Optimizing response strategies of healthcare system in a large-scale disaster

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...

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Main Authors: Tantri, Fredy, Amir, Sulfikar
Other Authors: School of Social Sciences
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/165091
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1650912023-03-19T15:30:22Z Optimizing response strategies of healthcare system in a large-scale disaster Tantri, Fredy Amir, Sulfikar School of Social Sciences Interdisciplinary Graduate School (IGS) Social sciences::Sociology Healthcare Disaster Response 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. Ministry of Education (MOE) National Research Foundation (NRF) Published version This work is an outcome of the Future Resilient Systems project at the Singapore-ETH Centre (SEC), which was funded by the National Research Foundation of Singapore (NRF) under its Campus for Research Excellence and Technological Enterprise (CREATE) programme (FI 370074011). Sulfikar Amir received additional research support from Singapore Ministry of Education’s Academic Research Fund Tier-1 Grant Number RG53/19 (NS). 2023-03-13T02:49:24Z 2023-03-13T02:49:24Z 2022 Journal Article 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 2096-7527 https://hdl.handle.net/10356/165091 10.1016/j.jnlssr.2022.06.001 2-s2.0-85135692381 4 3 288 301 en FI 370074011 RG53/19 (NS) Journal of Safety Science and Resilience © 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/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Social sciences::Sociology
Healthcare
Disaster Response
spellingShingle Social sciences::Sociology
Healthcare
Disaster Response
Tantri, Fredy
Amir, Sulfikar
Optimizing response strategies of healthcare system in a large-scale disaster
description 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.
author2 School of Social Sciences
author_facet School of Social Sciences
Tantri, Fredy
Amir, Sulfikar
format Article
author Tantri, Fredy
Amir, Sulfikar
author_sort Tantri, Fredy
title Optimizing response strategies of healthcare system in a large-scale disaster
title_short Optimizing response strategies of healthcare system in a large-scale disaster
title_full Optimizing response strategies of healthcare system in a large-scale disaster
title_fullStr Optimizing response strategies of healthcare system in a large-scale disaster
title_full_unstemmed Optimizing response strategies of healthcare system in a large-scale disaster
title_sort optimizing response strategies of healthcare system in a large-scale disaster
publishDate 2023
url https://hdl.handle.net/10356/165091
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