Evaluation of the Spatial Effect of Network Resilience in the Yangtze River Delta: An Integrated Framework for Regional Collaboration and Governance under Disruption

Abstract

Public health emergencies are characterized by significant uncertainty and robust transmission, both of which will be exacerbated by population mobility, threatening urban security. Enhancing regional resilience in view of these risks is critical to the preservation of human lives and the stability of socio-economic development. Network resilience (NR) is widely accepted as a strategy for reducing the risk of vulnerability and maintaining regional sustainability. However, past assessments of it have not sufficiently focused on its spatial effect and have overlooked both its internal evolution characteristics and external threats which may affect its function and effectiveness. Therefore, we used the Yangtze River Delta Region (YRDR) as a case study and conceptualized an integrated framework to evaluate the spatial pattern and mechanisms of NR under the superposition of the COVID-19 pandemiv and major holidays. The results indicated that the topology of a population mobility network has a significant effect on its resilience. Accordingly, the network topology indexes differed from period to period, which resulted in a decrease of 17.7% in NR. For network structure, the Shanghai-Nanjing and Shanghai-Hangzhou development axes were dependent, and the network was redundant. In the scenario where 20% of the cities were disrupted, the NR was the largest. Furthermore, the failure of dominant nodes and the emergence of vulnerable nodes were key factors that undermined the network’s resilience. For network processes, NR has spatial effects when it is evolute and there is mutual inhibition between neighboring cities. The main factors driving changes in resilience were found to be GDP, urbanization rate, labor, and transportation infrastructure. Therefore, we propose a trans-scale collaborative spatial governance system covering “region-metropolitan-city” which can evaluate the uncertain disturbances caused by the network cascade effect and provide insights into the sustainable development of cities and regions.