Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival
Bovine respiratory disease (BRD) is the leading cause of morbidity in feedlot cattle. The ability to accurately identify the expected BRD risk of cattle would allow managers to detect high-risk animals more frequently. Five classification models were built and evaluated towards predicting the expect...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Pathogens |
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| Online Access: | https://www.mdpi.com/2076-0817/11/4/442 |
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| author | Hector A. Rojas Brad J. White David E. Amrine Robert L. Larson |
| author_facet | Hector A. Rojas Brad J. White David E. Amrine Robert L. Larson |
| author_sort | Hector A. Rojas |
| collection | DOAJ |
| description | Bovine respiratory disease (BRD) is the leading cause of morbidity in feedlot cattle. The ability to accurately identify the expected BRD risk of cattle would allow managers to detect high-risk animals more frequently. Five classification models were built and evaluated towards predicting the expected BRD risk (high/low) of feedlot cattle within the first 45 days on feed (DOF) and incorporate an economic analysis to determine the potential health cost advantage when using a predictive model compared with standard methods. Retrospective data from 10 U.S. feedlots containing 1733 cohorts representing 188,188 cattle with known health outcomes were classified into high- (≥15% BRD morbidity) or low- (<15%) BRD risk in the first 45 DOF. Area under the curve was calculated from the test dataset for each model and ranged from 0.682 to 0.789. The economic performance for each model was dependent on the true proportion of high-risk cohorts in the population. The decision tree model displayed a greater potential economic advantage compared with standard procedures when the proportion of high-risk cohorts was ≤45%. Results illustrate that predictive models may be useful at delineating cattle as high or low risk for disease and may provide economic value relative to standard methods. |
| first_indexed | 2024-03-09T10:31:38Z |
| format | Article |
| id | doaj.art-f20be56c82d049cda0b3ecf93efb8f8d |
| institution | Directory Open Access Journal |
| issn | 2076-0817 |
| language | English |
| last_indexed | 2024-03-09T10:31:38Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Pathogens |
| spelling | doaj.art-f20be56c82d049cda0b3ecf93efb8f8d2023-12-01T21:17:50ZengMDPI AGPathogens2076-08172022-04-0111444210.3390/pathogens11040442Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post ArrivalHector A. Rojas0Brad J. White1David E. Amrine2Robert L. Larson3Beef Cattle Institute, Kansas State University, Manhattan, KS 66506, USABeef Cattle Institute, Kansas State University, Manhattan, KS 66506, USABeef Cattle Institute, Kansas State University, Manhattan, KS 66506, USABeef Cattle Institute, Kansas State University, Manhattan, KS 66506, USABovine respiratory disease (BRD) is the leading cause of morbidity in feedlot cattle. The ability to accurately identify the expected BRD risk of cattle would allow managers to detect high-risk animals more frequently. Five classification models were built and evaluated towards predicting the expected BRD risk (high/low) of feedlot cattle within the first 45 days on feed (DOF) and incorporate an economic analysis to determine the potential health cost advantage when using a predictive model compared with standard methods. Retrospective data from 10 U.S. feedlots containing 1733 cohorts representing 188,188 cattle with known health outcomes were classified into high- (≥15% BRD morbidity) or low- (<15%) BRD risk in the first 45 DOF. Area under the curve was calculated from the test dataset for each model and ranged from 0.682 to 0.789. The economic performance for each model was dependent on the true proportion of high-risk cohorts in the population. The decision tree model displayed a greater potential economic advantage compared with standard procedures when the proportion of high-risk cohorts was ≤45%. Results illustrate that predictive models may be useful at delineating cattle as high or low risk for disease and may provide economic value relative to standard methods.https://www.mdpi.com/2076-0817/11/4/442bovine respiratory diseasepredictive modelingeconomic analysis |
| spellingShingle | Hector A. Rojas Brad J. White David E. Amrine Robert L. Larson Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival Pathogens bovine respiratory disease predictive modeling economic analysis |
| title | Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival |
| title_full | Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival |
| title_fullStr | Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival |
| title_full_unstemmed | Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival |
| title_short | Predicting Bovine Respiratory Disease Risk in Feedlot Cattle in the First 45 Days Post Arrival |
| title_sort | predicting bovine respiratory disease risk in feedlot cattle in the first 45 days post arrival |
| topic | bovine respiratory disease predictive modeling economic analysis |
| url | https://www.mdpi.com/2076-0817/11/4/442 |
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