DEVELOPING A COMPREHENSIVE FRAMEWORK FOR ASSESSING COMMUNITY RESILIENCE TO PUBLIC HEALTH EMERGENCIES IN HENAN PROVINCE: INSIGHTS FROM SCIBERT ANALYSIS
DOI:
https://doi.org/10.21837/pm.v23i38.1822Keywords:
Community Resilience, Public Health Emergencies, SciBERT Algorithm, Community PlanningAbstract
In the wake of frequent global pandemic outbreaks, the assessment of community resilience has emerged as a critical task for ensuring public health and safety. This study develops a comprehensive framework for evaluating community resilience to public health emergencies, focusing on communities in Henan Province, China. The research integrates a systematic literature review with advanced methodologies, including the SciBERT algorithm for indicator extraction, K-means clustering analysis, elbow method, silhouette analysis, and the Analytic Hierarchy Process (AHP). The resulting framework identifies key dimensions—Spatial Design and Infrastructure, Community Services and Support, Landscape and Ecology, and Medical and Safety Measures—that are essential for enhancing community resilience. The framework was validated through case studies in both urban and rural communities, revealing significant differences in resilience performance and highlighting the need for tailored strategies. This study offers a scientifically validated tool for public health managers and community planners, aiming to strengthen community resilience and improve response capabilities in future public health crises.
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