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The effects of evolutionary adaptations on spreading processes in complex networks.
Eletreby, Rashad; Zhuang, Yong; Carley, Kathleen M; Yagan, Osman; Poor, H Vincent.
Affiliation
  • Eletreby R; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213.
  • Zhuang Y; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213.
  • Carley KM; Institute for Software Research, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213.
  • Yagan O; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213; oyagan@ece.cmu.edu poor@princeton.edu.
  • Poor HV; Department of Electrical Engineering, Princeton University, Princeton, NJ 08544 oyagan@ece.cmu.edu poor@princeton.edu.
Proc Natl Acad Sci U S A ; 117(11): 5664-5670, 2020 03 17.
Article in En | MEDLINE | ID: mdl-32123091
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computer Security / Internet / Feedback / Epidemics / Models, Theoretical Type of study: Prognostic_studies Limits: Humans Language: En Journal: Proc Natl Acad Sci U S A Year: 2020 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computer Security / Internet / Feedback / Epidemics / Models, Theoretical Type of study: Prognostic_studies Limits: Humans Language: En Journal: Proc Natl Acad Sci U S A Year: 2020 Document type: Article
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