Determination of value of bovine respiratory disease control using a remote early disease identification system compared with conventional methods of metaphylaxis and visual observations

Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview

Despite significant advances in vaccination strategies and antibiotic therapy, bovine respiratory disease (BRD) continues to be the leading disease affecting the global cattle industry. The etiology of BRD is complex, often involving multiple microbial agents, which lead to intricate interactions between the host immune system and pathogens during various beef production stages. These interactions present environmental, social, and geographical challenges. Accurate diagnosis is essential for effective disease management. Nevertheless, correct identification of BRD cases remains a daunting challenge for animal health technicians in feedlots. In response to current regulations, there is a growing interest in refining clinical diagnoses of BRD to curb the overuse of antimicrobials. This shift marks a pivotal first step toward establishing a structured diagnostic framework for this disease. This review article provides an update on recent developments and future perspectives in clinical diagnostics and prognostic techniques for BRD, assessing their benefits and limitations. The methods discussed include the evaluation of clinical signs and animal behavior, biomarker analysis, molecular diagnostics, ultrasound imaging, and prognostic modeling. While some techniques show promise as standalone diagnostics, it is likely that a multifaceted approach-leveraging a combination of these methods-will yield the most accurate diagnosis of BRD.

Influence of the At-Arrival Host Transcriptome on Bovine Respiratory Disease Incidence during Backgrounding

Bovine respiratory disease (BRD) remains the leading disease within the U.S. beef cattle industry. Marketing decisions made prior to backgrounding may shift BRD incidence into a different phase of production, and the importance of host gene expression on BRD incidence as it relates to marketing strategy is poorly understood. Our objective was to compare the influence of marketing on host transcriptomes measured on arrival at a backgrounding facility on the subsequent probability of being treated for BRD during a 45-day backgrounding phase. This study, through RNA-Seq analysis of blood samples collected on arrival, evaluated gene expression differences between cattle which experienced a commercial auction setting (AUCTION) versus cattle directly shipped to backgrounding from the cow–calf phase (DIRECT); further analyses were conducted to determine differentially expressed genes (DEGs) between cattle which remained clinically healthy during backgrounding (HEALTHY) versus those that required treatment for clinical BRD within 45 days of arrival (BRD). A profound difference in DEGs (n = 2961) was identified between AUCTION cattle compared to DIRECT cattle, regardless of BRD development; these DEGs encoded for proteins involved in antiviral defense (increased in AUCTION), cell growth regulation (decreased in AUCTION), and inflammatory mediation (decreased in AUCTION). Nine and four DEGs were identified between BRD and HEALTHY cohorts in the AUCTION and DIRECT groups, respectively; DEGs between disease cohorts in the AUCTION group encoded for proteins involved in collagen synthesis and platelet aggregation (increased in HEALTHY). Our work demonstrates the clear influence marketing has on host expression and identified genes and mechanisms which may predict BRD risk.

Technological Tools for the Early Detection of Bovine Respiratory Disease in Farms

Simple Summary

The inclusion of remote automatic systems that use continuous learning technology are of great interest in precision livestock cattle farming, since the average size of farms is increasing while time for individual observation is decreasing. Bovine respiratory disease is a main concern in both fattening and heifer rearing farms due to its impact on antibiotic use, loss of performance, mortality, and animal welfare. Much scientific literature has been published regarding technologies for continuous learning and monitoring of cattle’s behavior and accurate correlation with health status, including early detection of bovine respiratory disease. This review summarizes the up-to-date technologies for early diagnosis of bovine respiratory disease and discusses their advantages and disadvantages under practical conditions.

Abstract

Classically, the diagnosis of respiratory disease in cattle has been based on observation of clinical signs and the behavior of the animals, but this technique can be subjective, time-consuming and labor intensive. It also requires proper training of staff and lacks sensitivity (Se) and specificity (Sp). Furthermore, respiratory disease is diagnosed too late, when the animal already has severe lesions. A total of 104 papers were included in this review. The use of new advanced technologies that allow early diagnosis of diseases using real-time data analysis may be the future of cattle farms. These technologies allow continuous, remote, and objective assessment of animal behavior and diagnosis of bovine respiratory disease with improved Se and Sp. The most commonly used behavioral variables are eating behavior and physical activity. Diagnosis of bovine respiratory disease may experience a significant change with the help of big data combined with machine learning, and may even integrate metabolomics as disease markers. Advanced technologies should not be a substitute for practitioners, farmers or technicians, but could help achieve a much more accurate and earlier diagnosis of respiratory disease and, therefore, reduce the use of antibiotics, increase animal welfare and sustainability of livestock farms. This review aims to familiarize practitioners and farmers with the advantages and disadvantages of the advanced technological diagnostic tools for bovine respiratory disease and introduce recent clinical applications.

Construction of a conceptual framework for assessment of health-related quality of life in calves with respiratory disease

Bovine respiratory disease (BRD) is one of the most prevalent diseases affecting beef and dairy calves worldwide, with implications for lifetime productivity, antimicrobial use and animal welfare. Our objective was to construct a conceptual framework for assessment of health-related quality of life (HRQL) in calves with respiratory disease, based on indicators suitable for direct pen-side visual observation. Health-related quality of life measures aim to evaluate the subjective experience of the animal rather than any related pathology. A conceptual framework graphically represents the concepts to be measured and the potential relationships between them. A multistage, mixed method approach involving diverse data sources, collection methods and stakeholders was applied to promote comprehensiveness, understanding and validity of findings. A scoping review was conducted to identify, characterize and collate evidence of behavioural indicators of BRD. The indicators identified were mapped against the principal attributes of five prominent animal welfare assessment frameworks to appraise their correspondence with different characterizations of the dimensions of welfare. Forty-two semi-structured, individual, qualitative interviews with a purposeful sample of experienced veterinarians and stockpersons from UK, USA and Canada elicited in-depth descriptions of the visual observations of HRQL they make in diagnosing and assessing the response to treatment of calves with BRD. Verbatim interview transcripts were examined using inductive thematic analysis. Respondents provided insights and understanding of indicators of HRQL in BRD such as interaction with feed source, hair coat condition, specific characteristics of eye appearance, eye contact, rumen fill and stretching (pandiculation). In an on-farm pilot study to assess the value of potential HRQL behavioural indicators, there was a moderate positive correlation between behaviour and clinical scores (r_s = 0.59) across the 5 days preceding veterinary treatment for BRD. Interestingly, the behaviours evaluated were observed a median of 1.0 (interquartile range: 1.0-3.5) days before clinical indicators used in the scoring system. The proposed conceptual framework for assessment of HRQL features 23 putative indicators of HRQL distributed across two interrelated domains - clinical signs and behavioural expressions of emotional well-being. It has potential applications to inform the development of new HRQL measures such as structured questionnaires and automated sensor technologies.

Bovine Respiratory Disease Diagnosis: What Progress Has Been Made in Clinical Diagnosis?

Bovine respiratory disease (BRD) complex is a worldwide health problem in cattle and is a major reason for antimicrobial use in young cattle. Several challenges may explain why it is difficult to make progress in the management of this disease. This article defines the limitation of BRD complex nomenclature, which may not easily distinguish upper versus lower respiratory tract infection and infectious bronchopneumonia versus other types of respiratory diseases. It then discusses the obstacles to clinical diagnosis and reviews the current knowledge of readily available diagnostic test to reach a diagnosis of infectious bronchopneumonia.

A systematic review and network meta-analysis of injectable antibiotic options for the control of bovine respiratory disease in the first 45 days post arrival at the feedlot

We conducted a systematic review and network meta-analysis to determine the comparative efficacy of antibiotics used to control bovine respiratory disease (BRD) in beef cattle on feedlots. The information sources for the review were: MEDLINE®, MEDLINE In-Process and MEDLINE® Daily, AGRICOLA, Epub Ahead of Print, Cambridge Agricultural and Biological Index, Science Citation Index, Conference Proceedings Citation Index - Science, the Proceedings of the American Association of Bovine Practitioners, World Buiatrics Conference, and the United States Food and Drug Administration Freedom of Information New Animal Drug Applications summaries. The eligible population was weaned beef cattle raised in intensive systems. The interventions of interest were injectable antibiotics used at the time the cattle arrived at the feedlot. The outcome of interest was the diagnosis of BRD within 45 days of arrival at the feedlot. The network meta-analysis included data from 46 studies and 167 study arms identified in the review. The results suggest that macrolides are the most effective antibiotics for the reduction of BRD incidence. Injectable oxytetracycline effectively controlled BRD compared with no antibiotics; however, it was less effective than macrolide treatment. Because oxytetracycline is already commonly used to prevent, control, and treat BRD in groups of feedlot cattle, the use of injectable oxytetracycline for BRD control might have advantages from an antibiotic stewardship perspective.

A method of back-calculating the log odds ratio and standard error of the log odds ratio from the reported group-level risk of disease

In clinical trials and observational studies, the effect of an intervention or exposure can be reported as an absolute or relative comparative measure such as risk difference, odds ratio or risk ratio, or at the group level with the estimated risk of disease in each group. For meta-analysis of results with covariate adjustment, the log of the odds ratio (log odds ratio), with its standard error, is a commonly used measure of effect. However, extracting the adjusted log odds ratio from the reported estimates of disease risk in each group is not straightforward. Here, we propose a method to transform the adjusted probability of the event in each group to the log of the odds ratio and obtain the appropriate (approximate) standard error, which can then be used in a meta-analysis. We also use example data to compare our method with two other methods and show that our method is superior in calculating the standard error of the log odds ratio.

Whole blood transcriptomic analysis of beef cattle at arrival identifies potential predictive molecules and mechanisms that indicate animals that naturally resist bovine respiratory disease

Bovine respiratory disease (BRD) is a multifactorial disease complex and the leading infectious disease in post-weaned beef cattle. Clinical manifestations of BRD are recognized in beef calves within a high-risk setting, commonly associated with weaning, shipping, and novel feeding and housing environments. However, the understanding of complex host immune interactions and genomic mechanisms involved in BRD susceptibility remain elusive. Utilizing high-throughput RNA-sequencing, we contrasted the at-arrival blood transcriptomes of 6 beef cattle that ultimately developed BRD against 5 beef cattle that remained healthy within the same herd, differentiating BRD diagnosis from production metadata and treatment records. We identified 135 differentially expressed genes (DEGs) using the differential gene expression tools edgeR and DESeq2. Thirty-six of the DEGs shared between these two analysis platforms were prioritized for investigation of their relevance to infectious disease resistance using WebGestalt, STRING, and Reactome. Biological processes related to inflammatory response, immunological defense, lipoxin metabolism, and macrophage function were identified. Production of specialized pro-resolvin mediators (SPMs) and endogenous metabolism of angiotensinogen were increased in animals that resisted BRD. Protein-protein interaction modeling of gene products with significantly higher expression in cattle that naturally acquire BRD identified molecular processes involving microbial killing. Accordingly, identification of DEGs in whole blood at arrival revealed a clear distinction between calves that went on to develop BRD and those that resisted BRD. These results provide novel insight into host immune factors that are present at the time of arrival that confer protection from BRD.

Effects of transportation on cattle health and production: a review

The goal of this review is to present a concise and critical assessment of the literature related to physiologic responses in cattle that are subjected to transportation. Over two-thirds of US cattle are transported. Understanding trends in circulating physiologic parameters is an important part of mitigating the negative effects of transportation. For the producer, linking these effects after transportation to morbidity outcomes within the first 45 days on feed (i.e. especially development of bovine respiratory disease) is critical. Physiologic parameters in circulation are of primary importance and may have value for prediction of bovine respiratory disease on arrival and for the understanding of disease pathogenesis. The results of our literature survey indicated that post-transportation immune function, increased acute phase proteins, glucocorticoids, and inflammation are a pivotal starting point for understanding disease. These potential biomarkers may have utility in identifying disease for targeted therapeutics so that traditional protocols that rely heavily on metaphylaxis can be avoided. Additional research is needed to develop strategies for physiological marker identification, treatment methods, or predictive behaviors to prevent respiratory disease before and after transport. This review examines the significant deleterious effects of transportation handling and stress, and current immune system translation and non-antimicrobial mitigation strategies.

Using advanced technologies to quantify beef cattle behavior

For decades, we have relied upon visual observation of animal behavior to define clinical disease, assist in breeding selection, and predict growth performance. Limitations of visual monitoring of cattle behavior include training of personnel, subjectivity, and brevity. In addition, extensive time and labor is required to visually monitor behavior in large numbers of animals, and the prey instinct of cattle to disguise abnormal behaviors in the presence of a human evaluator is problematic. More recently, cattle behavior has been quantified objectively and continuously using advanced technologies to assess animal welfare, indicate lameness or disease, and detect estrus in both production and research settings. The current review will summarize three methodologies for quantification of cattle behavior with focus on U.S. beef production systems; 1) three-axis accelerometers that quantify physical behavior, 2) systems that document feeding and watering behavior via radio frequency, and 3) triangulation or global positioning systems to determine location and movement of cattle within a pen or pasture. Furthermore, advances in Wi-Fi and radio frequency technology have allowed many of these systems to operate remotely and in real-time and efforts are underway to develop commercial applications that may allow early detection of respiratory or other cattle diseases in the production environment. Current challenges with commercial application of technology for early disease detection include establishment of an appropriate algorithm to ensure maximum sensitivity and specificity, reliable and repeatable data collection in harsh environments, cost:benefit, and integration with traditional methodology for clinical diagnosis. Advanced technologies have also allowed cattle researchers to determine temporal variance in behavior or variability between experimental treatments. However, these data sets are typically very large and challenges exist regarding statistical analysis and reporting.