Saltar al contenido principal

ETHNOS_APP

Inicio • Búsqueda • Revistas • Lista 0

Assessing the vulnerability of urban public health system based on a hybrid model

Datos Bibliográficos

ID22079146
AutoresLingmei 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)
Año2025
Volumen13
Páginas1576214-1576214
Fecha de publicación2025-05-21
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Public Health (JOURNAL)
Identificadores de la revistaISSN: 2296-2565 • E-ISSN: 2296-2565
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1576214
PMID40469592
OpenAlexW4410571385
IdiomaEN
Citas recibidas1
Referencias citadas39

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

  • Vulnerability characteristics and adaptation strategies of public health systems in different regions of China

    Open Access•Yajun Teng, Y K Onno Teng et al.•Frontiers in Public Health•2025

  • What is a resilient health system? Lessons from Ebola

    Open Access•Margaret E Kruk, Michael Myers et al.•The Lancet•2015

  • Socioeconomic Vulnerability and Adaptation to Environmental Risk

    Open Access•Roland Brouwer, Roy Brouwer et al.•Risk Analysis•2007

  • Community resilience to flood hazards in Khyber Pukhthunkhwa province of Pakistan

    Open Access•Said Qasim, Mohammad Qasim et al.•International Journal of Disaster…•2016

  • Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Social Distancing Measures

    Open Access•Min Whui Fong, Huizhi Gao et al.•Emerging infectious diseases•2020

  • Evaluation of the vulnerability to public health events in the Guangdong-Hong Kong-Macao Greater Bay Area

    Open Access•Wenjing Cui, Jing Chen et al.•Frontiers in Public Health•2022

  • GIS-based Covid-19 vulnerability mapping in the West Bank, Palestine

    Open Access•Sameer Shadeed, Sandy Alawna•International Journal of Disaster…•2021

  • A system dynamics model for social vulnerability to natural disasters

    Open Access•Seyed Ashkan Zarghami, Jantanee Dumrak•International Journal of Disaster…•2021

  • Bayesian spatiotemporal forecasting and mapping of Covid‐19 risk with application to West Java Province, Indonesia

    Open Access•I Gede Nyoman Mindra Jaya, Henk Folmer•Journal of Regional Science•2021

  • Cities in a pandemic

    Open Access•Badi H Baltagi, Ying Deng et al.•Journal of Regional Science•2023

  • On the identification of most appropriate green roof types for urbanized cities using multi-tier decision analysis

    Open Access•Ömer Ekmekcioğlu•Sustainable Cities and Society•2023

  • A Web-based Public Participation GIS for assessing the age-friendliness of cities

    Open Access•Mohammadreza Jelokhani-Niaraki, Mohammadreza Jelokhani‐Niaraki et al.•Cities•2019

  • Covid-19 and urban vulnerability in India

    Open Access•Swasti Vardhan Mishra, Amiya Gayen et al.•Habitat International•2020

Obras citantes distintas1
Citas por año1
Intervalo de citas2025 - 2025 (1)
Velocidad de citaciónrecent
Altamente citadoNo
Tipos de citaNeutras: 1
Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae