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Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea

Author

Listed:
  • Yunhwan Kim

    (Division of Media Communication, Hankuk University of Foreign Studies, Seoul 02450, Korea)

  • Hohyung Ryu

    (Department of Applied Mathematics, Kyung Hee University, Yongin 446-701, Korea)

  • Sunmi Lee

    (Department of Applied Mathematics, Kyung Hee University, Yongin 446-701, Korea
    Institute of Natural Sciences, Kyung Hee University, Yongin 446-701, Korea)

Abstract

Super-spreading events have been observed in the transmission dynamics of many infectious diseases. The 2015 MERS-CoV outbreak in the Republic of Korea has also shown super-spreading events with a significantly high level of heterogeneity in generating secondary cases. It becomes critical to understand the mechanism for this high level of heterogeneity to develop effective intervention strategies and preventive plans for future emerging infectious diseases. In this regard, agent-based modeling is a useful tool for incorporating individual heterogeneity into the epidemic model. In the present work, a stochastic agent-based framework is developed in order to understand the underlying mechanism of heterogeneity. Clinical (i.e., an infectivity level) and social or environmental (i.e., a contact level) heterogeneity are modeled. These factors are incorporated in the transmission rate functions under assumptions that super-spreaders have stronger transmission and/or higher links. Our agent-based model has employed real MERS-CoV epidemic features based on the 2015 MERS-CoV epidemiological data. Monte Carlo simulations are carried out under various epidemic scenarios. Our findings highlight the roles of super-spreaders in a high level of heterogeneity, underscoring that the number of contacts combined with a higher level of infectivity are the most critical factors for substantial heterogeneity in generating secondary cases of the 2015 MERS-CoV transmission.

Suggested Citation

  • Yunhwan Kim & Hohyung Ryu & Sunmi Lee, 2018. "Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea," IJERPH, MDPI, vol. 15(11), pages 1-17, October.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:11:p:2369-:d:178515
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    References listed on IDEAS

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    1. J. O. Lloyd-Smith & S. J. Schreiber & P. E. Kopp & W. M. Getz, 2005. "Superspreading and the effect of individual variation on disease emergence," Nature, Nature, vol. 438(7066), pages 355-359, November.
    2. Alison P. Galvani & Robert M. May, 2005. "Dimensions of superspreading," Nature, Nature, vol. 438(7066), pages 293-295, November.
    3. Fujie, Ryo & Odagaki, Takashi, 2007. "Effects of superspreaders in spread of epidemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(2), pages 843-852.
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    Cited by:

    1. Seoyun Choe & Hee-Sung Kim & Sunmi Lee, 2020. "Exploration of Superspreading Events in 2015 MERS-CoV Outbreak in Korea by Branching Process Models," IJERPH, MDPI, vol. 17(17), pages 1-14, August.
    2. Yunhwan Kim & Hohyung Ryu & Sunmi Lee, 2021. "Effectiveness of Intervention Strategies on MERS-CoV Transmission Dynamics in South Korea, 2015: Simulations on the Network Based on the Real-World Contact Data," IJERPH, MDPI, vol. 18(7), pages 1-11, March.
    3. Bote Qi & Jingwang Tan & Qingwen Zhang & Meng Cao & Xingxiong Wang & Yu Zou, 2021. "Unfixed Movement Route Model, Non-Overcrowding and Social Distancing Reduce the Spread of COVID-19 in Sporting Facilities," IJERPH, MDPI, vol. 18(15), pages 1-9, August.
    4. Pelayo Martínez-Fernández & Zulima Fernández-Muñiz & Ana Cernea & Juan Luis Fernández-Martínez & Andrzej Kloczkowski, 2023. "Three Mathematical Models for COVID-19 Prediction," Mathematics, MDPI, vol. 11(3), pages 1-16, January.
    5. Antonio López-Quílez, 2019. "Spatio-Temporal Analysis of Infectious Diseases," IJERPH, MDPI, vol. 16(4), pages 1-2, February.

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