Issue |
EPL
Volume 98, Number 5, June 2012
|
|
---|---|---|
Article Number | 58004 | |
Number of page(s) | 5 | |
Section | Interdisciplinary Physics and Related Areas of Science and Technology | |
DOI | https://doi.org/10.1209/0295-5075/98/58004 | |
Published online | 11 June 2012 |
Impact of edge removal on the centrality betweenness of the best spreaders
1
Temasek Laboratories, National University of Singapore - Singapore 117508
2
Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University - 21 Nanyang Links, Singapore 637371
3
Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Singapore), National University of Singapore - Kent Ridge 119260, Singapore
4
Department of Physics, National University of Singapore - Singapore 117542
Received:
28
March
2012
Accepted:
10
May
2012
The control of epidemic spreading is essential to avoid potential fatal consequences and also, to lessen the unforeseen socio-economic impact. The need for effective control is exemplified during the severe acute respiratory syndrome (SARS) epidemy in 2003, which has inflicted nearly a thousand deaths as well as bankruptcies of airlines and related businesses. In this article, we examine the efficacy of control strategies on the propagation of infectious diseases based on removing connections within real-world airline networks with the associated economic and social costs taken into account through defining appropriate quantitative measures. We uncover the surprising results that removing less busy connections can be far more effective in hindering the spread of the disease than removing the more popular connections. Since disconnecting the less popular routes tends to incur less socio-economic cost, our finding suggests the possibility of trading minimal reduction in connectivity of an important hub with efficiencies in epidemic control. In particular, we demonstrate the performance of various local epidemic control strategies, and show how our approach can predict their cost effectiveness through the spreading control characteristics.
PACS: 89.75.Hc – Networks and genealogical trees / 87.23.Ge – Dynamics of social systems
© EPLA, 2012
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