Redefining Farm Risk: A Biosecurity and Proximity-Based Evaluation Matrix

Abstract

Biosecurity, in current farm evaluation procedures, is typically assessed through general inspection checklists that often presume compliance with the stipulated minimum distance requirements. However, such assumptions may overlook the nuanced role of biosecurity in mitigating disease risks. Additionally, farm assessments conducted for import certification or domestic recognition frequently lack standardized criteria, resulting in inconsistent and potentially inequitable evaluations. This article introduces a structured, risk-based farm evaluation matrix comprising eight criteria, categorized into severity and probability dimensions. Each criterion is rated at three levels, low, medium, and high, with corresponding numerical weights (5, 10, and 15) to enable consistent scoring. The Risk-Based Farm Score (RBFS) is calculated by multiplying the average scores of severity-related and probability-related criteria. To evaluate the matrix’s applicability, all attributes were held constant except for regulatory compliance and proximity to neighboring farms, each tested at three levels. Results demonstrate a clear inverse relationship between regulatory compliance and (RBFS), with higher regulatory compliance associated with lower risk scores. In contrast, proximity to other farms correlates with higher (RBFS), though its influence is less significant than that of regulatory compliance. Standard deviation analysis reveals greater variability in (RBFS) across compliance levels, underscoring the critical role of regulatory adherence in determining farm risk. Adoption of the developed farm evaluation matrix globally could enhance transparency, reduce trade barriers, and promote safer agricultural trade.