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Abstract Bovine respiratory disease (BRD) causes significant economic losses to the feedlot industry due to decreased production and increased costs associated with treatment. This study aimed to assess the impacts of BRD on performance, carcass traits, and economic outcomes defined using four BRD diagnosis methods: number of BRD treatments an animal received, pleural lesions at slaughter, lung lesions at slaughter, and clinical BRD status defined using both treatment records and lung and pleural lesions. Crossbred steers (n = 898), with an initial body weight of 432 kg (± SD 51), were followed from feedlot entry to slaughter. Veterinary treatment records were collected and lungs scored at slaughter for lesions indicative of BRD. There was an 18% morbidity rate and a 2.1% BRD mortality rate, with an average net loss of AUD$1,647.53 per BRD mortality. Animals treated ≥3 times for BRD had 39.6 kg lighter carcasses at slaughter and returned an average of AUD$384.97 less compared to animals never treated for BRD (P < 0.001). Animals with severe lung lesions at slaughter grew 0.3 kg/d less, had 14.3 kg lighter carcasses at slaughter, and returned AUD$91.50 less than animals with no lung lesions (P < 0.001). Animals with subclinical and clinical BRD had 16.0 kg and 24.1 kg lighter carcasses, respectively, and returned AUD$67.10 and AUD$213.90 less at slaughter, respectively, compared to healthy animals that were never treated with no lesions (P < 0.001). The severity of BRD based on the number of treatments an animal received and the severity of lung and pleural lesions reduced animal performance, carcass weight and quality, and economic returns. Subclinical BRD reduced animal performance and economic returns compared to healthy animals; however, subclinical animals still had greater performance than animals with clinical BRD. This information can be used to plan for strategic investments aimed at reducing the impacts of BRD in feedlot cattle such as improved detection methods for subclinical animals with lesions at slaughter and BRD treatment protocols.

Bovine respiratory disease (BRD) is a major health problem within the global cattle industry. This disease has a complex aetiology, with viruses playing an integral role. In this study, metagenomics was used to sequence viral nucleic acids in the nasal swabs of BRD-affected cattle. The viruses detected included those that are well known for their association with BRD in Australia (bovine viral diarrhoea virus 1), as well as viruses known to be present but not fully characterised (bovine coronavirus) and viruses that have not been reported in BRD-affected cattle in Australia (bovine rhinitis, bovine influenza D, and bovine nidovirus). The nasal swabs from a case–control study were subsequently tested for 10 viruses, and the presence of at least one virus was found to be significantly associated with BRD. Some of the more recently detected viruses had inconsistent associations with BRD. Full genome sequences for bovine coronavirus, a virus increasingly associated with BRD, and bovine nidovirus were completed. Both viruses belong to the Coronaviridae family, which are frequently associated with disease in mammals. This study has provided greater insights into the viral pathogens associated with BRD and highlighted the need for further studies to more precisely elucidate the roles viruses play in BRD.

Abstract Bovine respiratory disease (BRD) is the most significant disease affecting feedlot cattle. Indicators of BRD often used in feedlots such as visual signs, rectal temperature, computer-assisted lung auscultation (CALA) score, the number of BRD treatments, presence of viral pathogens, viral seroconversion, and lung damage at slaughter vary in their ability to predict an animal’s BRD outcome, and no studies have been published determining how a combination of these BRD indicators may define the number of BRD disease outcome groups. The objectives of the current study were (1) to identify BRD outcome groups using BRD indicators collected during the feeding phase and at slaughter through latent class analysis (LCA) and (2) to determine the importance of these BRD indicators to predict disease outcome. Animals with BRD (n = 127) were identified by visual signs and removed from production pens for further examination. Control animals displaying no visual signs of BRD (n = 143) were also removed and examined. Blood, nasal swab samples, and clinical measurements were collected. Lung and pleural lesions indicative of BRD were scored at slaughter. LCA was applied to identify possible outcome groups. Three latent classes were identified in the best model fit, categorized as non-BRD, mild BRD, and severe BRD. Animals in the mild BRD group had a higher probability of having visual signs of BRD compared with non-BRD and severe BRD animals. Animals in the severe BRD group were more likely to require more than 1 treatment for BRD and have ≥40 °C rectal temperature, ≥10% total lung consolidation, and severe pleural lesions at slaughter. Animals in the severe BRD group were also more likely to be naïve at feedlot entry and the first BRD pull for Bovine Viral Diarrhoea Virus, Bovine Parainfluenza 3 Virus, and Bovine Adenovirus and have a positive nasal swab result for Bovine Herpesvirus Type 1 and Bovine Coronavirus. Animals with severe BRD had 0.9 and 0.6 kg/d lower overall ADG (average daily gain) compared with non-BRD animals and mild BRD animals (P < 0.001). These results demonstrate that there are important indicators of BRD severity. Using this information to predict an animal’s BRD outcome would greatly enhance treatment efficacy and aid in better management of animals at risk of suffering from severe BRD.

Bovine Respiratory Disease (BRD) is the leading cause of morbidity and mortality in Australian feedlot cattle. Diagnosis for BRD is based on visual scoring of illness and the use of rectal temperature above a defined level to trigger treatment protocols. These methods often have a low accuracy at diagnosing BRD. Blood metabolomics monitors alterations in small metabolites in the body and can be used to indicate the presence of disease. The aim of the current study was to search for biomarkers for BRD and develop alternate diagnosis methods for BRD using the blood metabolome profile of feedlot steers. Visually BRD affected (n = 148) and visually healthy (n = 152) steers were removed from their group pens for clinical assessment and blood sampling for metabolomics analysis. Lung lesions indicative of BRD were scored for all trial animals upon slaughter. A non-targeted metabolomics approach based on nuclear magnetic resonance (NMR) spectrometry was used to search for blood biomarkers using classification and regression trees. The data were split into training and validation datasets for model development. Visual diagnosis (VD), visual + clinical diagnosis (VCD; visually sick and elevated rectal temperature or lung auscultation score), and lung lesion diagnosis (LLD; lung consolidation ≥ 10% or pleurisy score ≥ 2) were used as reference diagnosis methods for BRD. Metabolomics demonstrated a high accuracy at detecting BRD in the validation dataset when using the VD (Acc=0.85, Se=0.82, SP = 0.87) and VCD (Acc=0.81, Se=0.88, SP = 0.74), but was less accurate at detecting animals defined as sick using the LLD (Acc=0.74, Se=0.38, SP = 0.89) (Table 1). The models selected nine metabolites important in differentiating sick and healthy animals. The results suggest the blood metabolome is a useful indicator of BRD status and could therefore be used for confirmation of BRD in feedlot cattle.