Equation-Free multiscale computational analysis of individual-based epidemic dynamics on networks

Siettos, CI

dc.contributor.author	Siettos, CI	en
dc.date.accessioned	2014-03-01T01:35:38Z
dc.date.available	2014-03-01T01:35:38Z
dc.date.issued	2011	en
dc.identifier.issn	0096-3003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/21138
dc.subject	Bifurcation analysis	en
dc.subject	Complex systems	en
dc.subject	Individual-based epidemic models	en
dc.subject	Multiscale computations	en
dc.subject	Networks	en
dc.subject	Pair-wise correlations	en
dc.subject.classification	Mathematics, Applied	en
dc.subject.other	Bifurcation analysis	en
dc.subject.other	Bifurcation diagram	en
dc.subject.other	Black boxes	en
dc.subject.other	Coarse-grained	en
dc.subject.other	Complex networks	en
dc.subject.other	Computational analysis	en
dc.subject.other	Computational methodology	en
dc.subject.other	Connected graph	en
dc.subject.other	Epidemic dynamics	en
dc.subject.other	Epidemic models	en
dc.subject.other	Equation-Free	en
dc.subject.other	Individual-based	en
dc.subject.other	Long-term prediction	en
dc.subject.other	Macroscopic levels	en
dc.subject.other	Multiscale computations	en
dc.subject.other	Multiscales	en
dc.subject.other	Numerical bifurcation analysis	en
dc.subject.other	Optimization method	en
dc.subject.other	Pair-wise correlations	en
dc.subject.other	SIRS epidemic model	en
dc.subject.other	Stationary state	en
dc.subject.other	Steady state	en
dc.subject.other	System-level analysis	en
dc.subject.other	Time-dependent computations	en
dc.subject.other	Timestepper	en
dc.subject.other	Bifurcation (mathematics)	en
dc.subject.other	Computer simulation	en
dc.subject.other	Mathematical models	en
dc.subject.other	Simulated annealing	en
dc.subject.other	Disease control	en
dc.title	Equation-Free multiscale computational analysis of individual-based epidemic dynamics on networks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.amc.2011.05.067	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.amc.2011.05.067	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	The surveillance, analysis and ultimately the efficient long-term prediction and control of epidemic dynamics appear to be some of the major challenges nowadays. Detailed individual-based mathematical models on complex networks play an important role towards this aim. In this work, it is shown how one can exploit the Equation-Free approach and optimization methods such as Simulated Annealing to bridge detailed individual-based epidemic models with coarse-grained, system-level analysis within a pair-wise representation perspective. The proposed computational methodology provides a systematic approach for analyzing the parametric behavior of complex/multiscale epidemic simulators much more efficiently than simply simulating forward in time. It is shown how steady state and (if required) time-dependent computations, stability computations, as well as continuation and numerical bifurcation analysis can be performed in a straightforward manner. The approach is illustrated through a simple individual-based SIRS epidemic model deploying on a random regular connected graph. Using the individual-based simulator as a black box coarse-grained timestepper and with the aid of Simulated Annealing I compute the coarse-grained equilibrium bifurcation diagram and analyze the stability of the stationary states sidestepping the necessity of obtaining explicit closures at the macroscopic level. (C) 2011 Elsevier Inc. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE INC	en
heal.journalName	Applied Mathematics and Computation	en
dc.identifier.doi	10.1016/j.amc.2011.05.067	en
dc.identifier.isi	ISI:000293009400012	en
dc.identifier.volume	218	en
dc.identifier.issue	2	en
dc.identifier.spage	324	en
dc.identifier.epage	336	en