A decision support system based on disease scoring enables dairy farmers to proactively improve herd health

Decision support systems (DSSs) enable dairy farmers to make informed and timely decisions on herd health management. However, the lack of a disease scoring system by category and severity limits the application of this approach. In this study, we developed an innovative approach to dairy herd health management by establishing a novel scoring system for dairy herd health management aimed at providing a more nuanced understanding of disease impact. For this purpose, we retrieved 5-year data from 2 558 disease diary records of 798 primiparous and multiparous cows housed on a Czech farm and classified 125 production diseases into six categories, namely lameness, mastitis, postpartum diseases, digestive system, reproductive diseases and other diseases. Based on this metric, we developed a data-driven DSS for farm management. Using this DSS, we identified markers of disease categories for efficient veterinary monitoring on dairy farms. This DSS highlighted a decreasing trend of average monthly disease scores, yet the prevalence of postpartum and other diseases increased during the same period, due to changes in reproduction management within the herd. These findings underscore the need for data-driven targeted interventions for promoting the herd health. Therefore, our scoring model not only provides a comprehensive framework for dairy herd health monitoring and improvement but also advances dairy farming by providing a decision support system easily applicable to dairy farms based on available data recorded in disease diaries.