Fu Lingmei, Wang Zhirong, Zhu Yutao, Liang Benbu, Qian Ting, Ma Haiyun
College of Emergency Management, Nanjing Tech University, Nanjing, Jiangsu, China.
School of Management, Wuhan University of Technology, Wuhan, Hubei, China.
Front Public Health. 2025 May 21;13:1576214. doi: 10.3389/fpubh.2025.1576214. eCollection 2025.
Public health emergencies pose direct threats to economic and social development. The vulnerability of urban public health system is a major cause of public health emergency outbreaks. It is essential to assess the vulnerability urban public health system.
To address the uncertainty inherent to the vulnerability assessment process, a novel hybrid model is proposed. Stage 1 involves the development of an indicator system, incorporating a comprehensive set of vulnerability factors identified through literature review and expert consultation. Stage 2 involves the calculation of indicator weights using the Bayesian best-worst method (BWM)-a novel probabilistic group decision-making approach that incorporates Bayesian statistics with the traditional BWM. Stage 3 involves the determination of vulnerability levels using a cloud model. The cloud model can combine the randomness and fuzziness of assessment to deal with uncertainty. The model is applied to assess the vulnerability of Shanghai's public health system. Moreover, a sensitivity analysis was conducted to validate the effectiveness and robustness of the model.
A total of 18 factors were identified as affecting the vulnerability of the urban public health system. The most significant among them are "poor coordination and cooperation among various personnel," "insufficient information assurance," "low public awareness," and "low competency among staff in relevant departments and institutions."
The proposed hybrid model is both effective and robust. This study contributes to reducing the vulnerability of urban public health systems, thereby enhancing public health risk management in urban settings.
突发公共卫生事件对经济社会发展构成直接威胁。城市公共卫生系统的脆弱性是突发公共卫生事件爆发的主要原因。评估城市公共卫生系统的脆弱性至关重要。
为解决脆弱性评估过程中固有的不确定性，提出了一种新型混合模型。第一阶段涉及建立指标体系，纳入通过文献综述和专家咨询确定的一套全面的脆弱性因素。第二阶段涉及使用贝叶斯最佳最差方法（BWM）计算指标权重，这是一种将贝叶斯统计与传统BWM相结合的新型概率群体决策方法。第三阶段涉及使用云模型确定脆弱性水平。云模型可以结合评估的随机性和模糊性来处理不确定性。该模型用于评估上海公共卫生系统的脆弱性。此外，进行了敏感性分析以验证模型的有效性和稳健性。
共确定了18个影响城市公共卫生系统脆弱性的因素。其中最显著的是“各类人员之间协调合作不佳”、“信息保障不足”、“公众意识淡薄”以及“相关部门和机构工作人员能力低下”。
所提出的混合模型既有效又稳健。本研究有助于降低城市公共卫生系统的脆弱性，从而加强城市环境中的公共卫生风险管理。
