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On the effectiveness of random walks for modeling epidemics on networks

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  • Sooyeong Kim
  • Jane Breen
  • Ekaterina Dudkina
  • Federico Poloni
  • Emanuele Crisostomi

Abstract

Random walks on graphs are often used to analyse and predict epidemic spreads and to investigate possible control actions to mitigate them. In this study, we first show that models based on random walks with a single stochastic agent (such as Google’s popular PageRank) may provide a poor description of certain features of epidemic spread: most notably, spreading times. Then, we discuss another Markov chain based method that does reflect the correct mean infection times for the disease to spread between individuals in a network, and we determine a procedure that allows one to compute them efficiently via a sampling strategy. Finally, we present a novel centrality measure based on infection times, and we compare its node ranking properties with other centrality measures based on random walks. Our results are provided for a simple SI model for epidemic spreading.

Suggested Citation

  • Sooyeong Kim & Jane Breen & Ekaterina Dudkina & Federico Poloni & Emanuele Crisostomi, 2023. "On the effectiveness of random walks for modeling epidemics on networks," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-28, January.
    • Handle: RePEc:plo:pone00:0280277
    DOI: 10.1371/journal.pone.0280277
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    References listed on IDEAS

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    1. Shams, Bita & Khansari, Mohammad, 2015. "On the impact of epidemic severity on network immunization algorithms," Theoretical Population Biology, Elsevier, vol. 106(C), pages 83-93.
    2. Raffaele D’Ambrosio & Giuseppe Giordano & Serena Mottola & Beatrice Paternoster, 2021. "Stiffness Analysis to Predict the Spread Out of Fake Information," Future Internet, MDPI, vol. 13(9), pages 1-10, August.
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