Evidence map›Paper›PMID 32123091›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

The effects of evolutionary adaptations on spreading processes in complex networks.

Rashad Eletreby, Yong Zhuang, Kathleen M Carley, Osman Yağan, H Vincent Poor

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Integrated framework to study genomic surveillance of selective sweeps in multivariants dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Coupled models of genomic surveillance and evolving pandemics with applications for timely public health interventions.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  4. Spreading processes with mutations over multilayer networks.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Fundamental limitations on efficiently forecasting certain epidemic measures in network models.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  11. Review
  12. Article
  13. Article
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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.

Rashad EletrebyDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213.
Yong ZhuangDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213.
Kathleen M CarleyInstitute for Software Research, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213.
Osman YağanDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213; oyagan@ece.cmu.edu poor@princeton.edu.
H Vincent PoorDepartment of Electrical Engineering, Princeton University, Princeton, NJ 08544 oyagan@ece.cmu.edu poor@princeton.edu.ORCID 0000-0002-2062-131X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A common theme among previously proposed models for network epidemics is the assumption that the propagating object (e.g., a pathogen [in the context of infectious disease propagation] or a piece of information [in the context of information propagation]) is transferred across network nodes without going through any modification or evolutionary adaptations. However, in real-life spreading processes, pathogens often evolve in response to changing environments and medical interventions, and information is often modified by individuals before being forwarded. In this article, we investigate the effects of evolutionary adaptations on spreading processes in complex networks with the aim of 1) revealing the role of evolutionary adaptations on the threshold, probability, and final size of epidemics and 2) exploring the interplay between the structural properties of the network and the evolutionary adaptations of the spreading process.

Indexed as

FeedbackModels, TheoreticalCommunicable DiseasesComputer SecurityEpidemicsEvolution, MolecularHumansInternetepidemicsevolutioninformation propagationspreading processes

Identifiers

PMID32123091
PMCPMC7084153

What OpenQuestion holds

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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.