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Descendant distributions for the impact of mutant contagion on networks

Jonas S. Juul1,2,* and Steven H. Strogatz2,†

  • 1Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, Copenhagen 2100-DK, Denmark
  • 2Center for Applied Mathematics, Cornell University, Ithaca, New York 14853, USA

  • *jonas.juul@nbi.ku.dk
  • †strogatz@cornell.edu
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Phys. Rev. Research 2, 033005 – Published 1 July, 2020

DOI: https://doi.org/10.1103/PhysRevResearch.2.033005

Abstract

Contagion, broadly construed, refers to anything that can spread infectiously from peer to peer. Examples include communicable diseases, rumors, misinformation, ideas, innovations, bank failures, and electrical blackouts. Sometimes, as in the 1918 Spanish flu epidemic, a contagion mutates at some point as it spreads through a network. Here, using a simple susceptible-infected model of contagion, we explore the downstream impact of a single mutation event. Assuming that this mutation occurs at a random node in the contact network, we calculate the distribution of the number of “descendants,” d, downstream from the initial “patient zero” mutant. We find that the tail of the distribution decays as d−2 for complete graphs, random graphs, small-world networks, networks with block-like structure, and other infinite-dimensional networks. This prediction agrees with the observed statistics of memes propagating and mutating on Facebook and is expected to hold for other effectively infinite-dimensional networks, such as the global human contact network. In a wider context, our approach suggests a possible starting point for a mesoscopic theory of contagion. Such a theory would focus on the paths traced by a spreading contagion, thereby furnishing an intermediate level of description between that of individual nodes and the total infected population. We anticipate that contagion pathways will hold valuable lessons, given their role as the conduits through which single mutations, innovations, or failures can sweep through a network as a whole.

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Phys. Rev. Research 2, 033005– Published 1 July, 2020
  • Received 7 January 2020
  • Accepted 3 June 2020
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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