A multi-method integrated weighting framework for biosafety risk assessment of infectious substances

Area of Science:

• Public Health and Biosecurity
• Risk Management
• Decision Science

Background:

• Cross-border movement of infectious substances necessitates robust biosafety risk assessment for biosecurity.
• Current assessment methods struggle to integrate subjective expert judgment and objective data effectively.
• Heterogeneous information sources pose challenges for consistent and reliable risk evaluation.

Purpose of the Study:

• To develop a multi-method integrated weighting framework for cross-border biosafety risk assessment.
• To reconcile heterogeneous weighting information from subjective and objective sources.
• To enhance the consistency, robustness, and interpretability of biosafety risk evaluations.

Main Methods:

• Combined Fuzzy Analytic Hierarchy Process (FAHP) for subjective weights and Principal Component Analysis (PCA) for objective weights.
• Developed a constrained deviation-minimization optimization model to reconcile disparate weighting results.
• Applied an integrated TOPSIS-GRA (Grey Relational Analysis) model for risk quantification, considering ideal solutions and grey relational similarity.

Main Results:

• The proposed framework successfully integrates subjective and objective weighting information.
• The multi-method approach demonstrated improved consistency, robustness, and interpretability in biosafety risk evaluation.
• A case study on cross-border infectious substances validated the framework's effectiveness.

Conclusions:

• The developed framework offers a structured and reproducible tool for multi-criteria decision-making in biosafety.
• This approach provides practical support for managing risks associated with the cross-border movement of infectious substances.
• The integration of diverse data sources enhances the reliability of biosafety risk assessments under uncertainty.