Animal‐Related Research in the Arctic With a Focus on Animal Health and Zoonotic Disease: A Scoping Review
Bibliographic record
Abstract
The Arctic is habitat for a range of animal species, many of which are consumed by Indigenous Peoples and are central to Indigenous food sovereignty. Country food (locally harvested food from the land, sea and sky) is nutritious, and harvesting country food is an important cultural activity, making understanding of potential zoonotic disease exposure an important concern for public health. The objective of this scoping review was to describe the animal-related research in the Arctic regions of Alaska, Canada and Greenland, with a focus on zoonotic pathogens in animals and humans. Overall, 3072 articles described animal-related research, with common topics including animal health, environmental contaminants in animals and animal population estimates, whereas few articles included a consideration of Indigenous Knowledges. Parasites were the most common type of zoonotic pathogens studied, with terrestrial and marine mammals the most studied species groups. Trichinella and Toxoplasma were the most commonly studied zoonotic parasites in both animals and humans. Brucella spp., Leptospira interogans and Francisella tularensis were commonly studied bacterial zoonoses in the animal health literature, whereas Clostridium botulinum (and toxin) was the most studied zoonoses in humans related to bacteria from animals. Rabies or exposure to rabies was the most common zoonotic virus studied in both animals and humans. Common objectives for both animal health and human health studies included estimating prevalence, identifying risk factors and describing morbidity or mortality. Studies estimating disease incidence or evaluating the effectiveness of interventions were uncommon. Climate change considerations were increasingly being included as a study component over time. In conclusion, although there is a substantive body of research on animal and zoonotic health in these regions of the Arctic, further engagement with Indigenous Knowledges and more focused study on disease prevention and intervention are crucial for safeguarding both wildlife and human health in this unique environment.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".