Evidence map›Paper›PMID 34916861›Full record

ArticleRisk management and healthcare policy2021

Control and Prevention of the COVID-19 Epidemic in China: A Qualitative Community Case Study.

Yijin Wu, Quan Zhang, Linzi Li, Meiyu Li, Ying Zuo

Open access · goldAbstract read
In one paragraph

Article in Risk management and healthcare policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

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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 at 5 institutions in 1 country.

Yijin WuSchool of Translation Studies, Qufu Normal University, Rizhao, Shandong, People's Republic of China.
Quan ZhangSchool of International Affairs and Public Administration, Ocean University of China, Qingdao, Shandong, People's Republic of China.
Linzi LiRizhao Maternal and Child Health Hospital, Rizhao, Shandong, People's Republic of China.
Meiyu LiSchool of Economics and Management, China University of Petroleum (East China), Qingdao, Shandong, People's Republic of China.
Ying ZuoSchool of International Affairs and Public Administration, Ocean University of China, Qingdao, Shandong, People's Republic of China.
China University of Petroleum, East China · CNOcean University of China · CNPeople’s Hospital of Rizhao · CNQufu Normal University · CNShandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCross-infection among residents in communities is one of the most critical reasons for the rapid spread of the COVID-19 epidemic. The COVID-19 epidemic has been well controlled within Chinese communities, which has made important contributions to the country's fight against it.

methodsIn this study, a qualitative case study design, with mixed methods applied to data collection and analysis, was employed to explore epidemic prevention measures taken by a Chinese community, namely Mulin, during the pandemic.

resultsThe Mulin community established an integrated plan for epidemic prevention, including the prevention of the invasion of COVID-19, the prevention of cross-infection within the community, gaining the residents' trust and support, and providing the residents with convenient services.

conclusionIn the present work, the Mulin community was taken as a typical case study, and qualitative methods were employed to comprehensively summarize the practice and experience of the community's epidemic prevention. Mulin's practices could shed light on how communities in other countries, especially developing countries with large populations, can prevent the spread of COVID-19.

Indexed as

ChinacommunityCOVID-19epidemic prevention

Identifiers

PMID34916861
PMCPMC8668872
OpenAlexW4206636153

What OpenQuestion holds

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LicenceCC BY-NC
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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.