The 2004 Edentate Species Assessment Workshop
Bibliographic record
Abstract
Zoonotic parasites are important causes of endemic and emerging human disease in northern North America and Greenland (the North), where prevalence of some parasites is higher than in the general North American population. The North today is in transition, facing increased resource extraction, globalisation of trade and travel, and rapid and accelerating environmental change. This comprehensive review addresses the diversity, distribution, ecology, epidemiology, and significance of nine zoonotic parasites in animal and human populations in the North. Based on a qualitative risk assessment with criteria heavily weighted for human health, these zoonotic parasites are ranked, in the order of decreasing importance, as follows: Echinococcus multilocularis, Toxoplasma gondii, Trichinella and Giardia, Echinococcus granulosus/canadensis and Cryptosporidium, Toxocara, anisakid nematodes, and diphyllobothriid cestodes. Recent and future trends in the importance of these parasites for human health in the North are explored. For example, the incidence of human exposure to endemic helminth zoonoses (e.g. Diphyllobothrium, Trichinella, and Echinococcus) appears to be declining, while water-borne protozoans such as Giardia, Cryptosporidium, and Toxoplasma may be emerging causes of human disease in a warming North. Parasites that undergo temperature-dependent development in the environment (such as Toxoplasma, ascarid and anisakid nematodes, and diphyllobothriid cestodes) will likely undergo accelerated development in endemic areas and temperate-adapted strains/species will move north, resulting in faunal shifts. Food-borne pathogens (e.g. Trichinella, Toxoplasma, anisakid nematodes, and diphyllobothriid cestodes) may be increasingly important as animal products are exported from the North and tourists, workers, and domestic animals enter the North. Finally, key needs are identified to better assess and mitigate risks associated with zoonotic parasites, including enhanced surveillance in animals and people, detection methods, and delivery and evaluation of veterinary and public health services.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.004 | 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; both teacher heads agree on what is shown here.
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".