Measuring animal exposure in Canada: Foodbook study, 2014–2015
Bibliographic record
Abstract
Animal companionship can have many physical and psychological benefits; however, animals can also be a source of zoonotic infection, including enteric illnesses; it has been estimated that in Canada, nearly 85,000 enteric illnesses due to eight pathogens occur each year related to animal contact. There is a lack of baseline data on animal-related exposures in Canada and around the world. This information is critical to inform quantitative and qualitative risk assessments to prioritize intervention efforts in public health and reduce the associated burden of enteric illness. To help address this issue and assist evaluation of the risks associated with animal contact, the Foodbook study, conducted in 2014-2015, assessed exposure to animals, animal food and animal-related venues within the last 7 days among Canadians. Data were analysed by province and territory, age group and urban/rural residency. Overall, dogs and cats were the most commonly reported animal exposures (43.3% and 31.9%, respectively). The data suggest farm animal exposure occurs primarily at a farm/barn, and to a lesser extent at other animal-related venues (e.g., petting zoos or agricultural fairs). Approximately one in 25 respondents handled raw pet food within the last 7 days; the majority of which had also been exposed to a dog (86.4%). Children aged 0-9 years reported relatively high exposure to four types of high-risk animals: rodents (5.6%), poultry (4.0%), reptiles (2.1%) and amphibians (1.8%); with the most vulnerable children aged <5 years also reporting exposure to many of these high-risk animals. These results highlight potential areas for targeted intervention that can focus on high-risk populations (e.g., young children) exhibiting potentially risky behaviour such as being exposed to certain high-risk animals, or handling pet food, treats and raw pet food diets. Additionally, these results support the need to better understand the burden of enteric illness associated with animals and their environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".