Enteric outbreak surveillance in British Columbia, 2009-2013
Bibliographic record
Abstract
Background: Understanding enteric disease outbreak sources, burden of illness, mode of transmission and use of interventions informs planning, policy development and prevention programs.Objective: To describe trends in enteric disease outbreaks investigated in British Columbia (BC) between 2009 and 2013.Methods: An analysis was conducted of enteric disease outbreaks that had been entered into a national, secure web-enabled outbreak reporting system using the Canadian Network for Public Health Intelligence (CNPHI) and investigated in BC between January 1, 2009 and December 31, 2013.The data included information on pathogen, number of cases, hospitalizations, deaths, setting, mode of transmission, source, factors that contributed to the outbreak and interventions.Residential facility-based viral outbreaks and outbreaks associated with international travel were excluded.Results: There were 104 outbreaks investigated in BC between 2009 and 2013.Ninety-three were reported by BC organizations and 11 were national outbreak investigations reported by the Public Health Agency of Canada (PHAC).There was an average of 21 outbreaks per year.Overall, the annual rate of foodborne outbreaks in BC was 2.8 per one million population.Seventy-nine (76%) outbreaks had a pathogen identified, most commonly norovirus, Salmonella and E. coli.There was a total of 108 hospitalizations (3.8% of all cases) and two deaths (0.1% of all cases); one caused by botulism, the other by E. coli O157.Food service establishments were the most common setting (33.7%), followed by the community (24.0%) and private functions (12.5%).The food types most often reported were fruits and vegetables, meat and seafood.The data showed a pathogen-food source combination between Salmonella and eggs.Conclusion: This is the first publication summarizing trends in enteric disease outbreaks in BC including assessing sources, burden and interventions.Ongoing reporting and analysis of outbreak data in BC will allow for improved assessment of trends in sources and pathogens over time and further understanding of the effectiveness of interventions associated with outbreaks.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".