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Updated: Jan 16, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
A coupled model for public health risk: hazard and urban vulnerability in 18 cities in Sichuan, China
Lijuan Liu1,2,3, Jian Qiu1,2,3, Mian Yang1,4
1School of Architecture, Southwest Jiaotong University, Chengdu, China.
Introduction:
In the research and practice of disaster prevention/mitigation and urban resilience development, although existing studies have conducted multidimensional assessments of urban vulnerability to hazards and infectious disease risks, limitations persist-such as the lack of bidirectional coupling mechanism analysis and a disconnection from planning implementation. These constraints hinder the systematic governance of public health risks and the advancement of resilient city development.
Method:
This study selects 18 prefecture-level cities in Sichuan Province as case studies. By employing the entropy method and coupling coordination degree (CCD) model, we construct a "hazard-vulnerability" risk coupling model to systematically analyze the coupling coordination mechanisms, identify key influencing factors, and propose optimization pathways.
Results:
(1) The coupling coordination degree (CCD) between infectious disease hazards and urban vulnerability in Sichuan Province remains at a relatively low level overall (mean = 0.384). Specifically, Chengdu demonstrates a "low vulnerability-high hazard" characteristic (0.031), while Guangyuan and Panzhihua exhibit optimal coordination states (0.655 and 0.649 respectively). (2) The region generally follows the distribution pattern where lower CCD corresponds to higher risk levels. The coordinated development types show dispersed spatial distribution, whereas recession-maladjusted types are predominantly concentrated in the Chengdu Plain and southern Sichuan regions. (3) Among CCD subtypes, the "hazard-deficit" type emerges as the dominant pattern. (4) Economic-spatial-social-environmental factors demonstrate not only significant interaction effects but also pronounced spatial heterogeneity characteristics.
Conclusion:
Based on spatial coupling theory, this study innovatively constructs a "hazard-vulnerability" risk coupling model, which expands traditional risk assessment and urban vulnerability evaluation theories, providing a novel research perspective for urban risk management and regional sustainable development. The research results offer important quantitative evidence for formulating regionally differentiated public health strategies.
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