Evidence map›Paper›PMID 40255384›Full record

ArticleFrontiers in public health2025

The dynamic capabilities of county-level government in China during the outbreak of large-scale epidemics: a study based on three cases.

Changwei Wei, Juan Wang, Huangyue Wu, Zuying Xu, Jiahao Zhang

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. 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.

Changwei WeiSchool of Public Policy and Management, China University of Mining and Technology, Xuzhou, China.
Juan WangSchool of Public Policy and Management, China University of Mining and Technology, Xuzhou, China.
Huangyue WuSchool of Public Policy and Management, China University of Mining and Technology, Xuzhou, China.
Zuying XuSchool of Economics and Management, Huaibei Normal University, Huaibei, China.
Jiahao ZhangSchool of Public Policy and Management, China University of Mining and Technology, Xuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: After China entered the stage of normalized epidemic prevention and control, county-level government became the leading force and responsible body for prevention and control. In some counties, the epidemic was initially sporadic but later evolved into large-scale transmission. This situation posed a severe challenge to their dynamic capabilities. The dynamic capacity of county-level government largely determines the effectiveness of dealing with large-scale epidemics. Methods: This study selected three counties with a large-scale outbreak of COVID-19 in 2022 as samples for multi-case analysis, and used insight ability, integration ability, learning ability and innovation ability as dimensions for comparative analysis. Data and information were collected from the official websites of these three county-level governments using the octopus collector. Results: The dynamic capabilities of county-level government are related to the results of large-scale epidemic prevention and control. This topic has been less explored in existing research. Compared to Si County and Linshui County, Jiutai District clearly lacks dynamic capabilities in large-scale epidemic prevention and control. The different abilities of county-level government play different roles in epidemic prevention and control. Conclusion: County-level government are at the weakest stress point in the hierarchical structure of China's power system. They are at the forefront of public crisis management playing an important role, which further increase their pressure. Enhancing the dynamic capabilities of county-level government can greatly help them effectively respond to crises and alleviate their vulnerability.

Indexed as

COVID-19Disease OutbreaksEpidemicsLocal GovernmentChinaHumansSARS-CoV-2county-level governmentCOVID-19crisisdynamic capabilitieslarge-scale epidemics

Identifiers

PMID40255384
PMCPMC12006138

What OpenQuestion holds

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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.