Criticality and Information Dynamics in Epidemiological Models
AbstractUnderstanding epidemic dynamics has always been a challenge. As witnessed from the ongoing Zika or the seasonal Influenza epidemics, we still need to improve our analytical methods to better understand and control epidemics. While the emergence of complex sciences in the turn of the millennium have resulted in their implementation in modelling epidemics, there is still a need for improving our understanding of critical dynamics in epidemics. In this study, using agent-based modelling, we simulate a Susceptible-Infected-Susceptible (SIS) epidemic on a homogeneous network. We use transfer entropy and active information storage from information dynamics framework to characterise the critical transition in epidemiological models. Our study shows that both (bias-corrected) transfer entropy and active information storage maximise after the critical threshold (
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Erten, E.Y.; Lizier, J.T.; Piraveenan, M.; Prokopenko, M. Criticality and Information Dynamics in Epidemiological Models. Entropy 2017, 19, 194.
Erten EY, Lizier JT, Piraveenan M, Prokopenko M. Criticality and Information Dynamics in Epidemiological Models. Entropy. 2017; 19(5):194.Chicago/Turabian Style
Erten, E. Y.; Lizier, Joseph T.; Piraveenan, Mahendra; Prokopenko, Mikhail. 2017. "Criticality and Information Dynamics in Epidemiological Models." Entropy 19, no. 5: 194.
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