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Having achieved an export-led exponential economic growth, Singapore remains vulnerable to both natural disasters and economic crises. However, the economic repercussions and policy responses to extreme events for an island nation like Singapore are not as widely known or studied. This paper illustrates that impacts of a health disaster [Severe Acute Respiratory Syndrome (SARS)] and an economic crisis [Global Financial Crisis (GFC)] on the Singapore economy based on selected indicators of the financial market, macroeconomy and property sector. Crises of different nature entail different policy responses of different scales and this is highlighted in the policy responses to both SARS and GFC toward economic recovery. In the case of SARS, there were preventive measures toward diseases but no reactive measures as the SARS virus was a new strain. For GFC, the policy measures were simply reactive as preventive measures failed to regulate the financial markets effectively. Our paper makes the case that the impacts of such extreme events are systemic as they affect all aspects of Singaporean society and that, moreover, the island nation is more vulnerable to these shocks than is currently acknowledged.

Flying Ad-hoc Networks (FANETs) and Unmanned Aerial Vehicles (UAVs) are widely utilized in various rescues, disaster management and military operations nowadays. The limited battery power and high mobility of UAVs create problems like small flight duration and unproductive routing. In this paper, these problems will be reduced by using efficient hybrid K-Means-Fruit Fly Optimization Clustering Algorithm (KFFOCA). The performance and efficiency of K-Means clustering is improved by utilizing the Fruit Fly Optimization Algorithm (FFOA) and the results are analyzed against other optimization techniques like CLPSO, CACONET, GWOCNET and ECRNET on the basis of several performance parameters. The simulation results show that the KFFOCA has obtained better performance than CLPSO, CACONET, GWOCNET and ECRNET based on Packet Delivery Ratio (PDR), throughput, cluster building time, cluster head lifetime, number of clusters, end-to-end delay and consumed energy.

Emergency logistics is one of the most important parts of disaster relief operations. Quick and adequate decision making in this sector is vital but sometimes hard to achieve. This issue is currently faced by several humanitarian organizations, where the high turnover of staff and the lack of adequate tools make it hard to learn from past experiences. Choosing the most appropriate supplier, the adapted warehouse and transportation means is a complicated task. Indeed, on the one hand there are many criteria to take into account in the decision-making process, and on the other hand the relative importance of those criteria is changing over time. Existing academic works on this issue are very difficult to implement on real case scenarios as they do not propose practical solutions. In this paper, a decision model which evolves over time, depending on operations progresses is proposed. Selection of supplier, warehouse and vehicle are taken into consideration thanks to the Multi-Criteria Decision Making (MCDM) approach. In order to achieve a proper decision, Analytic Hierarchy Process (AHP) is used first to analyze the structure of alternatives selection problem and to determine weights of criteria. Then Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to obtain final ranking in a four-phases of humanitarian operation life cycle. A numerical example based on preliminary data from the French Red Cross including the sensitivity analysis is presented to clarify and validate the methodology.

This paper describes a knowledge-based decision support system (KB-DSS) to improve the preparedness of crisis situations induced by natural and technological hazards. The proposed KB-DSS aims to manage the potential cascading effects generated by a triggering hazard assessing the possible event time histories based on interconnected probabilistic simulation models. From a methodological point of view, a decision model based on two Multi-Criteria Decision-Making (MCDM) algorithms follows a cascading effect simulation model. This combination allows to support the decision maker in comparing a set of mitigation strategies on the basis of their expected impacts and his priorities. The algorithm is based on an ensemble approach, which combines decisions over an array of possible impact scenarios, instead of only relying on the average impact scenario. An application of the KB-DSS to the case of a possible reactivation of Nea Kameni volcano in Santorini is presented to show how the proposed architecture could be applied to a real case. The proposed methodology supports the emergency planners in making the best decisions supporting them also in the choice of the best timing for the intervention.

This paper examines the role of knowledge management systems (KMS) for disaster planning and response in the context of social work in Malaysia. The research is focused on the client — the Malaysian Association of Social Workers (MASW), where a web-based system to support disaster management was developed and implemented. The research objectives required the researchers' direct involvement with the MASW. Canonical Action Research (CAR) was used as the research methodology. The process and outcomes of this action research initiative is presented based on the five-stage CAR approach, consisting of (i) problem diagnosis, (ii) action planning, (iii) intervention, (iv) evaluation and (v) learning outcomes. The evaluation of the system is supported by quantitative analysis driven by survey instrumentation. Our findings suggests that successful utilisation of the system in the context of MASW's efforts and roles in disaster management in Malaysia, is contingent upon issues such as acceptance of KMS, and availability of resources to maintain the system. Other issues such as clear definition of the role of Information Technology (IT) for disaster management and willingness to share knowledge are also vital in this regard.

The concept of big data (BD) has been coupled with disaster management to improve the crisis response during pandemic and epidemic. BD has transformed every aspect and approach of handling the unorganized set of data files and converting the same into a piece of more structured information. The constant inflow of unstructured data shows the research lacuna, especially during a pandemic. This study is an effort to develop a pandemic disaster management approach based on BD. BD text analytics potential is immense in effective pandemic disaster management via visualization, explanation, and data analysis. To seize the understanding of using BD toward disaster management, we have taken a comprehensive approach in place of fragmented view by using BD text analytics approach to comprehend the various relationships about disaster management theory. The study’s findings indicate that it is essential to understand all the pandemic disaster management performed in the past and improve the future crisis response using BD. Though worldwide, all the communities face big chaos and have little help reaching a potential solution.

Natural disasters have the potential to trigger technological accidents with the accompanying release of contaminating substances in the environment. Such incidents are expected to increase as the effects of climate change become more pronounced in an increasingly urbanized landscape. The Flash Environmental Assessment Tool (FEAT) has been developed at the request of the Joint Environment Unit (JEU) of the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) and the United Nations Environment Programme (UNEP) in order to allow disaster responders, including assessment and coordination teams, to identify and prioritize locations with an evident risk of technological accidents and corresponding chemical releases. The evaluations from use of FEAT in disaster response, simulations, trainings and for hazard mapping provide evidence that the tool is considered useful, easy to use, and widely applicable both in disaster preparedness and response in developing countries, As such, FEAT can be first step in embarking on an inclusive disaster risk reduction programme, and should be followed by identified priority actions such as conduction of detailed risk assessments at the local level, creation of industrial hazard maps, regulation and enforcement of land-use in the vicinity of industrial facilities, and training disaster managers and adjacent communities on chemical accident response.

This paper aims to clarify the potential benefits and challenges of integrating environmental assessment (EA) and disaster management considerations, and current research gaps. In this context, the discussion is provided from three perspectives: (1) the consideration of disaster risk in EA; (2) the development of accelerated EA for post-disaster situations; and (3) the integration of EA into pre-disaster response and recovery planning. For this, a Japanese JSPS (Japan Society for the Promotion of Science)/UK ESRC (Economic and Social Research Council) financed UK-Japan project on the integration of environmental assessment (EA) and disaster management was conducted in 2012. It was concluded that whilst EA can be beneficial for disaster management, there are a number of potential pitfalls and an evident lack of research in the area.

Hurricane Sandy arrived on October 29, 2012 with enormous adverse impacts on one of the largest metropolitan areas in the world, the New York region, including its electric power and transportation systems that disrupted the social and economic fabric of a wide geographic area. How these services were restored is an important basis for proactively designing robust public services not only in areas affected by Hurricane Sandy but also for many similar areas and events worldwide. Recovery rates are one important indicator of consequences of disaster. Selected physical and social measures of recovery are analyzed for New York City electricity and rail transit services following Hurricane Sandy to capture the ability of these services to be restored over various time periods, and to illustrate the use of indicators of restoration for infrastructure service resilience analyses for disaster management and planning. Electricity impacts and recovery are presented in user-oriented terms as the ratio of customers affected and restored to both customers without service and total customers served in the period following the hurricane. Results showed that restoration rates varied among the boroughs of NYC potentially reflecting differences in infrastructure resilience and exposure conditions. Rail transit impacts and recovery were analyzed in terms of both the restoration of the two dozen subway lines as a physical measure and ridership by station as a user or social measure. Line recovery analyses showed that within about a couple of weeks of the storm almost 80 percent of the lines were fully restored, almost 20 percent were partially restored, and complete suspensions were rare indicating a high degree of restoration capacity. Ridership measured at stations was compared to levels and rates of change over various time periods around the storm period, as well as from the previous year. High correlations in ridership between single days before and after the storm indicated little redistribution of ridership across stations between those time periods, however, rates of change indicated about a 14–16 percent decline in ridership system-wide within a two week period following the storm relative to the same time period the year before, recovering later, possibly reflecting slower rates of social recovery relative to the recovery of the physical transit systems. A longer period of service quality effects occurred due to lingering equipment damage potentially attributed for example to water damage and corrosion from saltwater. These findings point to the importance of recovery time as at least an initial guide to ways of systematizing service restoration measures and are a foundation for physical, social, and institutional adaptation strategies some of which are already being put in place. Larger considerations remain however in interpreting recovery restoration goals and who decides them.

Much of effective disaster risk communications practice is based on the equitable distribution of crisis messaging to the target population. Priority is given, for example, to getting an evacuation message to the most people possible using a language and medium appropriate to that audience. Cognitive dissonance (CD) studies, however, show that well-intentioned disaster management messaging not only can produce an undesirable public reaction, but can also solidify public sentiment to resist or deny that very message. This focused literature review of a modest-sized body of research on the effects of cognitive dissonance on disaster management risk communications will produce two results. First, the research will demonstrate that a basic understanding of CD could help disaster communicators craft more effective messaging and, second, it will introduce a preliminary cognitive dissonance index (CDI) that can be easily plugged into existing crisis communication models. This “upgrade” to existing risk communication frameworks represents an efficient method to close the theory to practice loop and begin to account for the power of CD in our national and international disaster communications.

Ghana is susceptible to disasters including floods, earthquakes, domestic and industrial fires, rain and windstorms, epidemics, pest and insect infestation, boat and road accidents, and many others. There are no clear policies in place to help citizens cope with disasters or even report them if they occur. The research examines historical and current instrumental records, as well as the role of information technology in disaster management in Ghana. Furthermore, the study aims to assist state institutions in understanding the different types of ICT tools on which they can rely at each stage of a disaster to help inform, educate, and mitigate during a disaster. The survey was used to collect primary data from the study population, and the study’s methodology was also qualitative. Floods and wildfires, both domestic and industrial, are common in Ghana, according to the study's findings. It was also discovered that radio is the most widely used ICT tool for disaster reporting.

To develop an integrated framework to understand the field of disaster management and help nonprofit organizations take effective technology management decisions in terms of availability of technology, effective response to disruptions, mitigate risk and improve their overall disaster management plan by using IT as a tool.

Thailand is a rising economy in the South Asia and it has been growing at a considerable rate than it neighbors. The economic growth has been halted by reoccurring natural disasters may it be consistent floods, droughts, earthquakes or Tsunamis. The country being diverse in geographical setting is prone to many natural hazards. The disaster management structure in Thailand is present but lacks in several aspect due to political instability and emphasis on the indigenous knowledge. This chapter tries to explore various aspects of disasters in Thailand in the context of social, economic and framework at the government level.

Humanitarian logistics is a kind of logistics focused on alleviates suffering of vulnerable people. This logistics historically appears after military and commercial logistics, being in the field of disaster management where its specificity is greater. These specific characteristics can be grouped in three big features: decision makers, strategic goals and uncertainty. Main stakeholders are identified (classified into local, national and international level), showing the large number of decision makers involved and the urgent need for coordination between them. Strategic goals and performance measures of humanitarian logistics also are specific, being the most characteristic priority of effectiveness over efficiency. Thus, when designing decision support models in this context it is important to note that a humanitarian logistician cannot value economically the performance and goals achievement as they are lives and suffering. Finally, uncertainty and time pressure are variables that determine the environment in which decisions must be made, with different relevance throughout the process of decision making in disaster management. A brief overview of decision aid models and management systems for humanitarian logistics allows realizing that currently there is a booming of decision models, but a lack of integration of these with the information systems available for disaster management.

This paper introduces the theory of social marketing to the areas of disaster management that deal with natural disasters such as earthquakes, flooding, hurricanes, etc. The theory of social marketing as a sub-theory of marketing is introduced and its implications in the area of disaster management are discussed. The paper further illustrates how social marketing can benefit various levels of government as well as organizations and communities in the disaster affected regions. A model of social marketing related to disaster preparedness will advance the use of social marketing concepts such as product, promotion, place and price to help governments, organizations, and local communities prepare for possible natural disasters with minimum negative impact.

Extreme natural hazards, particularly the hydro-meteorological disasters, are emerging as a cause of major concern in the coastal regions of India and a few other developing countries. These have become more frequent in the recent past, and are taking a heavy toll of life and livelihoods. Low level of technology development in the rural areas together with social, economic and gender inequities enhance the vulnerability of the largely illiterate, unskilled, and resource-poor fishing, farming and landless labour communities. Their resilience to bounce back to pre-disaster level of normality is highly limited. For the planet Earth at crossroads, the imminent threat, however, is from a vicious spiral among environmental degradation, poverty and climate change-related natural disasters interacting in a mutually reinforcing manner. These, in turn, retard sustainable development, and also wipe out any small gains made thereof. To counter this unacceptable trend, the M.S. Swaminathan Research Foundation has developed a biovillage paradigm and rural knowledge centres for ecotechnological and knowledge empowerment of the coastal communities at risk. Frontier science and technologies blended with traditional knowledge and ecological prudence result in ecotechnologies with pro-nature, pro-poor and pro-women orientation. The rural communities are given training and helped to develop capacity to adopt ecotechnologies for market-driven eco-enterprises. The modern information and communication-based rural knowledge centres largely operated by trained semi-literate young women provide time- and locale-specific information on weather, crop and animal husbandry, market trends and prices for local communities, healthcare, transport, education, etc. to the local communities. The ecotechnologies and time- and locale-specific information content development are need-based and chosen in a ‘bottom-up’ manner. The use of recombinant DNA technology for genetic shielding of agricultural crops for coastal regions against abiotic stress (induced by the water- and weather-related natural disasters), strengthens the foundations of sustainable agriculture undertaken by the resource-poor small farm families.