Assessing the vulnerability of urban public health system based on a hybrid model
Datos Bibliográficos
| ID | 22079146 |
|---|---|
| Autores | Lingmei Fu (0000-0001-7009-1284, Nanjing Tech University), Zhirong Wang (0000-0002-3919-8304, Nanjing Tech University), Yutao Zhu (Wuhan University of Technology), Benbu Liang (0000-0002-6875-7996, Wuhan University of Technology), Ting Qian (0000-0001-6113-0341), Ting Ting Qian (Nanjing Tech University), Haiyun Ma (0009-0002-2440-6489, Nanjing Tech University, autor de correspondencia) |
| Año | 2025 |
| Volumen | 13 |
| Páginas | 1576214-1576214 |
| Fecha de publicación | 2025-05-21 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Frontiers in Public Health (JOURNAL) |
| Identificadores de la revista | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Editorial | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2025.1576214 |
| PMID | 40469592 |
| OpenAlex | W4410571385 |
| Idioma | EN |
| Citas recibidas | 1 |
| Referencias citadas | 39 |
Background: 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. Materials and methods: 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. Results: 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." Conclusion: 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
Computer security · Environmental health · Environmental planning · Geography · Public health · Computer Science · Disaster Response and Management · Facility Location and Emergency Management · Infrastructure Resilience and Vulnerability Analysis · Medicine · Nursing
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| Obras citantes distintas | 1 |
|---|---|
| Citas por año | 1 |
| Intervalo de citas | 2025 - 2025 (1) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 1 |