Herd-level occurrence and risk factors associated with respiratory and enteric pathogens from dairy calves in Ontario: A cross-sectional study
Bibliographic record
Abstract
This cross-sectional herd-level study aimed to determine the occurrence of and risk factors for pathogens associated with neonatal calf diarrhea (NCD) and bovine respiratory disease (BRD) on Ontario dairy farms. From April to August 2022, a convenience sample of 100 dairy farms was visited once. A questionnaire covering farm biosecurity, calving and colostrum management, preweaning nutrition, and housing was administered on-farm. At each farm visit, approximately 5 calves between 2 and 35 d old were randomly selected for fecal sampling. Furthermore, approximately 5 calves between 21 to 122 d old were randomly selected for nasopharyngeal sampling. In total, 363 fecal samples (from 83 dairy farms) and 390 nasopharyngeal swab samples (from 80 dairy farms) were collected. Fecal samples were analyzed individually using a multiplex PCR to identify bacterial and parasitic enteric pathogens. Nasopharyngeal swabs were analyzed as one pooled sample per farm using bacterial culture and real-time PCR. The most common enteric pathogens detected at herd-level were Cryptosporidium parvum (67.4%) and Escherichia coli K99+ (13.2%). The most common respiratory pathogens detected at herd-level were Pasteurella multocida (62.5%), bovine coronavirus (42.5%), and Mycoplasma bovis (21.2%). Multivariable logistic models were built to explore associations between the most common pathogens and herd-level predictors selected from the questionnaire. Herd positivity for C. parvum was positively associated with having more than 61 preweaning calves per year and feeding mainly whole milk to calves. The presence of M. bovis was positively associated with herds that combined manual and automatic milk-feeding systems, and the presence of bovine coronavirus was positively associated with having more than 98 preweaning calves during the year. Univariable Poisson regression models were built to explore the association between the most common pathogens and preweaning calf mortality. Herds that were positive for C. parvum, M. bovis, or bovine coronavirus had a greater risk of preweaning calf mortality. These results provide insights for future research on pathogens associated with NCD and BRD and offer guidance for veterinarians and dairy farmers in implementing disease control measures in dairy calf herds.
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 | 0.000 | 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".