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ORIGINAL RESEARCH article

Front. Public Health
Sec. Disaster and Emergency Medicine
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1431158
This article is part of the Research Topic Communication Strategies in Public Health Disasters View all articles

Research on the Evaluation of Emergency Management Capability for Urban Public Health Emergencies under the Perspective of Resilience--A Case Study of Henan Province, China

Provisionally accepted
Yu Hao Yu Hao *Yuxin Tie Yuxin Tie Fan Zhang Fan Zhang Chaolun Sun Chaolun Sun *
  • Henan Polytechnic University, Jiaozuo, China

The final, formatted version of the article will be published soon.

    With the rapid development of the economy and society, the likelihood of sudden public health emergencies in urban areas continues to rise. In particular, major infectious diseases that have gained global attention, such as the SARS virus, H1N1 influenza, Ebola outbreak, and COVID-19 pandemic, have presented significant challenges to urban emergency management systems. Evaluating emergency management capability is a fundamental requirement for developing emergency response capacity. To this end, this study combines the theory of resilience with the theory of full-process equilibrium emergency management, selects 31 evaluation indicators from six key aspects: preparedness, forewarning, mitigation, disposal, recovery, and learning. The indicator weights are determined using the AHP-Entropy Weight Method, and a TOPSIS model is constructed to assess the emergency management capability of urban public health emergencies. The model's applicability is validated by examining 18 cities in Henan Province. The findings suggest that Jiaozuo, Hebi, Zhengzhou, and Luohe possess relatively robust emergency management capabilities for sudden public health incidents, whereas Kaifeng, Pingdingshan, and Shangqiu exhibit weaker capabilities.

    Keywords: public health emergencies1, The full process balance of emergency management2, Emergency management capacity3, capacity evaluation4, TOPSIS model5

    Received: 13 May 2024; Accepted: 07 Oct 2024.

    Copyright: © 2024 Hao, Tie, Zhang and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Yu Hao, Henan Polytechnic University, Jiaozuo, China
    Chaolun Sun, Henan Polytechnic University, Jiaozuo, China

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