Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/165091
Title: | Optimizing response strategies of healthcare system in a large-scale disaster | Authors: | Tantri, Fredy Amir, Sulfikar |
Keywords: | Social sciences::Sociology | Issue Date: | 2022 | Source: | Tantri, F. & Amir, S. (2022). Optimizing response strategies of healthcare system in a large-scale disaster. Journal of Safety Science and Resilience, 3(4), 288-301. https://dx.doi.org/10.1016/j.jnlssr.2022.06.001 | Project: | FI 370074011 RG53/19 (NS) |
Journal: | Journal of Safety Science and Resilience | Abstract: | Urban infrastructures are invariably constituted by social and technical components whose capacity to withstand crisis is determined by the resilience of their sociotechnical structures. This study aims to apply the principles of sociotechnical resilience in modeling and simulating disaster response in urban areas. Drawing on a case study of Jakarta, Indonesia, our study focuses on the role of hospitals as part of healthcare infrastructure in response to a large-scale disaster. Each hospital is modeled as a coordinated location with a certain amount of resources, primarily in terms of medical staff. We perform sensitivity analysis through Monte Carlo simulations to observe the impacts of various response strategies, disaster severity, and communication duration on system resilience. The results show that centralized systems are generally more suitable for dealing with low disaster severity, while the decentralized strategy performs better during a disaster with worse impacts. Additionally, the time taken for communication and coordination can significantly affect the performance of centralized systems. By simulating various scenarios, parameters, and recovery protocols, the model we developed can help policymakers, city planners, and other stakeholders design proper response strategies suitable to their structural conditions and available resources during a large-scale disaster in urban cities. | URI: | https://hdl.handle.net/10356/165091 | ISSN: | 2096-7527 | DOI: | 10.1016/j.jnlssr.2022.06.001 | Schools: | School of Social Sciences Interdisciplinary Graduate School (IGS) |
Rights: | © 2022 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | IGS Journal Articles SSS Journal Articles |
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1-s2.0-S2666449622000329-main.pdf | 5.16 MB | Adobe PDF | ![]() View/Open |
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