Evidence map›Paper›PMID 40606535›Full record

ReviewGlobal health & medicine2025

Creation and use of an index of the emergency resilience of urban public health management in China.

Shixiang Zhang, Yingyin Feng, Aiyong Zhu, Xiaoyan Huang, Tianxiang Huang

Abstract readReview
In one paragraph

Review in Global health & medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

5 authors.

Shixiang ZhangSchool of Nursing and Health Management, Shanghai University of Medicine and Health Science, Shanghai, China.
Yingyin FengSchool of Nursing and Health Management, Shanghai University of Medicine and Health Science, Shanghai, China.
Aiyong ZhuSchool of Nursing and Health Management, Shanghai University of Medicine and Health Science, Shanghai, China.
Xiaoyan HuangDivision of Emergency Management, Shanghai Center for Disease Control and Prevention, Shanghai, China.
Tianxiang HuangSchool of Health and Public Health, Shanghai University of Medicine and Health Science, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article proposes a framework for emergency resilience based on a review of the literature and theoretical analysis. On this basis, the Delphi method and the Analytic Hierarchy Process have been used to create an index of the emergency resilience of urban public health management. This index includes 6 primary indicators, 22 secondary indicators, and 93 tertiary indicators. An evaluation using the created index indicated that Shanghai's public health emergency management scored 82 out of 100, which is generally a good score. However, there are still problems such as the lack of specificity and implementability in emergency plans, the lack of diversification of reserves of emergency supplies, the low degree of sharing emergency information and cooperation, failure to capitalize on the advantages of traditional Chinese medicine, and the shortage of public health personnel in local communities. Overall, the index of the emergency resilience of urban public health management as was created from the perspective of preventing and controlling major infectious diseases is scientific and reliable, and it can effectively evaluate the current state of emergency management in urban public health.

Indexed as

creation of an indexemergency resilienceprevention and control of major infectious diseasespublic health emergency management

Identifiers

PMID40606535
PMCPMC12209874

What OpenQuestion holds

Textmetadata
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.