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

Dedi I. Inan, Ghassan Beydoun, Siti Hajar Othman, Biswajeet Pradhan and Simon Opper
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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
Simon Opper: Surround Australia, Nishi Building, NewActon, Canberra, ACT 2601, Australia

Sustainability, 2022, vol. 14, issue 12, 1-22

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.

Keywords: COVID-19; disaster management; agent-based models; disaster management knowledge; knowledge analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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