Serologic Evidence of Arthropod-Borne Virus Infections in Wild and Captive Ruminants in Ontario, Canada
Bibliographic record
Abstract
Arthropod-borne viruses (arboviruses) are globally widespread, and their transmission cycles typically involve numerous vertebrate species. Serologic testing of animal hosts can provide a routine surveillance approach to monitoring animal disease systems, can provide a surveillance alternative to arthropod testing and human case reports, and may augment knowledge of epizootiology. Wild and captive ruminants represent good candidate sentinels to track geographic distribution and prevalence of select arboviruses. They often are geographically widespread and abundant, inhabit areas shared by humans and domestic animals, and are readily fed on by various hematophagous arthropod vectors. Ontario, Canada, is home to high densities of coexisting humans, livestock, and wild cervids, as well as growing numbers of arthropod vectors because of the effects of climate change. We collected blood samples from 349 livestock (cattle/sheep) and 217 cervids (wild/farmed/zoo) in Ontario (2016-2019) to assess for antibodies to zoonotic and agriculturally important arboviruses. Livestock sera were tested for antibodies to bluetongue virus (BTV) and epizootic hemorrhagic disease virus (EHDV). Sera from cervids were tested for antibodies to BTV, EHDV, West Nile virus (WNV), eastern equine encephalitis virus (EEEV), Powassan virus (POWV), and heartland virus (HRTV). Fifteen (9.0%) cattle were seropositive for EHDV-serotype 2. Nine (4.2%) cervids were seropositive for arboviruses; three confirmed as WNV, three as EEEV, and one as POWV. All animals were seronegative for BTV and HRTV. These results reveal low seroprevalence of important agricultural, wildlife, and zoonotic pathogens and underline the need for continued surveillance in this and other regions in the face of changing environmental conditions.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".