Disaster Management Organizations Research Articles

Possibilities for Improving the Technical Equipment of Disaster Management Mobile Command Points

The use of disaster management command centres is typically implemented in a static way, however, the experiences of the past period have shown that for their effective operation, it is necessary to use solutions that enable the monitoring of events, as well as rapid relocation and deployment. An obvious solution for creating the aforementioned capabilities is the use of mobile command centres to support driving groups. Currently, the professional disaster management organisation has several devices that can be used as mobile command points, but their capacity does not allow the work of larger teams. The purpose of this thesis is to examine capabilities, with the implementation of which both the capacity of the disaster management organisation and the effectiveness of the interventions can be increased, taking into account domestic and international development trends.

Post-disaster damage and loss assessment in the Iranian healthcare sector: a qualitative interview study

BackgroundAccurate post-disaster damage and loss assessment is critical for the success of subsequent recovery programs. A comprehensive and systematic damage and loss assessment process involves evaluating the physical damage and financial impact of an event on individuals, communities, and assets. To ensure effective recovery, the various components and entities included in the program must be developed appropriately and efficiently. This study aimed to identify the components and entities of the Iranian healthcare sector’s post-disaster damage and loss assessment program.MethodsA qualitative study employing purposive sampling and semi-structured individual interviews was conducted with 18 participants between October 2022 and July 2023, with continuing until data saturation was achieved. Data collection involved semi-structured interviews and observational notes with experts, including representatives from the National Disaster Management Organization (NDMO), the Iranian Red Crescent Society, and the Disaster Risk Management Department of the Ministry of Health and Medical Sciences Universities. The interviews were conducted in the workplace of the participants. Thematic analysis, a conventional qualitative method, was employed for the analysis of the data. Following the transcription of the recorded interviews, the initial codes were extracted, reviewed for accuracy, and classified.ResultsThe results of this study are based on the insights and experiences of a diverse group of qualified experts in their respective fields. The findings were analysed and classification into ten main themes, 29 sub-themes, and 1,058 codes. The main themes were key concepts and principles of assessment; assessment stages; health system measures in assessment; roles and responsibilities; team composition; information and communication; coordination and collaboration; data collection and analysis; assessment tools and methods; and reporting, documentation, and recommendations.ConclusionAn understanding of key concepts and principles enables stakeholders to respond effectively to disasters, make informed decisions, and facilitate recovery and reconstruction efforts.

Utilizing Social Media and Crowdsourcing for Crisis Management and Communication: proposing an Integrative Framework

Utilizing social media and crowdsourcing (SMCS) in crisis management is crucial for improving communication and citizen engagement. However, practitioners working in crisis management organizations often face challenges when translating the outcomes of scientific research into actionable knowledge. To aid disaster management organizations, a comprehensive set of resources including practical tools, guidelines, and use examples are necessary. This will help response organizations to integrate the different components of SMCS coherently and consistently in their organizations and to promote disaster resilience for different users. An integrative Framework, developed by the authors as part of the EU-funded Horizon 2020 project, LINKS – strengthening links between technologies and society for European disaster resilience, serves such resources. This paper presents how this Framework came into being and describes its main components. It then provides a case study from the Netherlands, focusing on the scenario of industrial, chemical hazards, to illustrate how the Framework was actually used.

Leveraging domain-adapted transformer based models for disaster-specific tweet classification

Social media platforms play vital roles in disseminating information during crisis situations. Many rescue agencies, media outlets, and volunteers regularly monitor this data to identify and analyze disasters, ultimately mitigating life risks. However, effectively categorizing these messages based on information types is crucial for enhancing the situational awareness of emergency responders. This paper addresses the challenge of analyzing informal crisis-related social media texts by classifying disaster event tweets into 10 humanitarian categories associated with 19 major natural disaster events. We fine-tune seven state-of-the-art pre-trained transformer models and compare their performance with the recently introduced domain-specific models, i.e., CrisisTransformers. We empirically found that CrisisTransformers outperform seven strong baseline transformer models in classifying disaster-specific tweets from the HumAID dataset, achieving a macro-averaged F1 score of 0.77. Our work contributes to the crisis computing field by improving the classification of disaster-related tweets and enhancing the capabilities of emergency responders and disaster management organizations.

Categorization of tweets for damages: infrastructure and human damage assessment using fine-tuned BERT model.

Identification of infrastructure and human damage assessment tweets is beneficial to disaster management organizations as well as victims during a disaster. Most of the prior works focused on the detection of informative/situational tweets, and infrastructure damage, only one focused on human damage. This study presents a novel approach for detecting damage assessment tweets involving infrastructure and human damages. We investigated the potential of the Bidirectional Encoder Representations from Transformer (BERT) model to learn universal contextualized representations targeting to demonstrate its effectiveness for binary and multi-class classification of disaster damage assessment tweets. The objective is to exploit a pre-trained BERT as a transfer learning mechanism after fine-tuning important hyper-parameters on the CrisisMMD dataset containing seven disasters. The effectiveness of fine-tuned BERT is compared with five benchmarks and nine comparable models by conducting exhaustive experiments. The findings show that the fine-tuned BERT outperformed all benchmarks and comparable models and achieved state-of-the-art performance by demonstrating up to 95.12% macro-f1-score, and 88% macro-f1-score for binary and multi-class classification. Specifically, the improvement in the classification of human damage is promising.

Occupational Health and Safety Challenges Faced National Disaster Management Personnel

This study aims to look into how health and safety concerns affect the job performance of National Disaster Management Organization (NADMO) personnel in the Bono Region. Hazards, poor training, and psychological well-being are significant factors determining the efficiency of disaster response activities in the study. The study adopts a descriptive (case study) research design, emphasizing the importance of a comprehensive plan to solve these difficulties. The target population consists of 127 people from the municipal offices of Sunyani East, Wenchi, and Berekum. Purposive and simple random sampling selects 75 respondents from various departments and units. Self-administered questionnaires containing open-ended and closed-ended items are used to collect data. The data suggest that health concerns may have an impact on coworkers’ job performance among those who have had accidents. However, statistical significance is weak. Positive management relationships following fatal accidents have a minor correlation with better NADMO results, underlining the need for additional factors in the model. The relevance value supports the suggestion of organizing periodic health and safety lectures as an intervention to alleviate difficulties. Among the recommendations prioritizing comprehensive training, guaranteeing access to Personal PSafety equipment, addressing psychological well-being, and increasing organizational support.

From disregard to integration: Facets of disaster governance in times of changing forms of volunteering

The article analyzes diverse responses to changing forms of disaster volunteering in Germany. Based on an assessment of governing techniques of disaster management and civil protection organizations and authorities (DMOs) towards DMO-external volunteering, the article discusses, how changes in the voluntary system and the rise of new actors in the field are problematized, how entrenched practices are challenged and new techniques for collaboration are developed and how roles, responsibilities and identities are formed, questioned, and altered. It outlines four emerging research fields surrounding legitimacy, competition, democratization of disaster response and responsibilization and reflects upon calls to consider disaster (risk) governance as shared responsibility between governments and other stakeholders, as demanded in the Sendai Framework for Disaster Risk Reduction 2015–2030.

Disaster education: empowering resilience and mitigating PTSD in disaster-prone areas of China

The people of disaster-affected communities are suffering from post-traumatic stress disorder (PTSD) due to the adverse effects of natural disasters. Education about disasters has become a possible strategy for fostering resilience and easing PTSD symptoms. This study intends to investigate the moderating roles of social support and disaster experiences on the relationships between disaster education, psychological resilience, and PTSD in disaster-prone regions of Southwest China. This study used Disaster Education Evaluation Scale, Psychological Resilience Scale (CD-RISC), Social Support Rating Scale (SRSS), event intensity Scale and Post Traumatic Stress Disorder Self-Rating Scale (PTSD-SS), surveyed 712 residents in Yunnan, Guizhou, Sichuan and other areas where natural disasters frequently occur in Southwest China. The research findings indicate that there is a negative association between disaster education and PTSD. The association is influenced by the presence of improved psychological resilience, which acts as a mediator. Additionally, it was discovered that disaster events positively moderated the relationship between psychological resilience and PTSD while social support negatively moderated it. Resilience has a noteworthy role as a substantial mediator, highlighting its crucial function in mitigating the detrimental consequences of catastrophes and amplifying the beneficial outcomes of disaster education. These results imply that building psychological resilience, which might reduce PTSD symptoms in people living in disaster-prone regions, is a critical part of disaster education. The strength of the catastrophic event and social support are other factors that affect how psychological resilience and PTSD are related. The research argues that disaster education is crucial for strengthening community resilience and reducing PTSD symptoms in at-risk areas. To increase psychological resilience and lessen PTSD in high-risk locations, policymakers and disaster management organizations should emphasize disaster education initiatives and strengthen social support network.

Influencing factors on building and improving social trust in emergency and disaster relief efforts: a systematic review

Purpose This study aims to review the results of relevant studies to shed light on social trust-building in different contexts and the factors that affect it in disaster risk management. Design/methodology/approach This systematic review was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses model. The study keywords were searched for in PubMed, Scopus and Web of Science databases on August 2021. The inclusion criteria were English-written articles published in social trust and disaster relief efforts. Exclusion criteria were lack of access to the full text and article types such as nonoriginal articles. Findings Out of 1,359 articles found, 17 articles were included in the final analysis using four general categories: six articles on the role of local government in trust-building (local governments), five articles on the role of social media in trust-building (social media), four articles on the role of social capital in trust-building (social capital) and two articles on the importance of community participation in trust-building (community participation). Originality/value Understanding the role of social trust and the factors which influence it will help the development of community-based disaster risk management. Therefore, disaster management organizations and other relief agencies should take the findings of this study into account, as they can help guide policymaking and the adoption of strategies to improve public trust and participation in comprehensive disaster risk management. Further studies recommended understanding people’s experiences and perceptions of social trust, relief and disaster preparedness.

Monitoring and prediction of landslide-related deformation based on the GCN-LSTM algorithm and SAR imagery

A key component of disaster management and infrastructure organization is predicting cumulative deformations caused by landslides. One of the critical points in predicting deformation is to consider the spatio-temporal relationships and interdependencies between the features, such as geological, geomorphological, and geospatial factors (predisposing factors). Using algorithms that create temporal and spatial connections is suggested in this study to address this important point. This study proposes a modified graph convolutional network (GCN) that incorporates a long and short-term memory (LSTM) network (GCN-LSTM) and applies it to the Moio della Civitella landslides (southern Italy) for predicting cumulative deformation. In our proposed deep learning algorithms (DLAs), two types of data are considered, the first is geological, geomorphological, and geospatial information, and the second is cumulative deformations obtained by permanent scatterer interferometry (PSI), with the first investigated as features and the second as labels and goals. This approach is divided into two processing strategies where: (a) Firstly, extracting the spatial interdependency between paired data points using the GCN regression model applied to velocity obtained by PSI and data depicting controlling predisposing factors; (b) secondly, the application of the GCN-LSTM model to predict cumulative landslide deformation (labels of DLAs) based on the correlation distance obtained through the first strategy and determination of spatio-temporal dependency. A comparative assessment of model performance illustrates that GCN-LSTM is superior and outperforms four different DLAs, including recurrent neural networks (RNNs), gated recurrent units (GRU), LSTM, and GCN-GRU. The absolute error between the real and predicted deformation is applied for validation, and in 92% of the data points, this error is lower than 4 mm.

Reducing the Risk of Fire Outbreak in Compliance with Fire Safety Regulations in Ghana

Fire outbreak is a disturbing phenomenon that has over the years destroyed market centers. There is growing knowledge that the persistence of these fire disasters is as a result of people’s noncompliance with fire safety regulations. This study therefore contributes to the search for solutions by assessing stakeholders’ capacity to manage fires, While creating the individual trader’s awareness and knowledge on what they need to do against fire risk and disasters. The study is cross-sectional and involved 140 traders and three institutions: National Disaster Management Organization, Kumasi Metropolitan Assembly and Ghana National Fire Service. A systematic sampling technique was used in selecting 140 respondents from a total of 386 with the help of the Sloving technique. The study revealed that traders in the Kumasi Central Market were unaware of what they need to do in case of fire outbreak. It was also shown that, both traders and firefighting institutions do not comply with the safety measures to preventing fire outbreaks. Again it was revealed that haphazard development within the city center serves as a major hindrance for effective fire prevention and control. Based on findings, the study recommends intensive education of traders on how to prevent fire and how to use firefighting tools in case of fire disasters. The study further recommends the review and enforcement of fire prevention codes and regulations to ensure compliance by traders. Keywords: Fire, Safety, Safety measures Risk, Firefighting, Fire training DOI: 10.7176/JEP/14-13-07 Publication date: May 31 st 2023

Utilizing AEMS (Assess-EOP-Map-Simulate) Algorithm to Assess and Spatially Link Prehospital Emergency Medical Services Resources in Road-Traffic Mass Casualty Incidents in Kumasi, Ghana

Introduction:Due to the high number of road traffic accidents with acute injuries and fatalities–particularly in Mass Casualty Incidents (MCI) in low-resource urban sub-Saharan African cities–research was undertaken to create an evidence-based algorithm that could be used to assess and geospatially link EMS needs in Kumasi, Ghana, to trauma resources. Our examination showed that non-MCI fatalities was approximately 2.5%, however, MCI fatalities were found to be 1.8 times higher–at 4.3%, indicating significant opportunities in the planning, preparedness, care, and transport among MCI patient management.Therefore, several studies (funded through Fulbright-Fogarty and Fulbright Specialist programs), supported the development of the A-E-M-S (Assess-EOP-Map-Simulate) Medical Mass Casualty Algorithm that began networking accident ‘hotspots’ to existing trauma-level capabilities and surge capacity competencies in eight specified Kumasi hospitals. This low-cost response model promises to be an innovative alternative to long-term infrastructure development and high-priced resource distributions. Use of GIS and UAV drones allowed response systems to geospatially locate, classify, shift, and/or augment resources as needed in conjunction with hotspots.Method:Sample sizes were averaged at 295 for all patients' ages, with only a sample size of 292 for adults at 95% confidence intervals, and a standard deviation of 0.5. A total of 300 road-traffic accident victims were collected at KATH A&E in February-May, 2017, utilizing handheld devices by four researchers 24/7 daily.Results:Our examination showed that non-MCI fatalities were approximately 2.5%, however, MCI fatalities were found to be 1.8 times higher–at 4.3%, indicating significant opportunities in the planning, preparedness, care, and transport among MCI patient management.Conclusion:To date–and in partnership with Kwame Nkrumah University of Science and Technology, Komfo Anokye Teaching Hospital, Ghana Medical Council, Health Services, National Disaster Management Organization, and others–over 306 Ghanaian healthcare providers from 80 different facilities have been trained in the AEMS program.

Flood vulnerability analysis using different aggregation frameworks across watersheds of Ardabil province, northwestern Iran

Flood-vulnerable-area selection could be interpreted as an intricate multiple-criteria decision-making (MCDM) problem. Lacking systematic flood vulnerability maps in Iran usually leaves the National Disaster Management Organization and provincial authorities to rely on limited knowledge to inform their emergency actions. Therefore, the present study was conducted as pioneer research in flood problematization for solving disaster issues that have not been adequately considered in the country. To obtain a more trustworthy and safer decision, a complex set of multivariate flood vulnerability assessments was done for 26 watersheds of Ardabil province using the novel-ensemble MCDM frameworks. Towards this, the complex proportional assessment of alternatives (COPRAS) and the UK Department for International Development (DFID) approach was integrated with widely used weighting methods of Shannon's entropy (Entropy) and analytical hierarchy process (AHP). Finally, four different aggregation frameworks of COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP were developed and compared based on 19 criteria and three factors (exposure, sensitivity, and resilience). The flood vulnerability was obtained as 0.70 ± 0.13, 0.66 ± 0.18, 0.17 ± 0.10, and 0.20 ± 0.15, respectively, based on COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP. As can be seen, higher values were estimated according to COPRAS-based frameworks rather than DFID-based frameworks, except for resilience. The top-ranked watersheds in terms of exposure (i.e., Mashiran) and sensitivity (i.e., Samian) produced by aggregation frameworks match entirely. However, the top-ranked watersheds based on resilience and flood vulnerability slightly mismatch among the used aggregation's frameworks. These findings help the responsible authorities for natural disaster risk reduction to promote sustainable development processes and equitable access to financial resources.

The dynamics of cross-sector collaboration in disasters

PurposeThis study examines challenges to cross-sector collaboration in disasters. The authors use Malaysian flooding as the context for the study and offer a framework to understand different types of collaborators in disaster settings.Design/methodology/approachData were collected with semi-structured interviews, complemented with secondary data from government documents and news reports. The authors interviewed a total of 30 participants including six disaster aid recipients and 24 strategic and operational participants from 12 disaster management organizations. Thematic analysis was conducted including two cycles of coding, memoing and constant comparisons.FindingsThe authors present two key theoretical contributions: key barriers to cross-sector collaboration and a typology of collaboration in disasters. Key barriers include leadership approach and central vs local decision-making, differing levels of motivation to collaborate and the organizations' ability to collaborate in disasters. Despite these barriers, collaboration does occur in disaster settings. The authors suggest that the forms of collaboration may be driven primarily by differing motivations to collaborate and differing perceptions of others’ ability to collaborate, resulting in four types of collaboration: (1) enthusiastic, (2) mandate-driven, (3) reluctant and (4) non-collaboration.Originality/valueThe authors show that although the command-and-control model was dominant, organizations also attempted to improve disaster management efficacy through collaborative approaches. Central institutional agencies and their wider external partners are capable of using cross-sector collaboration as a strategy to tackle the complex problems post-disaster. However, pre-disaster relationship building will likely help organizations to collaborate more effectively when a disaster occurs.

Flood related depression and replacement of damaged household items

Despite the extensive literature on flood-related depression, depression severity for individual damaged household items is unclear. Furthermore, the effect of depression levels on the time taken to replace damaged household items is equivocal. To resolve these research gaps, this study employed a questionnaire to collect data from slum dwellers in Old Fadama and analysed using a Wilcoxon signed-rank test and stepwise multinomial regression techniques. The findings revealed that flood-affected persons ranked depression levels associated with damaged furniture/chairs/tables/sofa more severe than other household items such as Electronic: Fan/Iron, Electronic: Fridges/deep freezers/coolers/food storage, Beds/ Mattresses/other sleeping mats. Damaged items considered to have moderate cost generated mild depression levels while affordable items were less likely to generate severe depression. Concerning the replacement of damaged items, younger respondents, with lower income, in rent-free apartments and with low depression levels replaced damaged items after a year and more. The study recommends that National Disaster Management Organisation [NAMDO] should include the provision of psychological assistance to flood victims and spearhead the establishment of a national flood insurance policy, while insurers support with packages for slum areas in Ghana.

Perspectives on factors that influence local communities’ vulnerability to coastal floods in Ketu South Municipality of Ghana

Vulnerability studies in relation to coastal floods in Ghana have generally focused on assessing the biophysical vulnerability and flood hazard modelling - rather than exploring the combination of both biophysical and socioeconomic factors that affect the vulnerability of coastal communities to floods. In response, this study aimed to explore the factors that influence the vulnerability of coastal communities in Ketu South Municipality, Ghana, to floods. These communities remain vulnerable to coastal flood events from storm surges, high tidal waves, lagoon overflow and heavy rainfall. However, the local conditions that make these communities vulnerable is poorly understood. The study used data from eight (8) in-depth interviews, nine (9) Focus Group Discussions and 354-household survey to explore local vulnerability factors in the study area. Results show that factors such as low land elevation, inadequate sea defence structures, high flood frequency, large flood extent, long flood duration, flood impacts, are among the exposure factors influencing vulnerability in the study area. It also shows that socioeconomic factors; such as weak demographic groups, low-income levels, low level of education, and some local adaptation measures plus external flood relief supports from National Disaster Management Organization (NADMO) influence the vulnerability of the communities. The result further revealed salt production activities, and relocating to flood prone areas, as well as rise in coastal water table and rapid shoreline erosion are the observable vulnerability factors in the study area whiles gender was a significant social factor influencing flood preparedness. These results can be useful for flood disaster management programs.

BIM–GIS Integrated Utilization in Urban Disaster Management: The Contributions, Challenges, and Future Directions

In the 21st Century, disasters have severe negative impacts on cities worldwide. Given the significant casualties and property damage caused by disasters, it is necessary for disaster management organizations and the public to enhance urban disaster management. As an effective method, BIM (Building Information Modeling)–GIS (Geographic Information System) integration can significantly improve urban disaster management. Despite the significance of BIM–GIS integration, there is rarely the adoption of BIM–GIS integration in urban disaster management, which significantly hinders the development of the quality and efficiency of urban disaster management. To enhance urban disaster management and reduce the negative impact caused by disasters, this study is developed to perform a systematic review of the utilization of BIM–GIS integration in urban disaster management. Through the systematic review, the capabilities of BIM–GIS integration in disaster prevention and mitigation, disaster response, and post-disaster recovery are reviewed and analyzed. Moreover, the data acquisition approaches, interoperability, data utilization and analysis methods, and future directions of BIM–GIS integrated utilization in the disaster management process are also discussed and analyzed. Through this study, the public and urban disaster managers can effectively familiarize themselves with and utilize the capabilities of BIM–GIS integration in urban disaster management, thereby improving the urban disaster management efficiency and the survival rate of disaster victims worldwide. For BIM and GIS software developers, this study can support them to familiarize themselves with the methods and trends of BIM–GIS integrated utilization in urban disaster management and thus optimize the development of software for BIM and GIS.

Competitive Relief Supply Chain under the Uncertain Conditions

Relief operations and planning to implement them are essential due to the unpredictability of natural disaster occurrences and their concomitant damages. The Crisis and Disaster Management Organization’s responsibility is to execute plans, coordinate, control relief, and rescue operations to reduce the impacts and consequences of these disasters. Thus, this organization should attend to the struck regions’ needs with their maximum power as soon as possible. This study has initially reviewed the latest available literature regarding the humanitarian supply chain to determine the research gap. Accordingly, in this research, a mathematical model with a leader-follower approach for relief delivery in the crisis response phase was designed, which took into account the policies of the country of Iran for the distribution of relief items. The amount of inventory of suppliers was also considered as uncertain. Then, to validate it, a numerical example was solved by the metaheuristic algorithm MOEA/D. The results indicated that the designed model is valid and the selected algorithm to solve it has an acceptable performance. Finally, some effective parameters were selected in the model and the sensitivity of the model was evaluated based on their changes.

Traditional Indigenous Ecological Knowledge to Enhance Community-Based Disaster Resilience: Taiwan Mountain Area

The Sendai and Hyogo Frameworks emphasize integrating modern science with Indigenous knowledge, a bottom-up community-based disaster management approach. However, a top-down disaster management mechanism and a lack of awareness about Indigenous knowledge are part of the current reality in Taiwan. This study chose the great Cinsbu, an Atayal community in Taiwan, as a case study area, using interviews to explore traditional ecological knowledge in Indigenous people’s daily lives. The study also applies a bottom-up, community-based approach through workshops. This study’s goals are to apply Indigenous knowledge to improve community disaster planning and to work with communities to assist them in utilizing their (Indigenous) knowledge and resources. As a key to achieving disaster resilience, the study highlights three approaches based on traditional ecological knowledge: the natural environment, agriculture production, and social capital. The natural environment approach integrates modern science and traditional ecological knowledge through community risk mapping. The agriculture production approach conserves seeds and stores food using traditional methods, such as pickling and storing in traditional barns. The social capital approach establishes a disaster management organization based on social networking. Finally, the community develops hazard preparedness and disaster response measures based on traditional ecological knowledge. These measures can be integrated with existing disaster management to form a specific mechanism for Indigenous communities.

Temporary Organizations in Disaster Response: Crisis, Temporality, and Governance

For most modern governments, disasters are events that are demarcated from so-called normalcy by changes in organization and temporality. As much as the changes in procedures or staffing, these new structures are distinguished by their temporality. They are explicitly temporary organizations, designed to accomplish a specific task before dissolving and returning authority to the permanent organization. The choice to change to temporary organizations in times of crisis carries a number of implications. The switch to an entity that is both a part of the government, and distinct from it and that will disappear at some unspecified but unswervingly expected point in the future when the crisis is “over” points to a distinct separation between the disaster period and “normalcy,” and indicates that the disaster period will give way to normalcy again. It allows the government to portray the crisis as exogenous and separate from on-going policies, depicting it as the result of uncontrollable natural forces that must be dealt with on an ad hoc basis and ignoring links to long-term governance in areas of education, housing, health, and other areas. This paper uses original interviews and documentary data, collected as dissertation research, to look at the formation, dissolution, and occasional failure of temporary, government-based disaster management organizations across two events: Hurricane Katrina in the United States in 2005, and the 2011 earthquake and tsunami in northeastern Japan.