The influence of infection control policies: A systematic study of the dynamics of an individual-based epidemic model with isolation

Reppas, A; Tsoumanis, AC; Siettos, CI

dc.contributor.author	Reppas, A	en
dc.contributor.author	Tsoumanis, AC	en
dc.contributor.author	Siettos, CI	en
dc.date.accessioned	2014-03-01T02:45:49Z
dc.date.available	2014-03-01T02:45:49Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32408
dc.subject	Bifurcation Diagram	en
dc.subject	Coarse Grained	en
dc.subject	Critical Point	en
dc.subject	Epidemic Model	en
dc.subject	Infection Control	en
dc.subject	Oscillations	en
dc.subject	Time Dependent	en
dc.subject.other	Amplitude oscillation	en
dc.subject.other	Bifurcation diagram	en
dc.subject.other	Coarse-grained	en
dc.subject.other	Computational protocols	en
dc.subject.other	Control policy	en
dc.subject.other	Critical points	en
dc.subject.other	Epidemic models	en
dc.subject.other	Equation-Free	en
dc.subject.other	Illustrative examples	en
dc.subject.other	Individual-based	en
dc.subject.other	Infection control	en
dc.subject.other	Multiscale	en
dc.subject.other	Regular networks	en
dc.subject.other	Stochastic epidemics	en
dc.subject.other	Systematic study	en
dc.subject.other	Time-dependent solutions	en
dc.subject.other	Bioinformatics	en
dc.subject.other	Disease control	en
dc.subject.other	Dynamics	en
dc.subject.other	Equations of state	en
dc.subject.other	Stochastic models	en
dc.subject.other	Simulators	en
dc.title	The influence of infection control policies: A systematic study of the dynamics of an individual-based epidemic model with isolation	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/BIBE.2008.4696766	en
heal.identifier.secondary	http://dx.doi.org/10.1109/BIBE.2008.4696766	en
heal.identifier.secondary	4696766	en
heal.publicationDate	2008	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 epidemic simulators. In particular we address the development of a computational protocol that enables detailed epidemic simulators to converge to their coarse-grained critical points which mark the onset of instabilities including the emergence of time-dependent solutions. As our illustrative example, we choose a simple individual-based stochastic epidemic model deploying in a fixed random regular network. 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 construct the approximate coarse-grained bifurcation diagrams illustrating the dependence of the solutions on the disease characteristics.	en
heal.journalName	8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008	en
dc.identifier.doi	10.1109/BIBE.2008.4696766	en