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Fast and principled simulations of the SIR model on temporal networks

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  • Petter Holme

Abstract

The Susceptible–Infectious–Recovered (SIR) model is the canonical model of epidemics of infections that make people immune upon recovery. Many of the open questions in computational epidemiology concern the underlying contact structure’s impact on models like the SIR model. Temporal networks constitute a theoretical framework capable of encoding structures both in the networks of who could infect whom and when these contacts happen. In this article, we discuss the detailed assumptions behind such simulations—how to make them comparable with analytically tractable formulations of the SIR model, and at the same time, as realistic as possible. We also present a highly optimized, open-source code for this purpose and discuss all steps needed to make the program as fast as possible.

Suggested Citation

  • Petter Holme, 2021. "Fast and principled simulations of the SIR model on temporal networks," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-15, February.
    • Handle: RePEc:plo:pone00:0246961
    DOI: 10.1371/journal.pone.0246961
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    References listed on IDEAS

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    1. Luis E C Rocha & Fredrik Liljeros & Petter Holme, 2011. "Simulated Epidemics in an Empirical Spatiotemporal Network of 50,185 Sexual Contacts," PLOS Computational Biology, Public Library of Science, vol. 7(3), pages 1-9, March.
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    Cited by:

    1. Lazebnik, Teddy, 2023. "Computational applications of extended SIR models: A review focused on airborne pandemics," Ecological Modelling, Elsevier, vol. 483(C).
    2. Tao, Li & Kong, Shengzhou & He, Langzhou & Zhang, Fan & Li, Xianghua & Jia, Tao & Han, Zhen, 2022. "A sequential-path tree-based centrality for identifying influential spreaders in temporal networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).

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