Abstract
Biosafety risk assessment of infectious substances in cross-border movement is essential for preventing biosecurity threats and supporting regulatory decision-making. However, existing approaches often rely either on subjective expert judgment or purely objective data, making it difficult to effectively integrate heterogeneous information sources. This study proposes a multi-method integrated weighting framework for cross-border biosafety risk assessment by combining the Fuzzy Analytic Hierarchy Process (FAHP), Principal Component Analysis (PCA), and an integrated TOPSIS–GRA evaluation model.In the proposed framework, FAHP and PCA are used to derive subjective and objective indicator weights, respectively. The discrepancies between different weighting results are explicitly characterized, and a constrained deviation-minimization optimization model is constructed to reconcile heterogeneous weighting information and obtain a combined weight vector under normalization constraints. The integrated TOPSIS–GRA model is then applied to quantify biosafety risks by jointly considering the distance from ideal solutions and grey relational similarity. A scenario-based case study on cross-border infectious substances demonstrates that the proposed framework improves the consistency, robustness, and interpretability of biosafety risk evaluation. The results indicate that the proposed approach provides a structured and reproducible tool for multi-criteria decision-making under uncertainty and offers practical support for biosafety management.
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The data used to support the findings of this study are available from the corresponding author and first author upon request.
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Funding
This study was supported by National Key Research and Development Program of China grant(2023YFC2605801).
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F.W.and C.L.wrote the main manuscript text ,J.L. and Y.B. and J.T. and Z.L. prepared table 1–5.All authors reviewed the manuscript.
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Wu, F., Li, C., Bian, Y. et al. A multi-method integrated weighting framework for biosafety risk assessment of infectious substances. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39982-7
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DOI: https://doi.org/10.1038/s41598-026-39982-7
