Evidence map›Paper›PMID 36160756›Full record

ArticleComputational urban science2022

Establishment of hospital resilience framework in urban China: insight from Wuhan City.

Annan Jin, Gang Li, Yue Yu, Jiaobei Wang, Qifan Nie

Abstract read
In one paragraph

Article in Computational urban science, 2022. 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.

Annan JinCollege of Urban and Environmental Sciences, Northwest University, 710127 Xi'an, China.
Gang LiCollege of Urban and Environmental Sciences, Northwest University, 710127 Xi'an, China.
Yue YuCollege of Urban and Environmental Sciences, Northwest University, 710127 Xi'an, China.
Jiaobei WangCollege of Urban and Environmental Sciences, Northwest University, 710127 Xi'an, China.
Qifan NieAlabama Transportation Institute, 248 Kirkbride Lane, Tuscaloosa, AL 35487 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the Corona Virus Disease 2019 (COVID-19) swept the world, many countries face a problem that is a shortage of medical resources. The role of emergency medical facilities in response to the epidemic is beginning to arouse public attention, and the construction of the urban resilient emergency response framework has become the critical way to resist the epidemic. Today, China has controlled the domestically transmitted COVID-19 cases through multiple emergency medical facilities and inclusive patient admission criteria. Most of the existing literature focuses on case studies or characterizations of individual facilities. This paper constructs an evaluation system to measure urban hospital resilience from the spatial perspective and deciphered the layout patterns and regularities of emergency medical facilities in Wuhan, the city most affected by the epidemic in China. Findings indicate that the pattern of one center and two circles are a more compelling layout structure for urban emergency medical facilities in terms of accessibility and service coverage for residents. Meanwhile, the Fangcang shelter hospital has an extraordinary performance in terms of emergency response time, and it is a sustainable facility utilization approach in the post-epidemic era. This study bolsters areas of the research on the urban resilient emergency response framework. Moreover, the paper summarizes new medical facilities' planning and location characteristics and hopes to provide policy-makers and urban planners with valuable empirical evidence.

Indexed as

COVID-19Hospital resilienceOptimizationResponse frameworkSpatial analysis

Identifiers

PMID36160756
PMCPMC9483400

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LicenceCC BY
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Registered trials

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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.