Containing epidemics in a local cluster via antidote distribution and partial quarantine

Zhenqi Lu, Johan Wahlström, and Arye Nehorai
Phys. Rev. E 104, 034307 – Published 17 September 2021

Abstract

The study of spreading phenomena in networks, in particular the spread of disease, has attracted considerable interest in the network science research community. In this paper, we show that the outbreak of an epidemic can be effectively contained and suppressed in a small subnetwork by a combination of antidote distribution and partial quarantine. We improve over existing antidote distribution schemes based on personalized PageRank in two ways. First, we replace the constraint on the topology of this subnetwork described by Chung et al. [Internet Math. 6, 237 (2009)] that a large fraction of the value of the personalized PageRank vector must be contained in the local cluster, with a partial quarantine scheme. Second, we derive a different lower bound on the amount of antidote. We show that, under our antidote distribution scheme, the probability of the infection spreading to the whole network is bounded, and the infection inside the subnetwork will disappear after a period that is proportional to the logarithm of the number of initially infected nodes. We demonstrate the effectiveness of our strategy with numerical simulations of epidemics on benchmark networks. We also test our strategy on two examples of epidemics in real-world networks. Our strategy is dependent only on the rate of infection, the rate of recovery, and the topology around the initially infected nodes, and is independent of the rest of the network.

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  • Received 14 May 2021
  • Accepted 26 August 2021

DOI:https://doi.org/10.1103/PhysRevE.104.034307

©2021 American Physical Society

Physics Subject Headings (PhySH)

Networks

Authors & Affiliations

Zhenqi Lu1, Johan Wahlström2, and Arye Nehorai1

  • 1Preston M. Green Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA
  • 2Department of Computer Science, University of Exeter, Exeter EX4 4QF, United Kingdom

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Issue

Vol. 104, Iss. 3 — September 2021

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