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Developing reusable COVID-19 disaster management plans using agent-based analysis

Dedi I. Inan, Dedi I. Inan and Beydoun, Ghassan and Othman, Siti Hajar and Pradhan, Biswajeet and Opper, Simon (2022) Developing reusable COVID-19 disaster management plans using agent-based analysis. Sustainability, 14 (12). pp. 1-22. ISSN 2071-1050

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Official URL: http://dx.doi.org/10.3390/su14126981

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.

Item Type:Article
Uncontrolled Keywords:agent-based models, COVID-19, disaster management, disaster management knowledge, knowledge analysis
Subjects:T Technology > T Technology (General) > T58.6-58.62 Management information systems
Divisions:Computing
ID Code:104345
Deposited By: Yanti Mohd Shah
Deposited On:04 Feb 2024 04:06
Last Modified:04 Feb 2024 04:06

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