Ultimately, disease control programs have one goal: to predict disease and take measures in order to prevent disease from occurring. According to Dr. Martin Green, Professor of Cattle Health & Epidemiology at the University of Nottingham, more can be done to prevent mastitis. Green spoke on the subject at the World Buiatrics Congress in Dublin in July.
Early in his presentation, Green discussed current approaches to mastitis control, but pointed out that most used are reactive, rather than prospective. “Whilst automation has increased and improved, and in many developed dairy nations, classical contagious mastitis pathogen are now at low prevalence, there remains a reliance on generic control strategies that originated in the 1960s,” Green wrote in his presentation report.
In particular, he spoke about current on-farm investigations conducted by veterinarians and advisors who are asked to assess farm records and management practices. Following that, they may suggest a new approach, one that incorporates the principles of herd health management, including goal setting and on-going disease monitoring. Management practices are amended until incidents of disease decrease or no longer occur.
The key question now, suggests Green, is how to move from current approaches to mastitis control. A more ideal method would be to make use of current data to predict what is likely to happen in the future, he said. These opportunities, more and more, are becoming a reality.
Four examples of predictive biology for mastitis management
1. Predicting cow susceptibility
Predicting the susceptibility of an individual cow can be extremely valuable not only when it comes to making breeding decisions, but also in terms of individualized management practices. Green believes that susceptibility is, to some extent, dictated by genetic influences.
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