About: Winning the competition: enhancing counter-contagion in SIS-like epidemic processes

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About: Winning the competition: enhancing counter-contagion in SIS-like epidemic processes Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.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	Winning the competition: enhancing counter-contagion in SIS-like epidemic processes
Creator	Kalogeratos, Argyris Mannelli, Stefano
source	ArXiv
abstract	In this paper we consider the epidemic competition between two generic diffusion processes, where each competing side is represented by a different state of a stochastic process. For this setting, we present the Generalized Largest Reduction in Infectious Edges (gLRIE) dynamic resource allocation strategy to advantage the preferred state against the other. Motivated by social epidemics, we apply this method to a generic continuous-time SIS-like diffusion model where we allow for: i) arbitrary node transition rate functions that describe the dynamics of propagation depending on the network state, and ii) competition between the healthy (positive) and infected (negative) states, which are both diffusive at the same time, yet mutually exclusive on each node. Finally we use simulations to compare empirically the proposed gLRIE against competitive approaches from literature.
has issue date	2020-06-24(xsd:dateTime)
has license	arxiv
sha1sum (hex)	503bf089daa5a8174cf6bb5db6e5ba52da5c4824
resource representing a document's title	Winning the competition: enhancing counter-contagion in SIS-like epidemic processes
resource representing a document's body	covid:503bf089daa5a8174cf6bb5db6e5ba52da5c4824#body_text
is schema:about of	named entity 'DESCRIBE' named entity 'EPIDEMICS' named entity 'TIME' named entity 'LITERATURE' named entity 'TRANSITION' »more»

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