The Economic Impact of Infectious Bronchitis on the Canadian Poultry Industry
Bibliographic record
Abstract
Infectious bronchitis is a common, highly contagious, acute, and economically important viral disease of chickens caused by infectious bronchitis virus (IBV), a gammacoronavirus. It affects the respiratory system, reproductive organs, and kidneys. Morbidity is 100%, and mortality can go well up to 30%, while egg production drops by up to 50% or more depending upon secondary infection by bacterial pathogens. Emerging IBV variants have led to outbreaks in vaccinated flocks due to a lack of cross-protective immunity, which represents a concern for producers. It is imperative that we assess the economic impact of IBV on the Canadian poultry industry to make important decisions on control and mitigation. I hypothesized that vaccination to prevent infectious bronchitis (IB) in poultry layers would have net positive economic benefits for Canadian poultry producers. A multiple scenario framework with Monte Carlo simulation and benefit-cost analysis was applied. The economic impact of IB on layer farms in Canada was examined by setting up models of Canadian layer poultry farms using data from Agriculture and Agri-Food Canada, scientific papers, the internet, and industry sources to perform simulations for various revenue classes across a range of IBV infection scenarios while considering possible control and prevention options. The results show that the impact of IB outbreaks on Canadian poultry industry is estimated to be around 207 billion CAD annually. The high benefit-cost ratios (5-9) from adopting IB vaccines suggest that vaccination as a preventive strategy would be highly cost effective. The study demonstrated the value of vaccination as a preventive or mitigation strategy against potential losses due to IBV. Understanding the extent of economic losses IB outbreaks cause to layer producers would inform the development of timely and cost-effective disease control and preventive measures in order to minimize the impact of IB on egg and chicken production.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".