Exploring Disaster Preparedness for the Aging Population

Older adults are encountering harsh recovery after disasters, and compounding this problem is the lack of research on older adults\u27 perceptions on disaster preparedness as aging affects the ability to react to emergency situations. To partially address that gap, the purpose of this general qualitative research study was to use Rotter\u27s spectrum of locus of control theory to examine the level of preparation regarding disaster preparation of older adults who were living independently in single-family homes in a state affected by Hurricane Sandy. Data were collected through a qualitative survey distributed to adults aged 65 to 80-years (N=88) and publicly available documents from federal and state emergency management agencies. These data were inductively coded and subjected to a thematic analysis procedure. Findings identified 3 themes that consisted of (a) delayed acceptance, (b) defective instinct, and, (c) unexpected effects of disasters. This study contributes to social change by helping emergency management officials understand the deficiencies in preparedness by an aging population which may in turn improve the quality of life for older adults by stressing proper preparation for sheltering in place or evacuation in the event of a disaster

Role of Insurance in Post Disaster Recovery Planning in Business Community

The whole world is facing a substantial of natural disasters which brings severe damages throughout the world. Attention must be given to rehabilitate the business community that is affected by these disasters. However, improper planning for recovering damages in business community becomes a major issue when it obstructs the continuation and development of the business community. Therefore, required measures should be taken to avoid collapsing of development of the business community affected by disasters. In this context, insurance plays a vital role to reinstate the business while reducing the financial consequences of the disaster. This study investigates the role of insurance as a provision to recover the disastrous destruction of the business community in Sri Lanka. To achieve this, the survey method was used as the approach and semi structured interviews carried out within five experts from insurance sector and eight experts from the business community. Content analysis was used to analyze the collected data from the empirical study. The analysis of the findings based on two areas of insurers’ and insured’ perception of insurance. One of the major finding was that the insurance is not extended to any frequent disaster prone area of the country unless accepted by the insured with either higher premium amount or higher amount of deductible. As per the insurer’s side, some issues of the current practice are identified as less awareness, dishonesty and fraudulent practice of the insured which leads to less identification of the insurance as a risk management strategy within the business community. According to the insured, main purposes of obtaining insurance are quick recovery of business and to fulfil the borrowing requirements. Recommendations were developed as increase the awareness, educating and the government participation to increase the insurance penetration to the business community

Named data networking for efficient IoT-based disaster management in a smart campus

Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS

Considering Disaster Volunteer Behavior and the Work Environment in Managerial Decision Making

Over the last two decades, large-scale disaster events have significantly increased in frequency and intensity, causing tremendous loss of lives and property. A large number of relief organizations rely on their volunteers to respond to many disasters around the globe, serving people and communities in need. While their contributions are priceless, turnover among disaster volunteers has become a significant problem for these relief organizations. Work environment factors, such as volunteers being mismatched with tasks, unsuitable workloads, and conflict within groups of volunteers may give rise to turnover intentions, which may in turn lead to actual turnover. The link between work environment factors and volunteer turnover intentions in these situations has not yet received considerable attention in terms of quantitative research. Therefore, the purpose of this dissertation is to develop quantitative models that consider the factors that may cause turnover or turnover intentions. The goal of these models is to help decision makers for non-governmental organizations (NGOs) better manage their disaster volunteers during relief efforts, with the aim of satisfying community needs and improving volunteer retention rates. The first study addresses a gap in volunteer staff planning and scheduling where volunteer training is first presented, with volunteer turnover represented as a percentage of volunteer–task mismatch. We have developed a mixed-integer programming model for assigning optimal volunteer assignments based on a range of possible short- and long-term community need scenarios. The objective is to minimize the costs of unmet community needs, volunteer attrition due to mismatch assignments, and volunteer expenses. Under different demand scenarios, the optimum solution of volunteer assignment is to allow unskilled volunteers to start training early so that they can help skilled volunteers when a peak of long-term skilled task demand is expected. The second study investigates the effects of work environment factors on the satisfaction level and turnover intentions of disaster volunteers. Using an online survey, data from 386 disaster volunteers are collected and analyzed. Confirmatory factor analysis (CFA) and structural equation modeling are used to test the measurement model and answer research questions focused on volunteer behavior. After assessing and confirming the measurement model, we use the structural model to test the hypotheses and provide prediction equations. Job-fit, training, workload, volunteer group, and supervisor are the key work environment factors considered in this study. The findings suggest that these work environment factors have a positive significant relationship with satisfaction and a negative significant relationship with turnover intentions. The last study focuses on developing a simulation modeling approach that considers a volunteer’s satisfaction and turnover intentions in relation to management decisions of an NGO during a relief event. We use a survey to gather information from disaster volunteer managers about how they manage their volunteer teams and use this information and the findings from the second study to model a realistic relief event. We develop a hybrid simulation model, agent based and discrete event (AB-DE), that handles volunteer task and location assignments, as well as workload. Using data analysis from the surveys, we also introduce a group conflict variable within the simulation model. We evaluate the impact of different management decisions on unmet community needs, as well as on volunteer satisfaction and turnover intentions from the organization. This study uses a numerical example based on the survey data. Considering the scenario in which disaster volunteer managers do not assign heavy workload to disaster volunteers, the results of this study suggest that as a surplus of available volunteers’ increases, the overall satisfaction increases while the turnover intention decreases due to dissatisfaction with a non-essential workload as well as from group conflict. In contrast, when the number of volunteers is less than what is needed, disaster volunteers’ satisfaction and turnover intentions were not affected even if there is high group conflict due to the positive effect of the workload that offsets the negative impact of the group conflict

Internet of things for disaster management: state-of-the-art and prospects

Disastrous events are cordially involved with the momentum of nature. As such mishaps have been showing off own mastery, situations have gone beyond the control of human resistive mechanisms far ago. Fortunately, several technologies are in service to gain affirmative knowledge and analysis of a disaster's occurrence. Recently, Internet of Things (IoT) paradigm has opened a promising door toward catering of multitude problems related to agriculture, industry, security, and medicine due to its attractive features, such as heterogeneity, interoperability, light-weight, and flexibility. This paper surveys existing approaches to encounter the relevant issues with disasters, such as early warning, notification, data analytics, knowledge aggregation, remote monitoring, real-time analytics, and victim localization. Simultaneous interventions with IoT are also given utmost importance while presenting these facts. A comprehensive discussion on the state-of-the-art scenarios to handle disastrous events is presented. Furthermore, IoT-supported protocols and market-ready deployable products are summarized to address these issues. Finally, this survey highlights open challenges and research trends in IoT-enabled disaster management systems. © 2013 IEEE

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

SoS in Disasters: Why following the manual can be a mistake

According to both the US Geological Survey and the World Bank, $280 billion dollars could have been saved if$40 billion dollars had been invested in disaster prevention. Natural and human-made disasters that have occurred over the last few years show that there is a gap in disaster prevention caused by the interconnected nature of risks, which cannot be foreseen with current risk management methods. In this paper we point out how disaster management could benefit from a SoS approach in emergency response and preparedness strategies. Using recent disasters as case studies, we identify some keys to success in managing a SoS in preparation, during and in the aftermath of a disaster. In particular, we discuss the idea of the interconnectedness of risks in independent and interdependent systems and the application of Boardman and Sauser’s concept of “creative disobedience”, which are fundamental for goal achievement of systems belonging to a SoS