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Developing Reusable COVID-19 Disaster Management Plans Using Agent-Based Analysis

Author

Listed:
  • Dedi I. Inan

    (Department of Informatics Engineering, Universitas Papua, Manokwari 98314, Indonesia)

  • Ghassan Beydoun

    (Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney, Ultimo, NSW 2007, Australia)

  • Siti Hajar Othman

    (School of Computing, Faculty of Engineering, University Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia)

  • Biswajeet Pradhan

    (Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney, Ultimo, NSW 2007, Australia
    Center of Excellence for Climate Change Research, King Abdulaziz University, P. O. Box 80234, Jeddah 21589, Saudi Arabia
    Earth Observation Centre, Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia)

  • Simon Opper

    (Surround Australia, Nishi Building, NewActon, Canberra, ACT 2601, Australia)

Abstract

Since late 2019, the COVID-19 biological disaster has informed us once again that, essentially, learning from best practices from past experiences is envisaged as the top strategy to develop disaster management (DM) resilience. Particularly in Indonesia, however, DM activities are challenging, since we have not experienced such a disaster, implying that the related knowledge is not available. The existing DM knowledge written down during activities is generally structured as in a typical government document, which is not easy to comprehend by stakeholders. This paper therefore sets out to develop an Indonesia COVID-19 Disaster Management Plan (DISPLAN) template, employing an Agent-Based Knowledge Analysis Framework. The framework allows the complexities to be parsed before depositing them into a unified repository, facilitating sharing, reusing, and a better decision-making system. It also can instantiate any DISPLAN for lower administration levels, provincial and regency, to harmonise holistic DM activities. With Design Science Research (DSR) guiding these processes, once the plan is developed, we successfully evaluate it with a real case study of the Manokwari Regency. To ensure its effectivity and usability, we also conduct a post-evaluation with two authorities who are highly involved in the Indonesia task force at the regency level. The results from this post-evaluation are highly promising.

Suggested Citation

  • Dedi I. Inan & Ghassan Beydoun & Siti Hajar Othman & Biswajeet Pradhan & Simon Opper, 2022. "Developing Reusable COVID-19 Disaster Management Plans Using Agent-Based Analysis," Sustainability, MDPI, vol. 14(12), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:6981-:d:833329
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    References listed on IDEAS

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    1. Silva, Petrônio C.L. & Batista, Paulo V.C. & Lima, Hélder S. & Alves, Marcos A. & Guimarães, Frederico G. & Silva, Rodrigo C.P., 2020. "COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
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    4. Dedi I. Inan & Ghassan Beydoun & Biswajeet Pradhan, 2022. "Disaster Management Knowledge Analysis Framework Validated," Information Systems Frontiers, Springer, vol. 24(6), pages 2077-2097, December.
    5. Dedi Iskandar Inan & Ghassan Beydoun & Simon Opper, 2018. "Agent-Based Knowledge Analysis Framework in Disaster Management," Information Systems Frontiers, Springer, vol. 20(4), pages 783-802, August.
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