Establishing criteria to initiate enteric outbreak investigations in British Columbia
Bibliographic record
Abstract
OBJECTIVE: To establish and evaluate criteria to initiate provincial enteric outbreak investigations based on characteristics of alerts, clusters and successful outbreak investigations. METHODS: We tracked all enteric disease alerts and clusters reported to the British Columbia Centre for Disease Control (BCCDC) in 2011 and 2012. Information was collected on etiology, number of cases, geographic spread, dates reported, and method of notification. Actions were classified as no further action, review/report or investigation. Outbreak investigation outcome was classified as solved/not solved. 2011 data were used to identify characteristics of alerts and clusters more likely to lead to outbreak investigations and of solved outbreaks to establish criteria. Criteria for initiating an outbreak investigation were evaluated retrospectively using 2011 data and then implemented in 2012. RESULTS: In 2011, 251 alerts/clusters of enteric diseases were reported. Fourteen (5.6%) led to an outbreak investigation and nine (64.3%) of the outbreaks were solved. Analyzing the data retrospectively, criteria were identified from the alerts and clusters that led to outbreak investigations and successful outbreak investigations: pathogen specificity, timely notification, a common source or event, and multi-regional outbreaks or outbreaks reported by other agencies. After applying these criteria prospectively in 2012, we took action on a smaller proportion of the 244 alerts and clusters (32.0% compared to 44.6% in 2011) and 66.7% of them were solved (compared to 64.3% in 2011). CONCLUSION: Continued evaluation will identify whether this will improve outbreak investigations and use of resources in British Columbia.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".