Evidence map›Paper›PMID 35004130›Full record

ArticleComplex & intelligent systems2022

The selection of COVID-19 epidemic prevention and control programs based on group decision-making.

Chunsheng Cui, Baiqiu Li, Liu Wang

Abstract read
In one paragraph

Article in Complex & intelligent systems, 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

3 authors.

Chunsheng CuiCollege of Computer and Information Engineering, Henan University of Economics and Law, 180 Jinshui East Road, Zhengzhou, 450046 Henan China.
Baiqiu LiCollege of Computer and Information Engineering, Henan University of Economics and Law, 180 Jinshui East Road, Zhengzhou, 450046 Henan China.ORCID 0000-0001-7670-1266
Liu WangCollege of Computer and Information Engineering, Henan University of Economics and Law, 180 Jinshui East Road, Zhengzhou, 450046 Henan China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has been wreaking havoc on the world for close to two years. As the virus continues to mutate, epidemic prevention and control has become a long and experienced war. In the face of the sudden spread of virus strains, how to quickly and effectively formulate prevention and control plans are essential to ensuring the safety and social stability of cities. This paper is based on the characteristics, namely, its persistence and the high transmissibility of mutated strains, as well as the database of epidemic prevention and control plans formed as part of the existing prevention and control measures. Then, epidemic prevention experts select effective alternatives from the program database and rank their preferences through the preliminary analysis of the local epidemic situation. The process of the integration scheme aims to minimize the differences in an effort to maximize the needs of the local epidemic. Once the consensus ranking of the scheme is obtained, the final prevention and control scheme can be determined. The proposed method of this paper can optimize the opinions of the epidemic prevention expert group and form a consensus decision, whilst also saving time by carrying out the work effectively, which is of certain practical significance to the prevention and control effect of local outbreaks.

Indexed as

Alternative rankingConsensus reachingEpidemic prevention and controlGroup decision making

Identifiers

PMID35004130
PMCPMC8724238

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.