Abstract
A two-layer susceptible-infected-recovered/unaware-aware (SIR-UA) epidemic model is presented to analyze the effect of different heterogeneous networks in a population. Random, scale-free, and small-world network topologies are tested to investigate the impact of awareness on the spread of epidemics in a two-layer network with diverse combinations of degree and structure. Susceptible and infected (both unaware and aware) individuals are associated with their neighboring nodes in a social network structure with various degree distributions. In the two-layer SIR-UA epidemic model, a virtual network represents the connections that spread information, while a physical network represents the physical social interactions that spread diseases. We test various combinations of network structures in virtual or physical networks, to understand the impact of information diffusion on the spread of epidemics in a heterogeneous network structure. Then, the effects of awareness on the spread of a disease are discussed. Finally, phase diagrams are illustrated to reveal the final regions covered by an epidemic with various network parameters. We find that a disease spreads less if the virtual social network is more connected than the network of physical connections.
| Original language | English |
|---|---|
| Pages (from-to) | 565-574 |
| Number of pages | 10 |
| Journal | Communications in Nonlinear Science and Numerical Simulation |
| Volume | 72 |
| DOIs | |
| Publication status | Published - Jun 30 2019 |
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All Science Journal Classification (ASJC) codes
- Numerical Analysis
- Modelling and Simulation
- Applied Mathematics
Cite this
Analysis of epidemic outbreaks in two-layer networks with different structures for information spreading and disease diffusion. / Kabir, K. M.Ariful; Tanimoto, Jun.
In: Communications in Nonlinear Science and Numerical Simulation, Vol. 72, 30.06.2019, p. 565-574.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Analysis of epidemic outbreaks in two-layer networks with different structures for information spreading and disease diffusion
AU - Kabir, K. M.Ariful
AU - Tanimoto, Jun
PY - 2019/6/30
Y1 - 2019/6/30
N2 - A two-layer susceptible-infected-recovered/unaware-aware (SIR-UA) epidemic model is presented to analyze the effect of different heterogeneous networks in a population. Random, scale-free, and small-world network topologies are tested to investigate the impact of awareness on the spread of epidemics in a two-layer network with diverse combinations of degree and structure. Susceptible and infected (both unaware and aware) individuals are associated with their neighboring nodes in a social network structure with various degree distributions. In the two-layer SIR-UA epidemic model, a virtual network represents the connections that spread information, while a physical network represents the physical social interactions that spread diseases. We test various combinations of network structures in virtual or physical networks, to understand the impact of information diffusion on the spread of epidemics in a heterogeneous network structure. Then, the effects of awareness on the spread of a disease are discussed. Finally, phase diagrams are illustrated to reveal the final regions covered by an epidemic with various network parameters. We find that a disease spreads less if the virtual social network is more connected than the network of physical connections.
AB - A two-layer susceptible-infected-recovered/unaware-aware (SIR-UA) epidemic model is presented to analyze the effect of different heterogeneous networks in a population. Random, scale-free, and small-world network topologies are tested to investigate the impact of awareness on the spread of epidemics in a two-layer network with diverse combinations of degree and structure. Susceptible and infected (both unaware and aware) individuals are associated with their neighboring nodes in a social network structure with various degree distributions. In the two-layer SIR-UA epidemic model, a virtual network represents the connections that spread information, while a physical network represents the physical social interactions that spread diseases. We test various combinations of network structures in virtual or physical networks, to understand the impact of information diffusion on the spread of epidemics in a heterogeneous network structure. Then, the effects of awareness on the spread of a disease are discussed. Finally, phase diagrams are illustrated to reveal the final regions covered by an epidemic with various network parameters. We find that a disease spreads less if the virtual social network is more connected than the network of physical connections.
UR - http://www.scopus.com/inward/record.url?scp=85060849309&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060849309&partnerID=8YFLogxK
U2 - 10.1016/j.cnsns.2019.01.020
DO - 10.1016/j.cnsns.2019.01.020
M3 - Article
AN - SCOPUS:85060849309
VL - 72
SP - 565
EP - 574
JO - Communications in Nonlinear Science and Numerical Simulation
JF - Communications in Nonlinear Science and Numerical Simulation
SN - 1007-5704
ER -