Print Email Facebook Twitter Resilience of epidemics for SIS model on networks Title Resilience of epidemics for SIS model on networks Author Lu, Dan (Beihang University) Yang, Shunkun (Beihang University) Zhang, Jiaquan (Beihang University) Wang, H. (TU Delft Multimedia Computing) Li, Daqing (Beihang University) Date 2017 Abstract Epidemic propagation on complex networks has been widely investigated, mostly with invariant parameters. However, the process of epidemic propagation is not always constant. Epidemics can be affected by various perturbations and may bounce back to its original state, which is considered resilient. Here, we study the resilience of epidemics on networks, by introducing a different infection rate λ2 during SIS (susceptible-infected-susceptible) epidemic propagation to model perturbations (control state), whereas the infection rate is λ1 in the rest of time. Noticing that when λ1 is below λc, there is no resilience in the SIS model. Through simulations and theoretical analysis, we find that even for λ2 < λc, epidemics eventually could bounce back if the control duration is below a threshold. This critical control time for epidemic resilience, i.e., cdmax, seems to be predicted by the diameter (d) of the underlying network, with the quantitative relation cdmax ~ dα. Our findings can help to design a better mitigation strategy for epidemics. To reference this document use: http://resolver.tudelft.nl/uuid:34f368c1-ccbe-49f1-8752-33d1813212f4 DOI https://doi.org/10.1063/1.4997177 ISSN 1054-1500 Source Chaos: an interdisciplinary journal of nonlinear science, 27 (8), 1-6 Part of collection Institutional Repository Document type journal article Rights © 2017 Dan Lu, Shunkun Yang, Jiaquan Zhang, H. Wang, Daqing Li Files PDF 26112514.pdf 1.2 MB Close viewer /islandora/object/uuid:34f368c1-ccbe-49f1-8752-33d1813212f4/datastream/OBJ/view