Coarse-grained bifurcation analysis and detection of criticalities of an individual-based epidemiological network model with infection control

Reppas, AI; Tsoumanis, AC; Siettos, CI

dc.contributor.author	Reppas, AI	en
dc.contributor.author	Tsoumanis, AC	en
dc.contributor.author	Siettos, CI	en
dc.date.accessioned	2014-03-01T01:33:00Z
dc.date.available	2014-03-01T01:33:00Z
dc.date.issued	2010	en
dc.identifier.issn	0307-904X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20273
dc.subject	Bifurcation analysis	en
dc.subject	Control	en
dc.subject	Epidemiology	en
dc.subject	Individual-based models	en
dc.subject	Multi-scale computations	en
dc.subject.classification	Engineering, Multidisciplinary	en
dc.subject.classification	Mathematics, Interdisciplinary Applications	en
dc.subject.classification	Mechanics	en
dc.subject.other	Amplitude oscillation	en
dc.subject.other	Bifurcation analysis	en
dc.subject.other	Bifurcation diagram	en
dc.subject.other	Coarse-grained	en
dc.subject.other	Computational framework	en
dc.subject.other	Control policy	en
dc.subject.other	Critical points	en
dc.subject.other	Equation-Free	en
dc.subject.other	Illustrative examples	en
dc.subject.other	Individual-based	en
dc.subject.other	Individual-based models	en
dc.subject.other	Infection control	en
dc.subject.other	Multi-scale computations	en
dc.subject.other	Multiscales	en
dc.subject.other	Network models	en
dc.subject.other	Regular networks	en
dc.subject.other	Stochastic epidemics	en
dc.subject.other	Time-dependent solutions	en
dc.subject.other	Bifurcation (mathematics)	en
dc.subject.other	Disease control	en
dc.subject.other	Equations of state	en
dc.subject.other	Stochastic models	en
dc.subject.other	Simulators	en
dc.title	Coarse-grained bifurcation analysis and detection of criticalities of an individual-based epidemiological network model with infection control	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.apm.2009.06.005	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.apm.2009.06.005	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	We present and discuss how the so called Equation-free approach for multi-scale computations can be used to systematically study certain aspects of the dynamics of detailed individual-based epidemiological simulators. As our illustrative example, we choose a simple individual-based stochastic epidemic model evolving on a fixed random regular network (RRN). We show how control policies based on the isolation of the infected population can dramatically influence the dynamics of the disease resulting to big-amplitude oscillations. We also address the development of a computational framework that enables detailed epidemiological simulators to converge to their coarse-grained critical points, which mark the onset of the emergent time-dependent solutions as well as to trace branches of coarse-grained unstable equilibria. Using the individual-based simulator we construct the coarse-grained bifurcation diagrams illustrating the dependence of the solutions on the disease characteristics. (C) 2009 Elsevier Inc. All rights reserved	en
heal.publisher	ELSEVIER SCIENCE INC	en
heal.journalName	Applied Mathematical Modelling	en
dc.identifier.doi	10.1016/j.apm.2009.06.005	en
dc.identifier.isi	ISI:000272065400003	en
dc.identifier.volume	34	en
dc.identifier.issue	3	en
dc.identifier.spage	552	en
dc.identifier.epage	560	en