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A Hybrid Agent-Based and Equation Based Model for the Spread of Infectious Diseases

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  • Elizabeth Hunter
  • Brian Mac Namee
  • John Kelleher

Abstract

Both agent-based models and equation-based models can be used to model the spread of an infectious disease. Equation-based models have been shown to capture the overall dynamics of a disease outbreak while agent-based models are able to capture heterogeneous characteristics of agents that drive the spread of an outbreak. However, agent-based models are computationally intensive. To capture the advantages of both the equation-based and agent-based models, we create a hybrid model where the disease component of the hybrid model switches between agent-based and equation-based. The switch is determined using the number of agents infected. We first test the model at the town level and then the county level investigating different switch values and geographic levels of switching. We find that a hybrid model is able to save time compared to a fully agent-based model without losing a significant amount of fidelity.

Suggested Citation

  • Elizabeth Hunter & Brian Mac Namee & John Kelleher, 2020. "A Hybrid Agent-Based and Equation Based Model for the Spread of Infectious Diseases," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(4), pages 1-14.
    • Handle: RePEc:jas:jasssj:2020-30-2
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    References listed on IDEAS

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    1. Teruhiko Yoneyama & Sanmay Das & Mukkai Krishnamoorthy, 2012. "A Hybrid Model for Disease Spread and an Application to the SARS Pandemic," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-5.
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    Cited by:

    1. Mohamed Abdelkader Souissi & Achraf Ammar & Omar Trabelsi & Jordan M. Glenn & Omar Boukhris & Khaled Trabelsi & Bassem Bouaziz & Piotr Zmijewski & Hichem Souissi & Anis Ben Chikha & Tarak Driss & Hamd, 2021. "Distance Motor Learning during the COVID-19 Induced Confinement: Video Feedback with a Pedagogical Activity Improves the Snatch Technique in Young Athletes," IJERPH, MDPI, vol. 18(6), pages 1-13, March.
    2. Yong Li & Yu Sun & Chengcheng Zeng & Jinxing Li & Yanping Gao & Haisheng Li, 2022. "Research on the Influencing Factors for the Use of Green Building Materials through the Number Growth of Construction Enterprises Based on Agent-Based Modeling," Sustainability, MDPI, vol. 14(19), pages 1-13, October.
    3. Xingwei Li & Jingru Li & Yicheng Huang & Jinrong He & Xiang Liu & Jiachi Dai & Qiong Shen, 2022. "Construction enterprises’ adoption of green development behaviors: an agent-based modeling approach," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    4. Das, Saikat & Bose, Indranil & Sarkar, Uttam Kumar, 2023. "Predicting the outbreak of epidemics using a network-based approach," European Journal of Operational Research, Elsevier, vol. 309(2), pages 819-831.

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