An efficient immunization strategy based on transmission limit in weighted complex networks
Creators
- 1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094 (China)
- 2. Institute of Food Economics, Nanjing University of Finance and Economics, Nanjing, 210003 (China)
Description
The immunization strategy against the epidemic spreading in real world has attracted widespread attention of scientists from many different fields. However, the traditional immune behavior is achieved by deleting the edges in the network, which can lead to variations in the network structure and consequently serious damage to the efficiency of networks. In this paper, we studied a new type of immune strategy applied to weighted networks, which is to maintain the necessary network efficiency by limit the transmission(reduce the weight of edges) to suppress the spread of epidemic. It is similar to the inflammation around the infected parts of our body, which not only prevent epidemic from further spreading but also do no harm to the function of the body. We first set the rate of transmission be proportional to the edge weight according to the S–I epidemic spreading model. Then, we propose the specific dynamic evolution model for infected nodes that boosts efficient epidemic control. Theoretical analysis and simulation results indicate that the immunization strategy can efficaciously prevent the spread of the epidemic, while maintaining the high efficiency of the network.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.chaos.2018.06.014Additional details
Identifiers
- DOI
- 10.1016/j.chaos.2018.06.014;
- PII
- S0960077918303953;
Publishing Information
- Journal Title
- Chaos, Solitons and Fractals
- Journal Volume
- 114
- Journal Page Range
- p. 1-7
- ISSN
- 0960-0779
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 51023535
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Descriptors DEI
- EFFICIENCY; FUNCTIONS; INFLAMMATION; MATHEMATICAL MODELS; SIMULATION; VARIATIONS
- Descriptors DEC
- PATHOLOGICAL CHANGES; SYMPTOMS
Optional Information
- Notes
- © 2018 Published by Elsevier Ltd.