Evaluating Megacity Resilience to Pandemics: The Case of China.

IF 3.3 3区医学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Risk Analysis Pub Date : 2025-09-04 DOI:10.1111/risa.70102

Yaru Cheng, Hongyun Si, Zhikang Bao

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引用次数: 0

Abstract

Megacities' inherent complexity and dense populations heighten vulnerability to health crises, necessitating pandemic resilience research. This study pioneers a tailored resilience assessment framework for pandemic-facing megacities, building upon a refined Tyler and Moench urban resilience model. Applying grey correlation-technique for order preference by similarity to ideal solution (TOPSIS) methodology and barrier diagnosis modeling, we evaluated eight Chinese megacities. Key findings reveal: First, pandemic resilience scores exhibited fluctuating growth across all cities from 2014 to 2021. Shanghai demonstrated the most rapid improvement (23.13% increase), contrasting with Shenzhen's marginal gain (1.82%). Second, Shanghai achieved optimal coordination across systems, agents, and institutional dimensions in 2017, 2020, and 2021, whereas Shenzhen displayed the least dimension integration during 2016-2021. This dimensional equilibrium critically determines overall urban resilience. Finally, barrier analysis identified population scale, urban size, resource allocation efficiency, and mobility patterns as dominant resilience constraints. The findings and policy recommendations of this study can inform megacity development and pandemic response planning.

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评估特大城市应对流行病的韧性：以中国为例。

特大城市固有的复杂性和密集的人口增加了对卫生危机的脆弱性，因此有必要进行大流行复原力研究。本研究在完善的Tyler和Moench城市韧性模型的基础上，为面临大流行的特大城市开创了量身定制的韧性评估框架。应用TOPSIS方法和障碍诊断模型，对中国8个特大城市进行了排序偏好评价。主要研究结果显示：首先，2014年至2021年，所有城市的大流行抵御力得分都出现了波动增长。上海的改善最为迅速（增幅为23.13%），而深圳的边际增幅为1.82%。2017年、2020年和2021年，上海在制度、主体和制度维度上达到最优协调，而深圳在2016-2021年表现出最小的维度整合。这种空间平衡至关重要地决定了城市的整体弹性。最后，屏障分析发现，人口规模、城市规模、资源配置效率和流动模式是主要的弹性约束因素。本研究的结果和政策建议可为特大城市发展和大流行应对规划提供参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Risk Analysis 数学-数学跨学科应用

CiteScore

7.50

自引率

10.50%

发文量

183

审稿时长

4.2 months

期刊介绍： Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include: • Human health and safety risks • Microbial risks • Engineering • Mathematical modeling • Risk characterization • Risk communication • Risk management and decision-making • Risk perception, acceptability, and ethics • Laws and regulatory policy • Ecological risks.