Mohamadali Morshedi , Makarand Hastak , Satish V. Ukkusuri , Seungyoon Lee
{"title":"量化灾后社区福祉:哈维飓风案例研究","authors":"Mohamadali Morshedi , Makarand Hastak , Satish V. Ukkusuri , Seungyoon Lee","doi":"10.1016/j.ijdrr.2024.104903","DOIUrl":null,"url":null,"abstract":"<div><div>Natural hazards such as hurricanes affect various aspects of the community members’ lives and their post-disaster well-being by causing significant disruptions in the key community activities in the immediate recovery phase. Furthermore, natural hazards leave behind short-term socio-economic impacts such as stress, anxiety, huge recovery expense, and lack of affordable housing. There is a need for incorporating both immediate and short-term impacts of natural hazards when measuring disaster recovery. This study aims to address this need by introducing community well-being as the metric for the recovery of communities from natural disasters. From this perspective, community resilience is defined as the capability of community to reach its pre-disaster state of well-being, in a timely and efficient manner. The study leverages Bottom-Up Spillover Theory and the existing literature to introduce a community well-being model. This model quantifies how the functionality of infrastructure systems can affect various aspects of community well-being based on 6 domains, 17 sub-domains, and 51 indicators. The indicators were quantified using survey data and 211-call data for the City of Houston, and data on the impact of Hurricane Harvey at the zip code level. The results showed that various dimensions of well-being were affected heterogeneously and followed different recovery patterns. The proposed framework can serve decision makers as a dashboard for identifying the well-being domains and sub-domains that should be addressed to enhance post-disaster well-being in the immediate-to short-term. Furthermore, the study introduces the phone call data as an inexpensive and timely replacement for multiple rounds of survey questionnaires for quantifying community well-being.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"114 ","pages":"Article 104903"},"PeriodicalIF":4.2000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying post-disaster community well-being: A case study of Hurricane Harvey\",\"authors\":\"Mohamadali Morshedi , Makarand Hastak , Satish V. 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The study leverages Bottom-Up Spillover Theory and the existing literature to introduce a community well-being model. This model quantifies how the functionality of infrastructure systems can affect various aspects of community well-being based on 6 domains, 17 sub-domains, and 51 indicators. The indicators were quantified using survey data and 211-call data for the City of Houston, and data on the impact of Hurricane Harvey at the zip code level. The results showed that various dimensions of well-being were affected heterogeneously and followed different recovery patterns. The proposed framework can serve decision makers as a dashboard for identifying the well-being domains and sub-domains that should be addressed to enhance post-disaster well-being in the immediate-to short-term. 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Quantifying post-disaster community well-being: A case study of Hurricane Harvey
Natural hazards such as hurricanes affect various aspects of the community members’ lives and their post-disaster well-being by causing significant disruptions in the key community activities in the immediate recovery phase. Furthermore, natural hazards leave behind short-term socio-economic impacts such as stress, anxiety, huge recovery expense, and lack of affordable housing. There is a need for incorporating both immediate and short-term impacts of natural hazards when measuring disaster recovery. This study aims to address this need by introducing community well-being as the metric for the recovery of communities from natural disasters. From this perspective, community resilience is defined as the capability of community to reach its pre-disaster state of well-being, in a timely and efficient manner. The study leverages Bottom-Up Spillover Theory and the existing literature to introduce a community well-being model. This model quantifies how the functionality of infrastructure systems can affect various aspects of community well-being based on 6 domains, 17 sub-domains, and 51 indicators. The indicators were quantified using survey data and 211-call data for the City of Houston, and data on the impact of Hurricane Harvey at the zip code level. The results showed that various dimensions of well-being were affected heterogeneously and followed different recovery patterns. The proposed framework can serve decision makers as a dashboard for identifying the well-being domains and sub-domains that should be addressed to enhance post-disaster well-being in the immediate-to short-term. Furthermore, the study introduces the phone call data as an inexpensive and timely replacement for multiple rounds of survey questionnaires for quantifying community well-being.
期刊介绍:
The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international.
Key topics:-
-multifaceted disaster and cascading disasters
-the development of disaster risk reduction strategies and techniques
-discussion and development of effective warning and educational systems for risk management at all levels
-disasters associated with climate change
-vulnerability analysis and vulnerability trends
-emerging risks
-resilience against disasters.
The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.