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The Pandemics in Artificial Society: Agent-Based Model to Reflect Strategies on COVID-19

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  • Situngkir, Hokky
  • Lumbantobing, Andika Bernad

Abstract

Various social policies and strategies have been deliberated and used within many countries to handle the COVID-19 pandemic. Some of those basic ideas are strongly related to the understanding of human social interactions and the nature of disease transmission and spread. In this paper, we present an agent-based approach to model epidemiological phenomena as well as the interventions upon it. We elaborate on micro-social structures such as social-psychological factors and distributed ruling behaviors to grow an artificial society where the interactions among agents may exhibit the spreading of the virus. Capturing policies and strategies during the pandemic, four types of intervention are also applied in society. Emerged macro-properties of epidemics are delivered from sets of simulations, lead to comparisons between each policy/strategy’s effectivity.

Suggested Citation

  • Situngkir, Hokky & Lumbantobing, Andika Bernad, 2020. "The Pandemics in Artificial Society: Agent-Based Model to Reflect Strategies on COVID-19," MPRA Paper 102075, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:102075
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    References listed on IDEAS

    as
    1. Hokky Situngkir, 2004. "Money-Scape: A Generic Agent-Based Model of Corruption," Computational Economics 0405003, University Library of Munich, Germany.
    2. John H. Miller & Scott E. Page, 2007. "Social Science in Between, from Complex Adaptive Systems: An Introduction to Computational Models of Social Life," Introductory Chapters, in: Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press.
    3. John H. Miller & Scott E. Page, 2007. "Complexity in Social Worlds, from Complex Adaptive Systems: An Introduction to Computational Models of Social Life," Introductory Chapters, in: Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press.
    4. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    5. Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 1(1), pages 57-72, March.
    6. Hokky Situngkir, 2004. "How Far Can We Go Through Social System?," Method and Hist of Econ Thought 0409002, University Library of Munich, Germany.
    7. Matz Dahlberg & Per-Anders Edin & Erik Gronqvist & Johan Lyhagen & John Osth & Alexey Siretskiy & Marina Toger, 2020. "Effects of the COVID-19 Pandemic on Population Mobility under Mild Policies: Causal Evidence from Sweden," Papers 2004.09087, arXiv.org.
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    More about this item

    Keywords

    COVID-19; coronavirus disease; policy; pandemic; social simulations; artificial society; agent-based modeling.;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other
    • H89 - Public Economics - - Miscellaneous Issues - - - Other
    • I1 - Health, Education, and Welfare - - Health
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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