Evidence map›Paper›PMID 34402008›Full record

ArticleEnvironmental science and pollution research international2022

System dynamics analysis of COVID-19 prevention and control strategies.

Shuwei Jia, Yao Li, Tianhui Fang

Abstract read
In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  11. Modeling COVID-19 effects on SDGs using system dynamics in Egypt.Environmental science and pollution research international · 2022
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  12. Review
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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

3 authors.

Shuwei JiaBusiness School, Henan University, Jinming District, Kaifeng, Henan, 475004, People's Republic of China. shuweijia999666@163.com.ORCID http://orcid.org/0000-0001-9765-6935
Yao LiBusiness School, Henan University, Jinming District, Kaifeng, Henan, 475004, People's Republic of China.
Tianhui FangBusiness School, East China University of Science and Technology, Shanghai, 200237, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic now affects the entire world and has many major effects on the global economy, environment, health, and society. Focusing on the harm COVID-19 poses for human health and society, this study used system dynamics to establish a prevention and control model that combines material supply, public opinion dissemination, public awareness, scientific and technological research, staggered work shifts, and the warning effect (of law/policy). Causal loop analysis was used to identify interactions between subsystems and explore the key factors affecting social benefit. Further, different scenarios were dynamically simulated to explore optimal combination modes. The main findings were as follows: (1) The low supervision mode will produce a lag effect and superimposed effect on material supply and impede social benefit. (2) The strong supervision mode has multiple performances; it can reduce online public opinion dissemination and the rate of concealment and false declaration and improve government credibility and social benefit. However, a fading effect will appear in the middle and late periods, and over time, the effect of strong supervision will gradually weaken (but occasionally rebound) and thus require adjustment. These findings can provide a theoretical basis for improving epidemic prevention and control measures.

Indexed as

COVID-19PandemicsBiomedical ResearchCommunicable Disease ControlGovernmentHealth PolicyHumansInformation DisseminationPublic OpinionSystems AnalysisCOVID-19Emergency supplyPrevention and control strategySystem dynamics

Identifiers

PMID34402008
PMCPMC8367034

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.