Epidemiology of Enteric Disease in C‐EnterNet’s Pilot Site – Waterloo Region, Ontario, 1990 to 2004
Bibliographic record
Abstract
OBJECTIVE: The objective of the present study was to describe the epidemiology of reportable enteric illness in Ontario's Waterloo region, including comparing calculated incidence rates with published rates, and adjusting for under-reporting to determine the number of community cases, where published data were available. METHODS: Descriptive analyses were performed on reportable disease data for 13 enteric diseases collected in the Waterloo region from 1990 to 2004. Poisson and negative binomial regression analyses were used to investigate differences in incidence rates among age, sex, the 15 years of data and seasons. Disease-specific incidence rates were calculated and compared with the literature, where possible. Under-reporting ratios from the literature were applied to estimate the number of cases of campylobacteriosis, nontyphoidal salmonellosis and verotoxigenic Escherichia coli infection at the community level. RESULTS: Over the study period, the average annual age- and sex-adjusted incidence rates per 100,000 population were highest for campylobacteriosis (49.69 cases), followed by giardiasis (31.87 cases) and nontyphoidal salmonellosis (25.97 cases). The incidence of most enteric illnesses peaked in the summer. The highest incidence occurred in young children, followed by adults in their 20s. Diarrhea (85.4%) was the most frequently reported symptom, food (57.4%) was the most commonly reported probable source, and home (41.7%) and travel (37.0%) were the two most frequently reported risk settings. CONCLUSIONS: Enteric illness was a significant health burden in the Waterloo region from 1990 to 2004. Because reportable disease data are subject to under-reporting, it is likely that the true burden is greater than estimated in the present study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".