Evidence map›Paper›PMID 35627450›Full record

ArticleInternational journal of environmental research and public health2022

One-Size-Fits-All Policies Are Unacceptable: A Sustainable Management and Decision-Making Model for Schools in the Post-COVID-19 Era.

Cunwei Yang, Weiqing Wang, Fengying Li, Degang Yang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Cunwei YangDepartment of Computer Science and Technology, Southwest University, Chongqing 402460, China.
Weiqing WangDepartment of Management Science and Engineering, Southwest University, Chongqing 402460, China.ORCID 0000-0002-9468-1120
Fengying LiDepartment of Environmental Science, Nanjing University of Information Science and Technology, Nanjing 210044, China.ORCID 0000-0002-4492-0672
Degang YangState Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.ORCID 0000-0002-2774-921X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes a sustainable management and decision-making model for COVID-19 control in schools, which makes improvements to current policies and strategies. It is not a case study of any specific school or country. The term one-size-fits-all has two meanings: being blind to the pandemic, and conducting inflexible and harsh policies. The former strategy leads to more casualties and does potential harm to children. Conversely, under long-lasting strict policies, people feel exhausted. Therefore, some administrators pretend that they are working hard for COVID-19 control, and people pretend to follow pandemic control rules. The proposed model helps to alleviate these problems and improve management efficiency. A customized queue model is introduced to control social gatherings. An indoor-outdoor tracking system is established. Based on tracing data, we can assess people's infection risk, and allocate medical resources more effectively in case of emergency. We consider both social and technical feasibility. Test results demonstrate the improvements and effectiveness of the model. In conclusion, the model has patched up certain one-size-fits-all strategies to balance pandemic control and normal life.

Indexed as

COVID-19ChildHumansOrganizational PolicyPandemicsPolicySchoolsCOVID-19decision-makingepidemiologymanagement sciencepublic health policies

Identifiers

PMID35627450
PMCPMC9140660

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.