An Evaluation of Rabies Vaccination Rates among Canines and Felines Involved in Biting Incidents within the Wellington–Dufferin–Guelph Public Health Department
Bibliographic record
Abstract
The objectives of this study were to determine the rate of animal bite incidents occurring in the human population of a local health department, and to determine the proportion of these canines and felines that were not up to date on their rabies vaccination at the time the incident occurred. Data were obtained from animal bite incidents reported to Wellington-Dufferin-Guelph Public Health during 2010 and 2011. Descriptive statistics of 718 eligible reports revealed the average rate of animal biting was 1.55 bites per 1000 residents per year. Approximately 54% of these animals were vaccinated against rabies, 32% were not up to date with their rabies vaccination, and the remaining 14.5% were of unknown status. The unit of analysis was the municipality, and the four outcomes of interest were: (i) number of animal bite incidents per 1000 residents, (ii) number of dog bite incidents per 1000 residents, (iii) proportion of animals involved in bite incidents that were not up to date with their rabies vaccination, and (iv) proportion of dogs that were not up to date. Associations between the outcomes and selected demographic variables were investigated using regression analysis. The number of veterinary clinics per 10,000 residents, and whether the municipality was urban or rural were identified as significant predictors for the number of animal bites per 1000 residents, and the number of dog bites. There were no significant predictors for the proportion of unvaccinated animals or dogs. Spatial clustering and the location of spatial clusters were assessed using the empirical Bayes index and spatial scan test. This analysis identified five municipalities within the health department that have a high rate of biting incidents and a high proportion of animals that were not up to date on their rabies vaccination. Such municipalities are ideal for targeted educational campaigns regarding the importance of vaccination in pets.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".