Evidence map›Paper›PMID 25401755›Full record

ArticlePloS one2014

Immunization of epidemics in multiplex networks.

Dawei Zhao, Lianhai Wang, Shudong Li, Zhen Wang, Lin Wang, Bo Gao

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
11.5field-weighted citation impact, top 1% of its field
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

19 citing papers in PubMed, 146 citations in OpenAlex.

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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

6 authors at 4 institutions in 2 countries.

Dawei ZhaoShandong Provincial Key Laboratory of Computer Network, Shandong Computer Science Center (National Supercomputer Center in Jinan), Jinan, China.
Lianhai WangShandong Provincial Key Laboratory of Computer Network, Shandong Computer Science Center (National Supercomputer Center in Jinan), Jinan, China.
Shudong LiCollege of Mathematics and Information Science, Shandong Institute of Business and Technology, Shandong, Yantai, China; College of Computer, National University of Defense Technology, Hunan, Changsha, China.
Zhen WangDepartment of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong; Center for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Center for Nonlinear and Complex systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
Lin WangCentre for Chaos and Complex Networks, Department of Electronic Engineering, City University of Hong Kong, Hong Kong.
Bo GaoSchool of Computer Information management, Inner Mongolia University of Finance and Economics, Hohhot, China.
City University of Hong Kong · HKHong Kong Baptist University · HKInner Mongolia University of Finance and Economics · CNNational Supercomputing Center in Wuxi · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks.

Indexed as

EpidemicsImmunizationModels, TheoreticalAlgorithmsHumans

Identifiers

PMID25401755
PMCPMC4234317
OpenAlexW2040932880

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.