Important Canine Zoonoses from a Public Health Perspective and the Introduction of Companion Animal Surveillance in the Prairie Provinces of Canada
Bibliographic record
Abstract
ABSTRACT Prioritizing zoonotic and/or sapronotic pathogens of domestic animal populations and initiating ongoing surveillance of such pathogens is needed in Canada. From a One Health perspective, gathering and recording more comprehensive disease data on the population of animals most closely associated with humans is extremely valuable and necessary. Therefore, the purpose of this thesis was to identify a subset of domestic canine pathogens of public health significance specific to the Prairie Provinces of Canada and to establish a framework for a companion animal surveillance initiative to the region. This research was conducted within a two- year period from September 2019 to April 2021. The first component of this research involved the creation of a comprehensive list of any pathogen historically reported in the domestic dog by reviewing several companion animal infectious disease textbooks, which resulted in 594 pathogens total. This list was then pared down to identify only those pathogens that were significant from a public health perspective in Canada and the prairies. This was accomplished using a formulated stepwise approach that pathogens only moved on to the final list if: (1) the pathogen was zoonotic/sapronotic/anthroponotic, (2) the domestic dog was involved in transmission, maintenance or detection of the pathogen, and (3) there was a level of risk for occurrence of the pathogen in Canada. Following this stepwise approach, of the initial 594 canine pathogens 84 pathogens were deemed important in Canada and the prairies from a public health perspective. A follow-up study to this research involved a prioritization exercise using experts in the field of veterinary medicine, public health, and epidemiology to identify the top 5 highest priority pathogens from the final list of 84 canine pathogens upon which to focus a companion animal surveillance program specific to the Prairie Provinces. The exercise was accomplished through a voluntary survey using a semi-quantitative ranking strategy. The resulting top 5 pathogens to come out of the exercise were: (1) Echinococcus spp. (granulosus, multilocularis), (2) MRSA, (3) Salmonella enterica, (4) MRSP, and (5) Borrelia burgdorferi. The final component of this research examined the utility of clinical veterinarians and veterinary clinics in a companion animal surveillance program. In addition, responses from clinical veterinarians were used to formulate case definitions for the top 5 highest priority pathogens intended for surveillance. Assessing dogs as sentinels for pathogens of public health concern using Lyme disease as an example was also conducted in this research chapter. Data was gathered through a voluntary survey disseminated to clinical veterinarians in the provinces of Alberta, Saskatchewan, and Manitoba. The results of this survey identified that clinical veterinarians are willing to participate in a surveillance program, that there is important in-clinic veterinary data not currently being captured from a population or disease monitoring standpoint, and that domestic dogs can serve as good sentinels for Lyme disease risk in humans, specific to the prairies. This thesis provided the foundational steps for a companion animal surveillance initiative specific to the Prairie Provinces of Canada. It identified which pathogens involving the domestic dog pose a significant public health risk in Canada and the prairies, prioritized these pathogens from highest to lowest concern using expert opinion, and established the importance of cooperation with practicing veterinarians and veterinary clinics for a companion animal surveillance program to be successful.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".