Evaluating clinical mastitis in four dimensions: Definition and correlation analysis of the production, somatic cell count, clinical and pathogen severity.

Abstract

Assessing clinical mastitis (CM) severity plays a crucial role in mastitis control. The current method for assessing CM severity mainly considers clinical symptoms while a comprehensive approach is lacking. This study aims to explore CM severity in different dimensions. We collected data on 129 CM cases detected by automatic milking system (AMS) and confirmed by herdsman from three farms in Belgium (n = 2) and the Netherlands (n = 1). The CM severity was assessed in four dimensions: production (maximum relative milk loss for the inflamed and uninflamed quarters separately), somatic cell count (deviation from cow-level baseline), clinical (mild, moderate, severe clinical symptoms), and pathogen (cultures from the inflamed quarter). We explored the relations between these dimensions and examined the impact of farm, parity, and lactation stage (LS). Our findings revealed that severity dimensions were positively correlated, with correlations from 0.30 to 0.50. The strongest correlation between dimensions occurred between the production dimension in inflamed and uninflamed quarters. Severity in the somatic cell count dimension exhibited the stronger correlation with production severity for uninflamed quarters and pathogen severity compared to other dimensions, and the clinical dimension showed the strongest association with the production dimension for uninflamed quarters. Additionally, farm, parity, and LS were found to influence both the severity within certain dimensions and the interrelationships among them. These results suggest that, although CM severity scores across the four dimensions are positively correlated, clear variations exist. Combining the four scores could help to capture the full scope of CM by simultaneously assessing the severity of cases across these dimensions. Despite potential detection bias in the CM cases, our findings provide an opportunity to develop a novel CM severity scoring system that could optimize treatment decisions and promote sustainability of the dairy sector.