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Network Biology, 2019, 9(3): 42-57
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Article

Average reachability: A new metric to estimate epidemic growth considering the network structure and epidemic severity

Bita Shams, Mohammad Khansari
Faculty of New Sciences and Technologies, University of Tehran, Amir Abad, North Kargar Street, Tehran 14399-57131, Iran

Received 12 May 2019;Accepted 15 June 2019;Published 1 September 2019
IAEES

Abstract
It is a fundamental issue to find a small subset of individuals in a complex network such that their immunization (i.e. removal) minimizes epidemic growth in the network. Though some network topological metrics have been proposed to estimate the effect of individual immunization or epidemic growth of the network, none of them considered the severity of the current epidemic. This paper proposes a new metric, called average reachability (AR) to estimate epidemic growth in a network. AR incorporates infection rate of epidemics to make a trade-off between network local connectivity and global reachability. Moreover, we intend to generalize stochastic hill-climbing immunization (SHCI) algorithm to minimize network epidemic growth regarding all estimation criteria. SIR simulation on immunized networks shows that the combination of AR and SHCI results in minimal epidemic growth compared to immunization algorithms that minimize density or sum of square partitions.

Keywords complex network;epidemic spreading;immunization;stochastic hill-climbing algorithm;average reachability.



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