{"title":"大规模灾害中医疗系统响应策略的优化","authors":"Fredy Tantri PhD , Sulfikar Amir PhD","doi":"10.1016/j.jnlssr.2022.06.001","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"3 4","pages":"Pages 288-301"},"PeriodicalIF":3.7000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666449622000329/pdfft?md5=31a6776695af8f5d786eb6164653fe6e&pid=1-s2.0-S2666449622000329-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Optimizing Response Strategies of Healthcare System in a Large-scale Disaster\",\"authors\":\"Fredy Tantri PhD , Sulfikar Amir PhD\",\"doi\":\"10.1016/j.jnlssr.2022.06.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":62710,\"journal\":{\"name\":\"安全科学与韧性(英文)\",\"volume\":\"3 4\",\"pages\":\"Pages 288-301\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666449622000329/pdfft?md5=31a6776695af8f5d786eb6164653fe6e&pid=1-s2.0-S2666449622000329-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"安全科学与韧性(英文)\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666449622000329\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"安全科学与韧性(英文)","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666449622000329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
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 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.