Evidence map›Paper›PMID 32287502›Full record

ArticleApplied mathematics and computation2019

Investigation of epidemic spreading process on multiplex networks by incorporating fatal properties.

Peican Zhu, Xinyu Wang, Shudong Li, Yangming Guo, Zhen Wang

Abstract read
In one paragraph

Article in Applied mathematics and computation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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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

15 citing papers in PubMed.

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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.

Peican ZhuSchool of Computer Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
Xinyu WangSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Shudong LiCyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou 510006, China.
Yangming GuoSchool of Computer Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
Zhen WangSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous efforts have been devoted to investigating the network activities and dynamics of isolated networks. Nevertheless, in practice, most complex networks might be interconnected with each other (due to the existence of common components) and exhibit layered properties while the connections on different layers represent various relationships. These types of networks are characterized as multiplex networks. A two-layered multiplex network model (usually composed of a virtual layer sustaining unaware-aware-unaware (UAU) dynamics and a physical one supporting susceptible-infected-recovered-dead (SIRD) process) is presented to investigate the spreading property of fatal epidemics in this manuscript. Due to the incorporation of the virtual layer, the recovered and dead individuals seem to play different roles in affecting the epidemic spreading process. In details, the corresponding nodes on the virtual layer for the recovered individuals are capable of transmitting information to other individuals, while the corresponding nodes for the dead individuals (which are to be eliminated) on the virtual layer should be removed as well. With the coupled UAU-SIRD model, the relationships between the focused variables and parameters of the epidemic are studied thoroughly. As indicated by the results, the range of affected individuals will be reduced by a large amount with the incorporation of virtual layers. Furthermore, the effects of recovery time on the epidemic spreading process are also investigated aiming to consider various physical conditions. Theoretical analyses are also derived for scenarios with and without required time periods for recovery which validates the reducing effects of incorporating virtual layers on the epidemic spreading process.

Indexed as

Epidemic information spreadingMultiplex networksTheoretical validationUAU-SIRD model

Identifiers

PMID32287502
PMCPMC7112296

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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.