Evidence map›Paper›PMID 40469592›Full record

ArticleFrontiers in public health2025

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

Lingmei Fu, Zhirong Wang, Yutao Zhu, Benbu Liang, Ting Qian, Haiyun Ma

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lingmei FuCollege of Emergency Management, Nanjing Tech University, Nanjing, Jiangsu, China.
Zhirong WangCollege of Emergency Management, Nanjing Tech University, Nanjing, Jiangsu, China.
Yutao ZhuSchool of Management, Wuhan University of Technology, Wuhan, Hubei, China.
Benbu LiangSchool of Law, Humanities and Sociology, Wuhan University of Technology, Wuhan, Hubei, China.
Ting QianCollege of Emergency Management, Nanjing Tech University, Nanjing, Jiangsu, China.
Haiyun MaCollege of Emergency Management, Nanjing Tech University, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Public HealthVulnerable PopulationsBayes TheoremChinaHumansModels, Theoreticalinfluential factorpublic health managementurban public health systemvulnerability assessmentweight determination

Identifiers

PMID40469592
PMCPMC12133845

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.