Vector-borne Viruses in Ungulates in Ontario, Canada: Distribution and Risk of Orbivirus Establishment
Bibliographic record
Abstract
The purpose of this thesis was to investigate the potential risk posed by vector-borne pathogens to Ontario’s wildlife and livestock populations, in particular, epizootic hemorrhagic disease viruses (EHDV) and bluetongue viruses (BTV). Ontario lacks information describing the prevalence and distribution of certain vectors and pathogens despite the imminent threat vector-borne pathogens may pose to wildlife and livestock populations with their northward spread facilitated by changing climatic conditions. A retrospective analysis was performed using post-mortem findings and diagnoses for wild cervids from Ontario and Nunavut over a 27-year period to provide a long-term outlook of detected diseases and potential health threats. The most common causes of morbidity and mortality were noninfectious. Deaths attributed to infectious diseases were most often bacterial in origin. Viral vector-borne pathogens were rarely documented. We documented the first cases of EHDV (serotype 2) in free-ranging white-tailed deer in southern Ontario in 2017. Then, we sought to characterize Culicoides vector abundance and distribution, as well as assess transmission of EHDV and BTV in livestock, and BTV, EHDV, West Nile virus (WNV), eastern equine encephalitis virus (EEEV), Powassan virus (POWV) and heartland virus from free-ranging and captive cervids across Ontario for two consecutive field seasons. From June-October of 2017-2018 LED light suction traps were placed on farms and in natural areas across southern Ontario, and all Culicoides vectors collected were taxonomically identified. A total of 33,905 Culicoides spp. were collected, encompassing 14 species from seven subgenera and one species group. Culicoides sonorensis, a known vector of EHDV and BTV, was collected both years. Additionally, C. kibunensis and C. baueri were collected both years and these represent new records for Ontario, with C. baueri representing a new species record for Canada. Blood samples from 349 livestock and 217 cervids were collected from 2016 to 2019. Fifteen (9.0%) cattle were seropositive for EHDV-serotype 2. Nine (4.2%) cervids were seropositive for flaviviruses; three were confirmed as WNV, three as EEEV, and one as POWV. Collectively, these results on vector and arthropod-borne virus abundance and distribution will contribute to the development of management strategies for safeguarding Ontario livestock and wildlife populations.
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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 | 0.000 |
| 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 | 0.000 |
| 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".