Evidence map›Paper›PMID 25923411›Full record

ArticleScientific reports2015

Optimizing hybrid spreading in metapopulations.

Changwang Zhang, Shi Zhou, Joel C Miller, Ingemar J Cox, Benjamin M Chain

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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.

Changwang Zhang1] Department of Computer Science, University College London, UK [2] Security Science Doctoral Research Training Centre, University College London, UK [3] School of Computer Science, National University of Defense Technology, Changsha, China.
Shi ZhouDepartment of Computer Science, University College London, UK.
Joel C Miller1] School of Mathematical Sciences, Monash University, Melbourne, Victoria, Australia [2] School of Biological Sciences, Monash University, Melbourne, Victoria, Australia [3] Monash Academy for Cross &Interdisciplinary Mathematics, Monash University, Melbourne, Victoria, Australia.
Ingemar J Cox1] Department of Computer Science, University of Copenhagen, Denmark [2] Department of Computer Science, University College London, UK.
Benjamin M ChainDivision of Infection and Immunity, University College London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemics, and examine the optimum balance between spreading mechanisms in terms of achieving the maximum outbreak size. We show the existence of critically hybrid epidemics where neither spreading mechanism alone can cause a noticeable spread but a combination of the two spreading mechanisms would produce an enormous outbreak. Our results provide new strategies for maximising beneficial epidemics and estimating the worst outcome of damaging hybrid epidemics.

Indexed as

Communicable DiseasesDisease OutbreaksDisease Transmission, InfectiousEpidemicsHumansModels, Theoretical

Identifiers

PMID25923411
PMCPMC4413882

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.