Using Risk Factor Weighting to Target and Create Effective Public Health Policy for Campylobacteriosis Prevention in Ontario, Canada
Bibliographic record
Abstract
Campylobacter is one of the major causes of foodborne illness globally, making prevention of Campylobacter infections a significant public health concern. Factors such as under-reporting and the low dose required to cause illness make surveillance and control of food-acquired campylobacteriosis challenging. A literature review was conducted to identify articles that included relevant information about the causes of foodborne illness, transmission of Campylobacter, specific risk factors associated with food-acquired Campylobacter infection and reported numbers of cases of Campylobacter. The majority of studies determine that specific demographic groups are at a higher risk for contracting foodborne illness, with age, gender and location being the most significant factors. Food-acquired campylobacteriosis accounts for up 74 to 85% of total cases, with poultry being the number one contributing vehicle. Location of food-acquired Campylobacter infection differs between countries. In Ontario, the majority of food-acquired campylobacteriosis cases are attributed to food prepared in the home. A risk factor diagram shows the source of Campylobacter organisms and the locations where people are exposed. It then shows causes of food-acquired Campylobacter infection, dividing them into human and non-human factors. Human factors are the major contributing causes of Campylobacter infection in people. Targeted policies should be developed which target these factors and address the specific groups that are at a higher risk for foodborne illness. Policy initiatives that focus on consumer level human factors will have the greatest impact on campylobacteriosis prevention. Further research needs to be conducted to determine the proportion of foodborne illness which can be attributed to specific risk factors and why consumers and food handlers do not follow proper procedures for minimizing exposure to Campylobacter organism. Targeted policies can provide a more cost-effective way to help prevent further cases of Campylobacter infection as well as improve disease surveillance.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 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) | 0.006 | 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".