed for local exposure details, representing a participation rate of 19.1% for the 110 gonorrhea cases and contacts. The majority of clients re-interviewed reported limited condom use (90.5%; n = 19), being under the influence of alcohol or drugs during sexual encounters (61.1%; n = 11), and meeting partners through local house parties (66.7%; n = 12). An additional one-third (n = 6) of participants met partners on-line. Eight unique STs were identified among 41 cases. In addition, 70% (n = 29) of the sequence typed cases belong to sequence group ST-7576; one isolate in the province was available from this group and was resistant to erythromycin and tetracycline. SNP assay results were available for 19 specimens among 7 different STs; all were predicted to be susceptible to cephalosporins and ciprofloxacin. There were 21 sexual network components identified, with 33% (n = 42) of individuals in network components of three or fewer people. The largest network represents 46.8% (n = 59) of cases and contacts. Conclusion. Using the combination of routine surveillance data, with enhanced exposure details and in-depth laboratory data, we were able to ascertain key aspects of the outbreak for local intervention. Disclosures. All authors: No reported disclosures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".