Epidemic Spreading and Localization in Multilayer Scale-free Networks

The creation and spreading of new pathogens by pathogen-pathogen interaction were modeled and computer-simulated using the Susceptible Infected Susceptible (SIS) model on three-layer scale-free networks: the Barabási-Albert (BA) networks, the Dorogovtsev-Mendes-Samukhin (DMS) networks and the shuffled BA networks. The new pathogen is a model of a new virus, critical privacy information (old pathogens are uncritical data) etc. When the emergence of a new pathogen was low, bimodal metastable states were observed. They had high states and low states of the prevalence. The high states were metastable states with positive prevalence. The low states have the prevalence fluctuating near 0. On both shuffled and non-shuffled networks, the epidemic prevalence in the metastable state on the BA networks are well explained by the the heterogeneous mean-field (HMF) formulation of the SIS+g model. The model does not match well on the DMS networks; this may be because their connectivity distributions are convex or concave. By the three-layer simulation, the infected nodes in layer-0 and layer-1 were found to be not always well-mixed i.e. they are localized. The localization occurred when the epidemic prevalence was low. The nodes with medium connectivity contributed to it. The meaning of results for privacy is discussed. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.31(2023) (online) DOI　http://dx.doi.org/10.2197/ipsjjip.31.97 ------------------------------

The creation and spreading of new pathogens by pathogen-pathogen interaction were modeled and computer-simulated using the Susceptible Infected Susceptible (SIS) model on three-layer scale-free networks: the Barabási-Albert (BA) networks, the Dorogovtsev-Mendes-Samukhin (DMS) networks and the shuffled BA networks. The new pathogen is a model of a new virus, critical privacy information (old pathogens are uncritical data) etc. When the emergence of a new pathogen was low, bimodal metastable states were observed. They had high states and low states of the prevalence. The high states were metastable states with positive prevalence. The low states have the prevalence fluctuating near 0. On both shuffled and non-shuffled networks, the epidemic prevalence in the metastable state on the BA networks are well explained by the the heterogeneous mean-field (HMF) formulation of the SIS+g model. The model does not match well on the DMS networks; this may be because their connectivity distributions are convex or concave. By the three-layer simulation, the infected nodes in layer-0 and layer-1 were found to be not always well-mixed i.e. they are localized. The localization occurred when the epidemic prevalence was low. The nodes with medium connectivity contributed to it. The meaning of results for privacy is discussed. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.31(2023) (online) DOI　http://dx.doi.org/10.2197/ipsjjip.31.97 ------------------------------