May the Best Meme Win!: New Exploration of Competitive Epidemic Spreading over Arbitrary Multi-Layer Networks
نویسندگان
چکیده
This study extends the SIS epidemic model for single virus propagation over an arbitrary graph to an SI1SI2S epidemic model of two exclusive, competitive viruses over a two-layer network with generic structure, where network layers represent the distinct transmission routes of the viruses. We find analytical results determining extinction, mutual exclusion, and coexistence of the viruses by introducing the concepts of survival threshold and winning threshold. Furthermore, we show the possibility of coexistence in SIS-type competitive spreading over multilayer networks. Not only do we rigorously prove a region of coexistence, we quantitate it via interrelation of central nodes across the network layers. Little to no overlapping of layers central nodes is the key determinant of coexistence. Specifically, we show coexistence is impossible if network layers are identical yet possible if the network layers have distinct dominant eigenvectors and node degree vectors. For example, we show both analytically and numerically that positive correlation of network layers makes it difficult for a virus to survive while in a network with negatively correlated layers survival is easier but total removal of the other virus is more difficult. We believe our methodology has great potentials for application to broader classes of multi-pathogen spreading over multi-layer and interconnected networks.
منابع مشابه
Multi-layer Clustering Topology Design in Densely Deployed Wireless Sensor Network using Evolutionary Algorithms
Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...
متن کاملFastSIR algorithm: A fast algorithm for the simulation of the epidemic spread in large networks by using the susceptible-infected-recovered compartment model
The epidemic spreading on arbitrary complex networks is studied in SIR (Susceptible Infected Recovered) compartment model. We propose our implementation of a Naive SIR algorithm for epidemic simulation spreading on networks that uses data structures efficiently to reduce running time. The Naive SIR algorithm models full epidemic dynamics and can be easily upgraded to parallel version. We also p...
متن کاملEpidemic Mitigation via Awareness Propagation in Multi-layer Networks
The pervasiveness of the Internet and smartphones enables individuals to participate in online social networks such Twitter and Facebook, besides the classic physical contact network. Such multi-layer network allows for feedback between networks / layers. For instance, the spread of a biological disease such as Ebola in a physical contact network may trigger the spreading of the information rel...
متن کاملDAVA: Distributing Vaccines over Networks under Prior Information
Given a graph, like a social/computer network or the blogosphere, in which an infection (or meme or virus) has been spreading for some time, how to select the k best nodes for immunization/quarantining immediately? Most previous works for controlling propagation (say via immunization) have concentrated on developing strategies for vaccination pre-emptively before the start of the epidemic. Whil...
متن کاملEpidemic Variability in Hierarchical Geographical Networks with Human Activity Patterns
Recently, some studies have revealed that non-Poissonian statistics of human behaviors stem from the hierarchical geographical network structure. On this view, we focus on epidemic spreading in the hierarchical geographical networks and study how two distinct contact patterns (i.e., homogeneous time delay (HOTD) and heterogeneous time delay (HETD) associated with geographical distance) influenc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1308.4880 شماره
صفحات -
تاریخ انتشار 2013