Associations between pathogen-specific cases of clinical mastitis and somatic cell count patterns

Area of Science:

• Veterinary Medicine
• Animal Science
• Dairy Science

Background:

• Clinical mastitis (CM) is a significant concern in dairy herds, impacting animal welfare and milk production.
• Somatic cell count (SCC) is a key indicator of udder inflammation, but its interpretation often relies on lactation averages.
• Understanding the dynamics of SCC during lactation may provide more nuanced insights into CM etiology.

Purpose of the Study:

• To investigate associations between specific pathogen-caused CM and SCC patterns during lactation.
• To compare the predictive value of SCC patterns versus lactation average SCC for CM.
• To determine if SCC patterns can differentiate between various mastitis-causing pathogens.

Main Methods:

• Utilized data from 274 Dutch dairy herds over 18 months, including 245,595 SCC test-day records from 19,733 cows.
• Defined SCC patterns based on three or five consecutive test-day records, differentiating short/long peaks and recovery.
• Applied logistic regression to analyze associations between SCC patterns and pathogen-specific CM.

Main Results:

• SCC patterns during lactation were as accurate, or more accurate, than lactation average SCC (>200,000 cells/mL) in predicting overall CM.
• Specific SCC patterns were associated with distinct pathogens: short peaks with *E. coli*, long increases with *Staphylococcus aureus*.
• *Streptococcus dysgalactiae* and *Streptococcus uberis* showed less clear associations with defined SCC patterns.

Conclusions:

• SCC pattern analysis offers a more precise method for predicting and potentially diagnosing CM compared to traditional lactation averages.
• Distinct SCC dynamic patterns can aid in identifying the causative pathogen of clinical mastitis.
• Further research may refine pattern definitions for pathogens like *Streptococcus* species.