About: Analysis, Identification, and Validation of Discrete-Time Epidemic Processes

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Analysis, Identification, and Validation of Discrete-Time Epidemic Processes
Creator	Başar, Tamer Beck, Carolyn Kirwan, Barret Liu, Ji Paré, Philip
source	ArXiv
abstract	Models of spread processes over non-trivial networks are commonly motivated by modeling and analysis of biological networks, computer networks, and human contact networks. However, identification of such models has not yet been explored in detail, and the models have not been validated by real data. In this paper, we present several different spread models from the literature and explore their relationships to each other; for one of these processes, we present a sufficient condition for asymptotic stability of the healthy equilibrium, show that the condition is necessary and sufficient for uniqueness of the healthy equilibrium, and present necessary and sufficient conditions for learning the spread parameters. Finally, we employ two real datasets, one from John Snow's seminal work on cholera epidemics in London in the 1850's and the other one from the United States Department of Agriculture, to validate an approximation of a well-studied network-dependent susceptible-infected-susceptible (SIS) model.
has issue date	2017-10-30(xsd:dateTime)
has license	arxiv
sha1sum (hex)	9cf87c2f67fca108c748244f0bc54faf718ca76a
resource representing a document's title	Analysis, Identification, and Validation of Discrete-Time Epidemic Processes
resource representing a document's body	covid:9cf87c2f67fca108c748244f0bc54faf718ca76a#body_text
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