IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i12p6981-d833329.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/12/6981/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/12/6981/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elia, Gianluca & Margherita, Alessandro, 2018. "Can we solve wicked problems? A conceptual framework and a collective intelligence system to support problem analysis and solution design for complex social issues," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 279-286.
    2. 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).
    3. Tongtong Li & Qi Wang & Zheng Xie, 2019. "Disaster response knowledge and its social determinants: A cross-sectional study in Beijing, China," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-10, March.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Dedi I. Inan & Ghassan Beydoun & Siti Hajar Othman, 2023. "Risk Assessment and Sustainable Disaster Management," Sustainability, MDPI, vol. 15(6), pages 1-5, March.
    3. Fattahi, Mohammad & Keyvanshokooh, Esmaeil & Kannan, Devika & Govindan, Kannan, 2023. "Resource planning strategies for healthcare systems during a pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 192-206.
    4. Moritz Kersting & Andreas Bossert & Leif Sörensen & Benjamin Wacker & Jan Chr. Schlüter, 2021. "Predicting effectiveness of countermeasures during the COVID-19 outbreak in South Africa using agent-based simulation," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
    5. Livermore, David & Van Dyne, Linn & Ang, Soon, 2022. "Organizational CQ: Cultural intelligence for 21st-century organizations," Business Horizons, Elsevier, vol. 65(5), pages 671-680.
    6. Li, Jing & Liu, XiaoWen, 2024. "An agent-based simulation model for analyzing and optimizing omni-channel retailing operation decisions," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    7. Shen, Meng & Li, Xiang & Lu, Yujie & Cui, Qingbin & Wei, Yi-Ming, 2021. "Personality-based normative feedback intervention for energy conservation," Energy Economics, Elsevier, vol. 104(C).
    8. Zachariah Sinkala & Vajira Manathunga & Bichaka Fayissa, 2022. "An Epidemic Compartment Model for Economic Policy Directions for Managing Future Pandemic," Papers 2202.05374, arXiv.org.
    9. Mellacher, Patrick, 2020. "COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model," MPRA Paper 103661, University Library of Munich, Germany.
    10. González-Parra, Gilberto & Villanueva-Oller, Javier & Navarro-González, F.J. & Ceberio, Josu & Luebben, Giulia, 2024. "A network-based model to assess vaccination strategies for the COVID-19 pandemic by using Bayesian optimization," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    11. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A., 2022. "Multifractal risk measures by Macroeconophysics perspective: The case of Brazilian inflation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    12. Liu, Hui & Su, Bingbing & Guo, Min & Wang, Jingbei, 2024. "Exploring R&D network resilience under risk propagation: An organizational learning perspective," International Journal of Production Economics, Elsevier, vol. 273(C).
    13. Almiala, Into & Aalto, Henrik & Kuikka, Vesa, 2023. "Influence spreading model for partial breakthrough effects on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    14. Ghassan Beydoun & Sergiu Dascalu & Dale Dominey-Howes & Andrew Sheehan, 2018. "Disaster Management and Information Systems: Insights to Emerging Challenges," Information Systems Frontiers, Springer, vol. 20(4), pages 649-652, August.
    15. Xu, Yuan-Hao & Wang, Hao-Jie & Lu, Zhong-Wen & Hu, Mao-Bin, 2023. "Impact of awareness dissemination on epidemic reaction–diffusion in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
    16. Wood, Aaron D. & Berry, Kevin, 2024. "COVID-19 transmission in a resource dependent community with heterogeneous populations: An agent-based modeling approach," Economics & Human Biology, Elsevier, vol. 52(C).
    17. Daniel K Sewell & Aaron Miller & for the CDC MInD-Healthcare Program, 2020. "Simulation-free estimation of an individual-based SEIR model for evaluating nonpharmaceutical interventions with an application to COVID-19 in the District of Columbia," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-18, November.
    18. Lopolito, Antonio & Caferra, Rocco & Nigri, Andrea & Morone, Piergiuseppe, 2024. "An evaluation of the impact of mitigation policies on health and the economy by managing social distancing during outbreaks," Evaluation and Program Planning, Elsevier, vol. 103(C).
    19. Gabler, Janos & Raabe, Tobias & Röhrl, Klara & Gaudecker, Hans-Martin von, 2021. "Der Effekt von Homeoffice auf die Entwicklung der Covid-19-Pandemie in Deutschland," IZA Standpunkte 100, Institute of Labor Economics (IZA).
    20. Ali M. Al-Shaery & Bilal Hejase & Abdessamad Tridane & Norah S. Farooqi & Hamad Al Jassmi, 2021. "Agent-Based Modeling of the Hajj Rituals with the Possible Spread of COVID-19," Sustainability, MDPI, vol. 13(12), pages 1-13, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:12:p:6981-:d:833329. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.