About: Stochastic epidemic dynamics on extremely heterogeneous networks

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Stochastic epidemic dynamics on extremely heterogeneous networks
Creator	House, Thomas Mckane, Alan Parra-Rojas, César
source	PMC
abstract	Networks of contacts capable of spreading infectious diseases are often observed to be highly heterogeneous, with the majority of individuals having fewer contacts than the mean, and a significant minority having relatively very many contacts. We derive a two-dimensional diffusion model for the full temporal behavior of the stochastic susceptible-infectious-recovered (SIR) model on such a network, by making use of a time-scale separation in the deterministic limit of the dynamics. This low-dimensional process is an accurate approximation to the full model in the limit of large populations, even for cases when the time-scale separation is not too pronounced, provided the maximum degree is not of the order of the population size.
has issue date	2016-12-19(xsd:dateTime)
bibo:doi	10.1103/physreve.94.062408
bibo:pmid	28085423
has license	no-cc
sha1sum (hex)	de53bb2b749d677e458221edaa8f17912a691d1d
schema:url	https://doi.org/10.1103/physreve.94.062408
resource representing a document's title	Stochastic epidemic dynamics on extremely heterogeneous networks
has PubMed Central identifier	PMC7226849
has PubMed identifier	28085423
schema:publication	Phys Rev E
resource representing a document's body	covid:de53bb2b749d677e458221edaa8f17912a691d1d#body_text
is schema:about of	named entity 'temporal' named entity 'network' named entity 'individuals' named entity 'heterogeneous' named entity 'INFECTIOUS' named entity 'MAJORITY' named entity 'SCALE' named entity 'CONTACTS' named entity 'MEAN' named entity 'accurate' named entity 'behavior' named entity 'maximum degree' named entity 'infectious diseases' named entity 'contacts' named entity 'extremely' named entity 'Stochastic' named entity 'epidemic' named entity 'macroscopic' named entity 'Cox-Ingersoll-Ross' named entity 'eigenvalues' named entity 'initial condition' named entity 'epidemic' named entity 'eigenvalues' named entity 'stochastic' named entity 'fixed point' named entity 'basic reproductive ratio' named entity 'graph' named entity 'Jacobian' named entity 'Fokker-Planck' named entity 'test charge' named entity 'power-law' named entity 'good approximation' named entity 'K i' named entity 'Infection' named entity 'sexually transmitted infections' named entity 'demographic' named entity 'Mathematical models' named entity 'epidemic' named entity 'good approximation' named entity 'projection operator' named entity 'degree distribution' named entity 'stochastic' named entity 'epidemic' named entity 'basic reproductive ratio' named entity 'eigenvalues and eigenvectors' named entity 'epidemic' named entity 'vector' named entity 'evolution' named entity 'good approximation' named entity 'epidemic' named entity 'stability matrix' named entity 'good approximation' named entity '1, 2' named entity 'applied work' named entity 'epidemic' named entity 'heterogeneity' named entity 'stability matrix' named entity 'Jacobian' named entity 'probability' named entity 'eigenvalues' named entity 'vector' named entity 'three-dimensional' named entity 'epidemic' named entity 'diffusion approximation' named entity 'graph' named entity 'epidemic' named entity 'basic reproductive ratio' named entity 'equations of motion' named entity 'variance' named entity 'diffusion' named entity 'epidemic' named entity 'fixed point' named entity 'stochastic dynamics' named entity 'graph' named entity 'infection' named entity 'epidemic' named entity 'infection' named entity 'chi-square distribution' named entity 'SDEs'

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