Abstract
Models of infection spreading have been used and applied to economic, health, and social contexts. Seeing them as an optimization problem, the spreading can be maximized or minimized. This paper presents a novel optimization problem for infection spreading control applied to networks. It uses as a parameter the number of relations (edges) that must be cut, and the optimal solution is the set of edges that must be cut to ensure the minimal infection over time. The problem uses the states of SEIS nodes, which is based on the SEIR and SIS models. We refer to the problem as Min-SEIS-Cluster. The model also considers that the infections occurred over different probabilities in different clusters of individuals (nodes). We also report a heuristic to solve Min-SEIS-Cluster. The analysis of the obtained results allows one to observe that there exists a positive correlation between the proportion of removed edges and relative increase of mitigation effectiveness.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Batagelj, V., Mrvar, A.: Pajek datasets (2006). http://vlado.fmf.uni-lj.si/pub/networks/data/
Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech.: Theory Exp. 2008(10), 10008 (2008)
Easley, D., Kleinberg, J.: Networks, Crowds, and Markets. Cambridge University Press, Cambridge (2010)
Fortunato, S., Castellano, C.: Community structure in graphs. In: Meyers, R.A. (ed.) Computational Complexity, pp. 490–512. Springer, New York (2012)
Gil, S., Kott, A., Barabási, A.L.: A genetic epidemiology approach to cyber-security. Sci. Rep. 4, 5659 (2014)
Goyal, S., Kearns, M.: Competitive contagion in networks. In: Proceedings of the 44th Symposium on Theory of Computing - STOC 2012. p. 759. ACM, New York (2012)
Goyal, S., Vigier, A., Jong, M.D., Elliot, M., Galeotti, A., Gallo, E., Gagnan, J., Goenka, A., Hoyer, B., Jackson, M., Kovenock, D., Levy, G., Meyer, M., Nava, F., Pancs, R., Prummer, A., Razin, R., Reich, B., Rutsaert, P.: Attack, defense and contagion in networks. Rev. Econ. Stud. (2014)
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., Vespignani, A.: Epidemic processes in complex networks. Rev. Mod. Phys. 87(3), 925–979 (2015)
Pionitti, P.Y.A., Gomes, M.F.D.C., Samay, N., Perra, N., Vespignani, A.: The infection tree of global epidemics. Netw. Sci. 2(01), 132–137 (2014)
Tsai, J., Weller, N., Tambe, M.: Analysis of heuristic techniques for controlling contagion. In: AAAI Fall Symposium: Social Networks and Social Contagion, pp. 69–75 (2012)
Xie, J., Kelley, S., Szymanski, B.K.: Overlapping community detection in networks. ACM Comput. Surv. 45(4), 1–35 (2013)
Acknowledgments
This work is partly supported by the Brazilian Research Council CNPq, the Universidade do Vale do Itajaí, and government of the State of Santa Catarina (Brazil).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
de Santiago, R., Zunino, W., Concatto, F., Lamb, L.C. (2016). A New Model and Heuristic for Infection Minimization by Cutting Relationships. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9948. Springer, Cham. https://doi.org/10.1007/978-3-319-46672-9_56
Download citation
DOI: https://doi.org/10.1007/978-3-319-46672-9_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-46671-2
Online ISBN: 978-3-319-46672-9
eBook Packages: Computer ScienceComputer Science (R0)