Farm classification by biosecurity level using a novel three-scale selection model

Area of Science:

• Veterinary Science
• Animal Health Management
• Agricultural Risk Assessment

Background:

• Effective farm biosecurity is crucial for disease prevention and relies on accurate assessments and improvement strategies.
• Classifying farms by biosecurity measures presents challenges, hindering progress in disease control.
• Existing classification methods may not fully capture nuanced biosecurity strengths and weaknesses.

Purpose of the Study:

• To develop and evaluate a novel 3-Scale Selection Model (3-SSM) for classifying dairy farms based on biosecurity assessment scores.
• To compare the performance of the 3-SSM against traditional Average-based and Cluster-based classification models.
• To provide a robust tool for identifying farms needing biosecurity improvements.

Main Methods:

• Developed the 3-Scale Selection Model (3-SSM) using biosecurity assessment scores from 723 dairy farms.
• Classified farms into three tiers: FC1-'Poor', FC2-'Medium', and FC3-'Good' Biosecurity.
• Evaluated the 3-SSM by comparing its classifications with Average-based (Model B) and Cluster-based (Model D) models.

Main Results:

• The 3-SSM classified 69.71% of farms as FC1-'Poor' and 16.32% as FC3-'Good' biosecurity.
• Significant discrepancies were observed when comparing 3-SSM classifications with Models B and D.
• The 3-SSM identified farms with high overall scores but critical weaknesses, unlike other models.

Conclusions:

• The 3-SSM offers a novel and effective approach to farm biosecurity classification.
• This model highlights farms requiring targeted biosecurity interventions, even those with seemingly good scores.
• The 3-SSM is adaptable and valuable for veterinarians, farmers, researchers, and policymakers for benchmarking and improvement.