Host spatiotemporal overlap in a park with high endemicity of Echinococcus multilocularis
Bibliographic record
Abstract
Background There has been a spate of recent cases of human alveolar echinococcosis (AE) in Alberta, Canada. Alveolar echinococcosis is caused byEchinococcus multilocularis, which is prevalent among coyote populations and present in domestic dogs in Alberta. Methods and results Using qPCR, we estimated the seasonal fecal prevalence ofE. multilocularisin coyotes and dogs in a multiuse recreation area close to Edmonton, Alberta, where we also setup remote cameras to model seasonal changes in the overlap in temporal activity and the spatial intensity of use among coyotes, humans, and dogs, as a proxy of potential transmission. We detectedE. multilocularisin 18 of 137 wild canid feces and none in 44 dog feces. After correcting for the qPCR test’s sensitivity and specificity, we estimated at 15.7% (9.7-22.7%, 95% CrI) the true fecal prevalence for coyotes. Temporal overlap between coyotes and both humans and dogs increased in the fall and winter relative to the spring and summer. Coyote intensity of use showed seasonal variations and was higher on maintained trails and locations closer to visitor parking and at sites with high intensity of dog use. Conclusions Our results reinforce the need of an integrated approach, typical of both One-Health and Eco-Health, to park management for minimizing the likelihood of transmission where human and dog activity results in significant overlap with the one of the natural definitive hosts of zoonotic parasites.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".