International journal of disaster risk reduction最新文献

{"title":"An intervention study of adopting a health action model to improve the effectiveness of disaster prevention learning of preschool senior class students","authors":"","doi":"10.1016/j.ijdrr.2024.104872","DOIUrl":"10.1016/j.ijdrr.2024.104872","url":null,"abstract":"<div><div>This study investigates the effect of adopting the health action model (HAM) to improve disaster prevention learning among preschool senior class students. A quasi-experimental design with pre- and post-tests was used to track the extended effects. Convenient sampling selected 60 senior-class students from a private preschool in New Taipei City, divided into experimental and control groups. The HAM was incorporated into 5 earthquake prevention lessons. The effectiveness was assessed using a Checklist of Earthquake-Prevention Learning Effectiveness, analyzed by generalized estimating equations. Results showed significant positive effects of the intervention on earthquake-prevention knowledge (post-test: B = 0.41, p &lt; .001; follow-up test: B = 0.23, p = .001), attitudes (post-test: B = 0.91, p &lt; .001; follow-up test: B = 0.97, p &lt; .001), skills (post-test: B = 1.10, p &lt; .001; follow-up test: B = 1.09, p &lt; .001), intentions (post-test: B = 0.88, p &lt; .001; follow-up test: B = 0.85, p = .001), and behaviors (post-test: B = 0.71, p &lt; .001; follow-up test: B = 0.61, p &lt; .001), with effects lasting for at least 5 weeks. These findings suggest that the intervention significantly enhances earthquake-prevention knowledge, attitudes, skills, intentions, and behaviors, and can serve as a reference for designing preschool earthquake-prevention courses.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multisource geoscience data-driven framework for subsidence risk assessment in urban area","authors":"","doi":"10.1016/j.ijdrr.2024.104901","DOIUrl":"10.1016/j.ijdrr.2024.104901","url":null,"abstract":"<div><div>Land subsidence, especially in developed cities, poses significant risks to human life, social property, and urban sustainability. Taking Liwan District in southern China as an example, this study proposed an acceptable framework for regional land subsidence risk assessment while complying with current national assessment system. With integrating the multi-source geospatial data from remote sensing and various geology surveys into ArcGIS, the subsidence risk assessment was carried out based on the subsidence susceptibility mapping, hazard and vulnerability surveying by using a series of data-driven methods. The results showed that, (<em>i</em>) although not all surface deformations detected by InSAR technology were caused by subsidence, they were instrumental in updating subsidence records; (<em>ii</em>) with the help of spatial correlation analysis using weight evidence as well as multi-source data fusion in high spatial resolution, the Random Forest-based classification models effectively identified the land use types and accurately mapped the land subsidence susceptibility; (<em>iii</em>) the hazard and vulnerability surveying based on a series of newly developed combined weight methods, improved the reliability of risk assessment; (<em>iv</em>) the extremely high- and high-risk areas from the zoning of the land subsidence, provided target areas for further management and prevention of land subsidence. This comprehensive and quantitative assessment framework highlights the need for continued monitoring in subsidence-prone regions, helping to propose strategies for risk mitigation and adaptive planning in urban areas.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictors of risk reduction behavior: Evidence in last-mile communities","authors":"","doi":"10.1016/j.ijdrr.2024.104875","DOIUrl":"10.1016/j.ijdrr.2024.104875","url":null,"abstract":"<div><div>Despite extensive research using Protection Motivation Theory (PMT) to analyze factors influencing protective behaviors during disasters, understanding how last-mile communities in vulnerable contexts—particularly in the Philippines—respond to early warning messages remains limited. This understanding is crucial, as these communities often bear the brunt of extreme weather events. Drawing data from surveys and semi-structured interviews, this study examined the predictors of risk reduction behaviors before and after Super Typhoon Mangkhut in two last-mile communities in Northern Philippines — Cabalitian and Mapita. Regression analysis demonstrated that all threat appraisal variables—perceived vulnerability, perceived severity, and fear—are predictors of risk reduction behaviors before Mangkhut. Coping appraisal variables, specifically response efficacy and self-efficacy, also positively influenced risk reduction action before Mangkhut. Among socio-demographic variables, only gender and age are predictors of risk reduction behaviors, with their influence varying between the two communities. Expanding the application of PMT, prior typhoon experience, trust, and social network strength also positively and significantly influenced risk reduction behaviors before and after Mangkhut. The study identified key infrastructural, institutional, and operational interventions to enhance coping capacity and reduce vulnerability in these communities, alongside policy implications to inform disaster risk reduction strategies and empower local preparedness efforts.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative risk assessment for overtopping of earth-fill dams in Japan using machine learning algorithms","authors":"","doi":"10.1016/j.ijdrr.2024.104892","DOIUrl":"10.1016/j.ijdrr.2024.104892","url":null,"abstract":"<div><div>Earth-fill dams serve as crucial agricultural structures in Japan and act as buffers against flooding. However, their failure often tends to cause even greater downstream damage. Consequently, there is an urgent need for a quantitative assessment of the risks to earth-fill dams posed by disasters. The current detailed method of assessment is complicated, labour-intensive, and costly; hence, constructing risk surrogate models will greatly reduce the workload. This study employs two machine learning methods, GPR (Gaussian Process Regression) and XGBoost (eXtreme Gradient Boost), to develop surrogate models for assessing the damage cost and overtopping probability for 70 earth-fill dams in Okayama and Hiroshima prefectures, Japan. The predictive performance of each model was quantified by comparing the results against those of the detailed method. From the results, XGBoost demonstrates superior performance compared to GPR based on the comparison of coefficient of determination (R²) and root mean square error (RMSE). To clarify the extent to which the variables influence the XGBoost model, the SHapley Additive exPlanations (SHAP) algorithm was implemented. It offers an efficient and interpretable avenue for earth-fill dam risk assessments.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seismic performance and recovery of medical infrastructure in Mexico City related to the September 19, 1985 and 2017 earthquakes","authors":"","doi":"10.1016/j.ijdrr.2024.104886","DOIUrl":"10.1016/j.ijdrr.2024.104886","url":null,"abstract":"<div><div>To date, the September 19, 1985 Michoacán (<em>M</em>_<em>s</em> = 8.1) and the September 19, 2017 Puebla-Morelos (<em>M</em>_<em>w</em> = 7.1) earthquakes have been the most devastating seismic events in Mexico City. During the 1985 earthquake, 13 important public hospital buildings collapsed or were demolished and 5800 hospital beds were lost. During the 2017 earthquake, 85 buildings of the medical sector were disturbed, two major public hospital were demolished and 1147 hospital beds were affected. In this paper, the author concentrates both in reviewing what occurred during the 1985 earthquake, and in reporting what it has been observed for the 2017 earthquake. From the structural viewpoint, the observed damage is discussed in relationships to: a) seismic codes, b) spectral demands, b) structural irregularities, c) soil settlements, d) tilting, e) structural pounding and, f) deterioration. The observed damaged inventory is also put into perspective with respect to the approximate number of medical facilities that are available in Mexico City. An instantaneous drop of seismic resilience for this sector is crudely assessed. Finally, the progress on the recovery process or adaptive resilience is discussed. Fortunately, most of the main hospitals in Mexico City were not severely damaged, and that it was why most of them and the hospital bed capacity in Mexico City previous to the 2017 earthquake was able to be recovered on time to attend the Covid-19 pandemic which affected Mexico since early 2020.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Analysis of Disaster Resilience Research: A Bibliometric Study a manuscript for submission as a Review Article to International Journal of Disaster Risk Reduction by","authors":"","doi":"10.1016/j.ijdrr.2024.104896","DOIUrl":"10.1016/j.ijdrr.2024.104896","url":null,"abstract":"<div><div>We analyzed the global disaster resilience research literature to advance understanding of its geographical context. A key objective was to map the variation in disaster research resilience activity to identify hotspots and areas of less activity. The motivation is to reveal regional imbalances in resilience research and collaboration to contribute to the global narrative regarding marginalized regions. The methodology involves an in-depth examination of Web of Science (WoS) bibliographic data from 2010-2020, using keywords to develop a comprehensive perspective of disaster resilience research. Additionally, the study incorporates empirical data from the Emergency Events Data (EM-DAT) maintained by the Centre for Research on the Epidemiology of Hazards at the Université Catholique de Louvain (CRED/UCLouvain) to provide context on the impact of disasters. A key innovation of this study is the Disaster Resilience Research Score (DRRS), a quantifiable metric to evaluate the state of disaster resilience research globally by country. The DRRS considers publications, citations, and institutional involvement to provide a well-rounded view of each country's contributions to the field. The results highlight the leading role in disaster resilience research of countries including the United States, Australia, the United Kingdom, Germany, and Italy. However, there is a notable lack of research activity in countries such as Ecuador, Algeria, Kenya, Cambodia, and Myanmar, which also exhibit relatively high vulnerability to environmental hazards. Our findings indicate that countries identified as resilience hotspots predominantly collaborate within their country. This study highlights opportunities for strengthening collaborations between resilience research hotspots and locations less represented in the resilience research literature. It underscores the importance of identifying hot and cold spots to direct future research and foster a more equitable and sustainable response to climate change and hazards.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A bayesian approach for the continuous monitoring of the prediction of the physiological evolution of a crisis victim: A decision support system","authors":"","doi":"10.1016/j.ijdrr.2024.104890","DOIUrl":"10.1016/j.ijdrr.2024.104890","url":null,"abstract":"<div><div>Catastrophic events like earthquakes demand innovative tools for crisis management. Mathematical modeling and decision support systems (DSSs) have proved crucial for understanding, predicting and mitigating disaster impact. The quantification of complex phenomena through probabilistic models, to estimate the likelihood of events, provides actionable insights that are essential for disaster risk reduction (DRR).</div><div>The present work stems from research conducted within the framework of the Search &amp; Rescue (S&amp;R) project (H2020-SU-SEC-2019), in particular from the development of the PHYSIO DSS module, the medical component of the S&amp;R Decision Support System (DSS). The PHYSIO DSS focuses on predicting the physiological evolution of crisis victims: using a Bayesian approach, it incorporates real-time field observations to forecast patient conditions. This enables the prediction of the evolution of physiological compensation, allowing efficient resource allocation and timely interventions. By providing real-time insights into victim severity, PHYSIO DSS empowers medical personnel to prioritize treatment, potentially saving lives. Its adaptability allows integration into different platforms, from crisis management systems to apps to personal health devices.</div><div>This tool has the potential to substantially enhance emergency response capability and overall disaster resilience by offering real-time, data-driven decision support.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the collaborative relationship of task-driven urban earthquake emergency organizations","authors":"","doi":"10.1016/j.ijdrr.2024.104887","DOIUrl":"10.1016/j.ijdrr.2024.104887","url":null,"abstract":"<div><div>Earthquake emergency response is a complex process, and a large number of tasks are involved in the process of urban earthquake emergency response. To further study the collaborative relationship between organisations in the city-level emergency collaboration network driven by different emergency tasks, this study first constructs a task–organisation relationship framework and explores the collaborative mechanism of organisations driven by tasks. Then, the co-expression analysis was used to analyse the degree of correlation between task-driven emergency organisations. Finally, considering the influence of tasks on the degree of inter-organisational collaboration, this study constructs a task-driven weighted directed emergency organisation collaboration network. Social network analysis was used to reveal the structural attributes of the task-driven organisational collaboration network, the collaborative characteristics among organisations in the network, and the structural positions of organisations in the collaborative network. It is found that the task-driven earthquake emergency collaboration network was relatively loose, and there were small groups with close collaboration in the network. Most organisations in these small groups are in the same task module, and their tasks are similar. Commanders in the task execution process are usually at the core of the network, and these organisations are usually the main coordinators of the overall emergency collaboration and task module networks. These findings can improve our understanding of earthquake emergency organisational collaboration relationships and inspire the optimisation of urban earthquake emergency management.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vulnerability simulation and evaluation of urban metro operation system: A hybrid structural equation model with system dynamics approach","authors":"","doi":"10.1016/j.ijdrr.2024.104889","DOIUrl":"10.1016/j.ijdrr.2024.104889","url":null,"abstract":"<div><div>To effectively identify the influence factors of urban metro operation system (UMOS) vulnerability and research the dynamic evolution process of system vulnerability, ensuring the long-term safety of UMOS, a hybrid method integrating structural equation model (SEM) and system dynamic (SD) is proposed to evaluate the UMOS vulnerability. The vulnerability evaluation indexes system of UMOS is established by questionnaire design, which includes four dimensions of personnel, equipment, management and environment. The effectiveness of the method is verified by taking Wuhan metro system in China as an example. The results indicate that (1) The influence of personnel, equipment, management and environment factors on UMOS is 30.2 %, 27.6 %, 21.6 % and 20.6 %, respectively. (2) The passenger flow level and emergency rescue system level have the greatest influence on the vulnerability of UMOS via sensitivity analysis. (3) Extreme weather conditions have the greatest impact on the environment sub-system vulnerability, which in turn affects the UMOS. Hence, the proposed method herein can simulate the long-term vulnerability of the entire UMOS and formulate corresponding improvement measures, thereby achieving sustainable transportation development.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing a multi-level european-wide composite indicator to assess vulnerability dynamics across time and space","authors":"","doi":"10.1016/j.ijdrr.2024.104885","DOIUrl":"10.1016/j.ijdrr.2024.104885","url":null,"abstract":"<div><div>The escalating frequency of extreme climatic events and ongoing urbanisation expose European communities to increasing disaster risks, which are determined not only by the hazardous events themselves, but also by the exposure and vulnerability to these hazards. Consequently, effective risk management strategies cannot overlook a comprehensive understanding of the factors influencing vulnerability of the communities. This paper addresses this need by presenting a European-wide framework for the development of a Vulnerability Index (VI) that evaluates vulnerability at both national and subnational scales. Adopting a multi-dimensional and multi-level approach, the VI captures socio-economic, political, environmental, and physical factors contributing to community resilience. A standardised, supranational methodology is employed, providing harmonised cross-country information and time series data for vulnerability and its underlying indicators. This comprehensive assessment facilitates the understanding of socio-economic dynamics, enabling the formulation of targeted policy actions at both country and subnational levels. By offering insights into current vulnerability trends, the VI underlines the importance of governance, economic factors, and disaster preparedness in reducing vulnerability at different administrative levels, while highlighting the role of social factors, such as poverty and social exclusion, in community vulnerability at sub-regional levels.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":null,"pages":null},"PeriodicalIF":4.2,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}