Evidence map›Paper›PMID 36612798›Full record

ArticleInternational journal of environmental research and public health2022

Quantifying Social Interventions for Combating COVID-19 via a Symmetry-Based Model.

Lei Zhang, Guang-Hui She, Yu-Rong She, Rong Li, Zhen-Su She

Abstract read
PubMed Full text at PMC Publisher
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

5 authors.

Lei ZhangInstitute of Health Systems Engineering, College of Engineering, Peking University, Beijing 100871, China.ORCID 0000-0002-3825-7456
Guang-Hui SheInstitute of Health Systems Engineering, College of Engineering, Peking University, Beijing 100871, China.
Yu-Rong SheInstitute of Health Systems Engineering, College of Engineering, Peking University, Beijing 100871, China.
Rong LiInstitute of Health Systems Engineering, College of Engineering, Peking University, Beijing 100871, China.
Zhen-Su SheInstitute of Health Systems Engineering, College of Engineering, Peking University, Beijing 100871, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has revealed new features in terms of substantial changes in rates of infection, cure, and death as a result of social interventions, which significantly challenges traditional SEIR-type models. In this paper we developed a symmetry-based model for quantifying social interventions for combating COVID-19. We found that three key order parameters, separating degree (S) for susceptible populations, healing degree (H) for mild cases, and rescuing degree (R) for severe cases, all display logistic dynamics, establishing a novel dynamic model named

Indexed as

COVID-19BeijingHumansPandemicsSARS-CoV-2Social WorkCOVID-19logistic dynamicsorder parametersSHR dynamical modelsymmetry analysis

Identifiers

PMID36612798
PMCPMC9819631

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.