An indicator model for assessing community resilience to the COVID-19 pandemic and its validation: A case study in Hong Kong

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Nan Liao, Muhammad Nawaz
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引用次数: 0

Abstract

The COVID-19 outbreak had a significant negative impact on the world, and the fifth wave of COVID-19 in Hong Kong brought a considerable shock to Chinese society. There is a growing call for more resilient cities. However, empirical evidence and validation of modeling studies of resilience indicators for urban community responses to the COVID-19 pandemic still need to be provided. In this study, a resilience assessment indicator model comprising 4 subsystems, 7 indicators, and 12 variables was developed to assess the resilience of Hong Kong communities in response to COVID-19 (i.e., Resilience Index). Furthermore, this study utilized regression models such as geographically weighted regression (GWR) and multiscale GWR (MGWR) to validate the resilience model proposed in this study at the model and variable levels. In the regression model, the Resilience Index and the individual variables in the resilience model are explanatory variables, and the outcomes of the COVID-19 pandemic (confirmed cases, confirmation rate, discharged cases, discharge rate) are dependent variables. The results showed that: (i) the resilience of Hong Kong communities to the COVID-19 pandemic was not strong in general and showed some clustered spatial distribution characteristics; (ii) the validation results at the model level showed that the Resilience Index did not explain the consequences of the COVID-19 pandemic to a high degree; (iii) the validation results at the variable level showed that the MGWR model was the best at identifying the relationships between explanatory variables and the dependent variable; and (iv) compared with the model-level assessment results, the variable-level assessment explained the consequences of the COVID-19 pandemic better than the model level assessment results. The above analysis and the spatial distribution maps of the resilience variables can provide empirically based and targeted insights for policymakers.

用于评估社区抵御 COVID-19 大流行能力的指标模型及其验证:香港案例研究
COVID-19 的爆发给世界带来了巨大的负面影响,而在香港爆发的第五波 COVID-19 给中国社会带来了相当大的冲击。提高城市抗灾能力的呼声日益高涨。然而,城市社区应对 COVID-19 大流行的复原力指标模型研究仍需提供实证证据和验证。本研究建立了一个由 4 个子系统、7 个指标和 12 个变量组成的复原力评估指标模型,以评估香港社区应对 COVID-19 的复原力(即复原力指数)。此外,本研究利用地理加权回归(GWR)和多尺度地理加权回归(MGWR)等回归模型,在模型和变量层面验证了本研究提出的复原力模型。在回归模型中,复原力指数和复原力模型中的各个变量为解释变量,COVID-19 大流行的结果(确诊病例、确诊率、出院病例、出院率)为因变量。结果显示(i) 香港社区对 COVID-19 大流行的复原力总体上并不强,并呈现出一些聚类空间分布特征;(ii) 模型层面的验证结果显示,复原力指数对 COVID-19 大流行后果的解释程度并不高;(iii) 变量层面的验证结果表明,MGWR 模型最能确定解释变量与因变量之间的关系; (iv) 与模型层面的评估结果相比,变量层面的评估结果比模型层面的评估结果更能解释 COVID-19 大流行病的后果。上述分析和复原力变量的空间分布图可为决策者提供基于经验的、有针对性的见解。
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
安全科学与韧性(英文)
安全科学与韧性(英文) Management Science and Operations Research, Safety, Risk, Reliability and Quality, Safety Research
CiteScore
8.70
自引率
0.00%
发文量
0
审稿时长
72 days
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