Infectious Disease Outbreaks Related to Drinking Water in Canada, 1974–2001
Bibliographic record
Abstract
Recent public attention on drinking water supplies in the aftermath of waterborne infection outbreaks in Walkerton and North Battleford raises questions about safety. We analyzed information on waterborne outbreaks occurring between 1974 and 2001 in order to identify apparent trends, review the current status of monitoring and reporting, and gain a better understanding of the impact of drinking water quality on public health and disease burden. Data from outbreak investigations, published and unpublished, were categorized by the type of drinking water provider and were assessed to be definitely, probably or possibly waterborne in nature. The final data set consisted of 288 outbreaks of disease linked to a drinking water source. There were 99 outbreaks in public water systems, 138 outbreaks in semi-public systems and 51 outbreaks in private systems. The main known causative agents of waterborne disease outbreaks were (in descending frequency of occurrence) Giardia, Campylobacter, Cryptosporidium , Norwalk-like viruses, Salmonella and hepatitis A virus. We found that severe weather, close proximity to animal populations, treatment system malfunctions, poor maintenance and treatment practices were associated with the reported disease outbreaks resulting from drinking water supplies. However, issues related to the accuracy, co-ordination, compatibility and detail of data exist. A systematic and coordinated national surveillance system for comparison purposes, trend identification and policy development is needed so that future waterborne disease outbreaks can be avoided.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".