Bovine respiratory disease (BRD) is one of the most prevalent, deadly, and costly diseases in young cattle. BRD has been recognized as a multifactorial disease caused mainly by viruses (bovine herpesvirus, BVDV, parainfluenza-3 virus, respiratory syncytial virus, and bovine coronavirus) and bacteria (Mycoplasma bovis, Pasteurella multocida, Mannheimia haemolytica and Histophilus somni). However, other microorganisms have been recognized to cause BRD. Influenza D virus (IDV) is a novel RNA pathogen belonging to the family Orthomyxoviridae, first discovered in 2011. It is distributed worldwide in cattle, the main reservoir. IDV has been demonstrated to play a role in BRD, with proven ability to cause respiratory disease, a high transmission rate, and potentiate the effects of other pathogens. The transmission mechanisms of this virus are by direct contact and by aerosol route over short distances. IDV causes lesions in the upper respiratory tract of calves and can also replicate in the lower respiratory tract and cause pneumonia. There is currently no commercial vaccine or specific treatment for IDV. It should be noted that IDV has zoonotic potential and could be a major public health concern if there is a drastic change in its pathogenicity to humans. This review summarizes current knowledge regarding IDV structure, pathogenesis, clinical significance, and epidemiology.

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.