Service flow changes in multilayer networks: A framework for measuring urban disaster resilience based on availability to critical facilities

Failures of roads and critical facilities under disasters can result in public service disruptions. Studies quantifying disaster resilience commonly focus on evaluating physical performance of infrastructure systems, often cannot capture their capacity that maintain available service to meet citizens' demands. This paper proposes a flow-based framework for quantitively measuring resilience by regarding changes in service availability to critical facilities as a primary measurement outcome. Through the utilization of multilayer networks, we effectively incorporate diverse datasets pertaining to population demographics, residential areas, critical facilities, and the roadway network. This integration enables us to simulate the intricate dynamics of public service flows within dynamic urban systems, thereby evaluating resilience levels and accurately mapping the spatial distribution patterns. The methodology was validated in Shanghai by quantifying regional variations in healthcare services under pluvial flood scenarios. The research findings highlight the heterogeneous redistribution of service flows during extreme events, leading to spatial variations in resilience outcomes, irrespective of the proximity to hazard-prone areas. The spatial clustering of vulnerable communities demonstrates a close association with mobility correlation patterns, which are strongly influenced by the distribution of facilities and the connectivity of the road network. Thus, using the framework offers valuable insights into risk mitigation and planning of critical facilities in extreme situations. It enhances the understanding on how urban resilience to disaster is influenced by urban form and flow interactions, generating robust evidence for policy.