ArticleFrontiers in public health2025
Research on optimization of emergency supplies customs clearance strategy from the perspective of public health security based on Chinese trade data.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study is significant for improving the accuracy of Customs' cross-border supervision of emergency supplies and ensuring the timely clearance of these essential goods. Methods: To ensure both the convenience and security of Customs oversight regarding emergency supplies, this study first systematically collects and organizes representative data on the import and export trade of these supplies. Proposed an enhanced Recency Frequency Monetary (RFM) cluster analysis model, building on the principles of k-means clustering. Subsequently, the model is employed to cluster the import and export trade data of emergency supplies. Finally, the paper offers optimization suggestions for customs clearance supervision based on the analysis results. Results: The study primarily focuses on the collection and organization of import and export trade data across six major categories of representative emergency supplies. By employing K-means clustering techniques, the research develops an improved RFM cluster analysis model, referred to as TR-TF-TV, and subsequently proposes strategies for customs supervision of emergency supplies. By integrating K-means clustering techniques, this study develops an advanced RFM cluster analysis model, referred to as TR-TF-TV. It subsequently proposes customs supervision strategies for emergency supplies. These strategies include a clustering analysis of trade data to ensure safe and efficient customs clearance, the preservation of integrity and stability within the emergency supplies supply chain, the enhancement of the national emergency management system, and the improvement of response capabilities to public health emergencies. Conclusion: This analysis of trade data concerning the import and export of emergency supplies, based on the enhanced RFM clustering model, represents an exploratory initiative in original model design. Recognizing the inherent limitations associated with the model's index design and data sample selection, we intend to refine these elements in future research, aiming to improve and validate the model to further optimize related countermeasures.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.