Prevalence of antibodies to Bovine Leukemia virus, Neospora caninum and risk factors, and biosecurity practices in beef cow-calf herds in Canada.
Bibliographic record
Abstract
A total of 4,778 cows from 179 herds were tested for antibodies to N. caninum using a commercially available ELISA. Neospora caninum herd-level seroprevalence ranged from 25.0% to 75.9% (a herd was considered positive with ≥ 2 cows testing positive). The true cow prevalence was estimated as 5.2% (95% CI= 4.6 – 5.8). "Pre-calving use of dry lots," "separation of cow-calf pair from other cows after calving," "use of standing water in summer," "use of running water in winter," "feeding heifers with manure handling equipment," "abortion and stillbirths left for canids" and "number of sightings of wild canids per year (categorized into three categories: less than 10 times per year, 11 – 25 times per year, and greater than 26 times per year) were positively associated with herd serological status. However, "washing boots between visits to livestock farms" was negatively associated with serological status. These 8 variables were included in a multivariable logistic regression model. Province and herd size were considered potential confounders and kept in the model regardless of significance. Only 4 variables remained significant in the final model. Risk factors associated with prevalence included the use of dry lots/corrals as pre-calving area (OR=2.8; 95% CI =1.3 – 6.2), the use of natural standing water in summer (OR=3.2; 95%CI=1.31 – 8.0), and leaving abortions/stillbirths for dogs or wild canids (OR=2.5; 95%CI=1.0 – 5.9). As the frequency of sighting coyotes and foxes increased so did herd seroprevalence to N. caninum. Risk factors suggested the likely role of horizontal transmission in the transmission of N. caninum in these beef cow-calf herds. Beef herd managers might consider biosecurity practices such as preventing the access of wild canids to fetuses and stillbirths thereby preventing pasture contamination and controlling contamination of water source with oocyst of N. caninum thereby reducing chances of infection. A herd was considered positive for Bovine leukemia virus (BLV) if ≥ 1 animal tested positive. Estimates of cow-level seroprevalence was 1.01% (95% CI= 0.73% – 1.29%) while herd seroprevalence was 12.4% (95% CI= 7.57 – 17.23). Potential risk factors examined for BLV transmission included the use of blade or surgical castration without disinfection between animals, using gouger and saw dehorning methods, multi-use of common rectal sleeve between cows without disinfection and the use of communal pasture where mating occurred. No associations existed between potential risk factors and seropositivity to BLV because the number of herds testing positive to BLV were too few to find any association. However, management practices observed in this study may have the potential to transmit infections. Lapses in biosecurity practices identified were addition of new animals to the herds (73.7%, 132/179), the use of communal grazing (24.0% (43/179) of herds using with 28% (12/43) using more than one communal pasture where mating occurred (93%, 40/43) with bulls from other herds. During communal grazing, contact herds ranged between 1 and 25 (mean = 7.4). Large herds (≥111) animals were more likely to use communal pasture compared to medium sized or small herds (≤46) (P<0.01).
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 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".