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Record W4390665323 · doi:10.3389/fcosc.2023.1294693

Coyote scat in cities increases risk of human exposure to an emerging zoonotic disease in North America

2024· article· en· W4390665323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Conservation Science · 2024
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsEchinococcus multilocularisWildlifeGeographyVeterinary medicineLivestockEnvironmental healthEcologyEchinococcosisBiologyForestryMedicineZoology

Abstract

fetched live from OpenAlex

Introduction Zoonoses associated with urban wildlife are increasingly concerning for human health and include the recent emergence of alveolar echinococcosis (AE) in North America. AE develops following infection with the tapeworm Echinococcus multilocularis . In Alberta, up to 65% of urban coyotes ( Canis latrans ) are infected with E. multilocularis , and infected scats contain eggs that can be accidentally ingested by people. Our goal was to determine the predictors of infection prevalence and intensity in coyote scats in Edmonton, Canada, and to identify the predictors of coyote scat deposition and content, especially as related to anthropogenic food sources and infrastructure. Methods To study infection prevalence and intensity, volunteers collected 269 scats, which were tested for E. multilocularis using polymerase chain reaction. We compared infection prevalence and shedding intensity by habitat and scat content. To determine predictors of scat presence and content, we used snow tracking to identify 1263 scats. We compared landscape characteristics at scats and available points, and among scats with different contents. We used negative binomial regression to predict scat abundance in city-delineated green spaces. Results 26.0% of tested scats were positive for E. multilocularis ( n = 70), and infection was twice as common as expected near compost and 1.3x more common than expected when scats contained anthropogenic food. Scats were more common than expected near other scats (80% within 1 m of scats, 27% at 11.5 m), buildings (19% at buildings, 16% at 80 m), and the camps of people experiencing homelessness (24% at camps, 20% at 60 m). Scats frequently contained fruit (52.9%), anthropogenic material (36.7%), and birdseed (16.0%), and scats containing anthropogenic material often occurred near human infrastructure, supporting a relationship between anthropogenic attractants and scat accumulation. Discussion These results suggest that abundant food sources and anthropogenic food increase coyote aggregation, increasing both scat abundance and infection rates, which in turn increases risk of exposure to zoonotic parasites for humans. Risk to humans might be reduced by preventing coyote access to anthropogenic and aggregated food sources and educating people who are likely to encounter infected soil or vegetation, including gardeners, park users, and people experiencing homelessness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.323
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it