Novel epidemic models on PSO-based networks
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 36-43 |
Journal / Publication | Journal of Theoretical Biology |
Volume | 477 |
Online published | 10 Jun 2019 |
Publication status | Published - 21 Sept 2019 |
Link(s)
Abstract
This paper proposes two spatio-temporal epidemic network models based on popularity and similarity optimization (PSO), called r-SI and r-SIS, respectively, in which new connections take both popularity and similarity into account. In the spatial dimension, the epidemic process is described by the diffusion equation; in the time dimension, the growth of an epidemic is described by the logistic map. Both models are represented by partial differential equations, and can be easily solved. Simulations are performed on both artificial and real networks, demonstrating the effectiveness of the two models.
Research Area(s)
- Epidemic dynamics, Hyperbolic space, Popularity, Similarity
Citation Format(s)
Novel epidemic models on PSO-based networks. / Fan, Dongmei; Jiang, Guo-Ping; Song, Yu-Rong et al.
In: Journal of Theoretical Biology, Vol. 477, 21.09.2019, p. 36-43.
In: Journal of Theoretical Biology, Vol. 477, 21.09.2019, p. 36-43.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review