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The effect of social distancing on the reach of an epidemic in social networks

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Listed:
  • Gutin, Gregory
  • Hirano, Tomohiro
  • Hwang, Sung-Ha
  • Neary, Philip R
  • Toda, Alexis Akira
Abstract
How does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a susceptible-infected-removed with social distancing model. The key feature of the model is that individuals are limited in the number of acquaintances that they can interact with, thereby constraining disease transmission to an infectious subnetwork of the original social network. While increased social distancing typically reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the network, indicating the need for policies that are network dependent. Our results also reveal the importance of coordinating policies at the 'global' level. In particular, the public health benefits from social distancing to a group (e.g. a country) may be completely undone if that group maintains connections with outside groups that are not following suit.

Suggested Citation

  • Gutin, Gregory & Hirano, Tomohiro & Hwang, Sung-Ha & Neary, Philip R & Toda, Alexis Akira, 2021. "The effect of social distancing on the reach of an epidemic in social networks," University of California at San Diego, Economics Working Paper Series qt7xv4h5qr, Department of Economics, UC San Diego.
    • Handle: RePEc:cdl:ucsdec:qt7xv4h5qr
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    References listed on IDEAS

    as
    1. Timothy C Reluga, 2010. "Game Theory of Social Distancing in Response to an Epidemic," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-9, May.
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    3. Dingel, Jonathan I. & Neiman, Brent, 2020. "How many jobs can be done at home?," Journal of Public Economics, Elsevier, vol. 189(C).
    4. Lančić, Alen & Antulov-Fantulin, Nino & Šikić, Mile & Štefančić, Hrvoje, 2011. "Phase diagram of epidemic spreading — unimodal vs. bimodal probability distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 65-76.
    5. Stefanie Gerke & Gregory Gutin & Sung-Ha Hwang & Philip Neary, 2019. "Public goods in networks with constraints on sharing," Papers 1905.01693, arXiv.org, revised Jun 2023.
    6. Bloom, David E. & Canning, David & Sevilla, Jaypee, 2004. "The Effect of Health on Economic Growth: A Production Function Approach," World Development, Elsevier, vol. 32(1), pages 1-13, January.
    7. Alessio Muscillo & Paolo Pin & Tiziano Razzolini, 2020. "Covid19: Unless one gets everyone to act, policies may be ineffective or even backfire," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-6, September.
    8. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost & Marco C. Sammon & Tasaneeya Viratyosin, 2020. "The Unprecedented Stock Market Impact of COVID-19," NBER Working Papers 26945, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Patrick Mellacher, 2022. "Endogenous viral mutations, evolutionary selection, and containment policy design," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(3), pages 801-825, July.
    2. Gerke, Stefanie & Gutin, Gregory & Hwang, Sung-Ha & Neary, Philip R., 2024. "Public goods in networks with constraints on sharing," Journal of Economic Theory, Elsevier, vol. 219(C).

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