# Measuring and optimizing the urban community resilience against public health emergencies: a case study in Nanjing, China

## TL;DR

This paper studies how urban communities can better handle public health emergencies by measuring and improving their resilience, using Nanjing, China as a case study.

## Contribution

The study introduces a resilience assessment framework with 31 factors and proposes both static and dynamic optimization strategies for urban community resilience.

## Key findings

- A resilience assessment framework with 31 key influencing factors was developed for urban communities.
- Static optimization strategies were proposed based on social, environmental, and economic factors.
- Dynamic strategies were identified using Bayesian network inference and importance analysis.

## Abstract

Urban communities, as the basic unit of urban governance, play a crucial role in responding to public health emergencies (PHEs). This study aims to investigate the resilience measurement and optimization strategies of urban communities in responding to PHEs in order to improve their resilience.

The study constructed a resilience assessment framework and identified 31 key influencing factors to measure the resilience of case communities in Nanjing. Through sensitivity analysis, static optimization strategies were proposed from social, environmental, and economic levels. Dynamic Bayesian network inference simulation and importance analysis were used to propose dynamic optimization strategies from pre, during, and long-term perspectives.

Through the combination of dynamic and static strategies, community managers promote resilience building from both short-term and long-term perspectives.

The study provides a valuable reference for comprehensively improving the emergency management system.