Evidence map›Paper›PMID 32287501›Full record

ArticleApplied mathematics and computation2018

Coupling dynamics of epidemic spreading and information diffusion on complex networks.

Xiu-Xiu Zhan, Chuang Liu, Ge Zhou, Zi-Ke Zhang, Gui-Quan Sun, Jonathan J H Zhu, Zhen Jin

Abstract read
In one paragraph

Article in Applied mathematics and computation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. A Systematic Review and Meta-Analysis of Hospitalised Current Smokers and COVID-19.International journal of environmental research and public health · 2020
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Pathogen diversity in meta-population networks.Chaos, solitons, and fractals · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Epidemic modeling for the resurgence of COVID-19 in Chinese local communities.Journal of safety science and resilience = An quan ke xue yu ren xing (Ying wen) · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. Article
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  19. Article
  20. Review
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

7 authors.

Xiu-Xiu ZhanResearch Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, PR China.
Chuang LiuResearch Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, PR China.
Ge ZhouResearch Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, PR China.
Zi-Ke ZhangResearch Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, PR China.
Gui-Quan SunComplex Systems Research Center, Shanxi University, Taiyuan 030006, PR China.
Jonathan J H ZhuWeb Mining Lab, Department of Media and Communication, City University of Hong Kong, Kowloon, Hong Kong Special Administrative Region, PR China.
Zhen JinComplex Systems Research Center, Shanxi University, Taiyuan 030006, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interaction between disease and disease information on complex networks has facilitated an interdisciplinary research area. When a disease begins to spread in the population, the corresponding information would also be transmitted among individuals, which in turn influence the spreading pattern of the disease. In this paper, firstly, we analyze the propagation of two representative diseases (

Indexed as

Coupling dynamicsEpidemic spreadingInformation diffusion

Identifiers

PMID32287501
PMCPMC7112333

What OpenQuestion holds

Textmetadata
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.