Evidence map›Paper›PMID 38528001›Full record

ArticleScientific reports2024

Investigating the spatiotemporal characteristics and medical response during the initial COVID-19 epidemic in six Chinese cities.

Li Lan, Gang Li, Muhammad Sajid Mehmood, Tingting Xu, Wei Wang, Qifan Nie

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

6 authors.

Li LanCollege of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China.
Gang LiCollege of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China. lig@nwu.edu.cn.
Muhammad Sajid MehmoodCollege of Geography and Environmental Science, Henan University, Kaifeng, 475001, China.
Tingting XuCollege of Urban and Environmental Sciences, Northwest University, Xi'an, 710127, China.
Wei WangNatural Resources Bureau of Shuocheng District, Shuozhou, 036000, Shanxi, China.
Qifan NieAlabama Transportation Institute, The University of Alabama, Tuscaloosa, AL, 35487-0288, USA.

Funding

Northwest University, China 2020
6 · The paper itself

Abstract

In the future, novel and highly pathogenic viruses may re-emerge, leading to a surge in healthcare demand. It is essential for urban epidemic control to investigate different cities' spatiotemporal spread characteristics and medical carrying capacity during the early stages of COVID-19. This study employed textual analysis, mathematical statistics, and spatial analysis methods to examine the situation in six highly affected Chinese cities. The findings reveal that these cities experienced three phases during the initial outbreak of COVID-19: "unknown-origin incubation", "Wuhan-related outbreak", and "local exposure outbreak". Cities with a high number of confirmed cases exhibited a multicore pattern, while those with fewer cases displayed a single-core pattern. The cores were distributed hierarchically in the central built-up areas of cities' economic, political, or transportation centers. The radii of these cores shrank as the central built-up area's level decreased, indicating a hierarchical decay and a core-edge structure. It suggests that decentralized built environments (non-clustered economies and populations) are less likely to facilitate large-scale epidemic clusters. Additionally, the deployment of designated hospitals in these cities was consistent with the spatial distribution of the epidemic; however, their carrying capacity requires urgent improvement. Ultimately, the essence of prevention and control is the governance of human activities and the efficient management of limited resources about individuals, places, and materials through leveraging IT and GIS technologies to address supply-demand contradictions.

Indexed as

COVID-19EpidemicsChinaCitiesDisease OutbreaksHumansSARS-CoV-2

Identifiers

PMID38528001
PMCPMC10963795

What OpenQuestion holds

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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.