Stabilizing Dog Populations and Improving Animal and Public Health Through a Participatory Approach in Indigenous Communities
Bibliographic record
Abstract
Free-roaming dog populations are a global concern for animal and human health including transmission of infectious disease (e.g. rabies, distemper and parasites), dog bite injuries/mortalities, animal welfare and adverse effects on wildlife. In Saskatchewan (SK), Canada, veterinary care is difficult to access in the remote and sparsely inhabited northern half of the province, where the population is predominately Indigenous. Even where veterinary clinics are readily available, there are important barriers such as cost, lack of transportation, unique cultural perspectives on dog husbandry and perceived need for veterinary care. We report the effects of introducing a community action plan designed to improve animal and human health, increase animal health literacy and benefit community well-being in two Indigenous communities where a dog-related child fatality recently occurred. Initial door-to-door dog demographic surveys indicated that most dogs were sexually intact (92% of 382 dogs), and few had ever been vaccinated (6%) or dewormed (6%). Approximately three animal-related injuries requiring medical care were reported in the communities per 1000 persons per year (95% CL: 1.6-6.6), and approximately 86% of 145 environmentally collected dog faecal samples contained parasites, far above levels reported in other urban or rural settings in SK. Following two subsidized spay/neuter clinics and active rehoming of dogs, parasite levels in dog faeces decreased significantly (P < 0.001), and important changes were observed in the dog demographic profile. This project demonstrates the importance of engaging people using familiar, local resources and taking a community specific approach. As well, it highlights the value of integrated, cross-jurisdictional cooperation, utilizing the resources of university researchers, veterinary personnel, public health, environmental health and community-based advocates to work together to solve complex issues in One Health. On-going surveillance on dog bites, parasite levels and dog demographics are needed to measure the long-term sustainability of benefits to dog, human and wildlife health.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".