Descriptive epidemiologic study of disease associated with influenza virus infections during three epidemics in horses
Bibliographic record
Abstract
OBJECTIVE: To describe 3 epidemics of respiratory tract disease caused by influenza virus infections in a large population of horses. DESIGN: Cross-sectional and prospective longitudinal observational studies. ANIMALS: All horses stabled at a Thoroughbred racetrack. PROCEDURES: During a 3-year period, descriptive information was collected as horses arrived at the racetrack and throughout race meetings. Routine observations and physical examinations were used to classify horses' disease status. Cause of epidemics was established by use of serologic testing and identification of influenza virus in nasal secretions. RESULTS: An epidemic of respiratory tract disease caused by influenza virus infections was identified during each year of the study. Attack rates of infectious upper respiratory tract disease (IURD) ranged from 16 to 28%. Incidence of disease caused by influenza virus infections during racing seasons in the second and third years was 27 and 37 cases/1,000 horses/mo, respectively. Physical distributions of stall locations revealed that affected horses were stabled throughout the population; horses affected later in epidemics were often clustered around horses affected earlier. Mucopurulent nasal discharge and coughing were observed in 83 and 62% of horses with IURD, respectively. Median duration of clinical disease was 11 days. Serologic testing was the most sensitive method used to detect influenza virus infections; 76% of affected horses seroconverted to influenza virus. CONCLUSIONS AND CLINICAL RELEVANCE: Epidemics of IURD were observed annually in association with influenza virus infections. Few precautions were taken to limit spread of infection. Preventing or decreasing the likelihood of exposure and improving immunity in the population could substantially decrease risk of disease in similar 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".