Evidence map›Paper›PMID 41741510›Full record

ArticleScientific reports2026

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

Fengze Wu, Chen Li, Yong Bian, Jin Li, Jie Tian, Zhian Li

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Fengze WuChina Jiliang University, Hangzhou, 310018, China.
Chen LiChina Jiliang University, Hangzhou, 310018, China. lichen@cjlu.edu.cn.
Yong BianChina Jiliang University, Hangzhou, 310018, China.
Jin LiChina Jiliang University, Hangzhou, 310018, China.
Jie TianChina Jiliang University, Hangzhou, 310018, China.
Zhian LiChina Jiliang University, Hangzhou, 310018, China.

Funding

National Key Research and Development Program of China 2023YFC2605801
6 · The paper itself

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.

Indexed as

BiosecurityContainment of BiohazardsDecision MakingFuzzy LogicHumansModels, TheoreticalPrincipal Component AnalysisRisk AssessmentBiosafetyInfectious substancesIntegrated weightingMulti-criteria decision-makingRisk assessmentTOPSIS-GRA

Identifiers

PMID41741510
PMCPMC13031422

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.