This special issue presents the findings obtained so far by the relevant studies that have been conducted mainly at the Global Centre for Disaster Statistics (GCDS), which is affiliated with the International Research Institute of Disaster Science (IRIDeS) at Tohoku University, Japan.
The establishment of the GCDS was jointly announced by the United Nations Development Program (UNDP) and the IRIDeS in March 2015 during the Third UN World Conference on Disaster Risk Reduction (UNWCDRR) in Sendai, Japan. The Centre is expected to contribute greatly to sustainable development, based on risk-informed policy making, through the following activities: providing scientific analyses and technical advice based on their disaster loss and damage data, supporting the United Nations International Strategy for Disaster Reduction (UNISDR) and individual countries in the work of monitoring the progress of the Sendai Framework for Disaster Risk Reduction (SFDRR) and the 2030 Agenda for Sustainable Development, and providing policy advice to build the capacities of national/local governments, based on their demands.
In this context, the guest editors of this special issue are pleased to publish valuable academic articles closely related to the GCDS’ activities that contribute to the development of disaster statistics. As Sasaki and Ono (2018) observed, there exist three major categories of research questions that contribute to the development of disaster statistics: investigation into disaster statistics and/or global disaster-related databases, development of the existing discipline-based research, and analysis of various issues through questionnaire surveys.
Last but not least, it is our hope that this special issue contributes to the literature of disaster statistics and accelerates its development.
At the Third UN World Conference on Disaster Risk Reduction (UNWCDRR) held in March 2015 in Sendai City, Japan, the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR), containing seven global targets, was adopted by 187 UN member states. With its outcome-oriented but non-numerical targets, quantitative approaches for monitoring disaster damage and loss by national governments became mandatory. The Global Centre for Disaster Statistics (GCDS) in Tohoku University was established in April 2015. The GCDS is expected to contribute to the evidence-based policy making by national and/or local governments. In addition, the GCDS aims at creating a synergy effect among academia, the UN organizations, and private companies in order to provide unprecedented values to all stakeholders worldwide. Under such circumstances, the special issue aims at publishing the research results obtained so far from the relevant studies that have been mainly conducted at the GCDS. The guest editors of the special issue are pleased to publish 13 valuable academic articles closely related to the activities of the GCDS, contributing to the development of disaster statistics. Based on the features of the 13 articles contained in the special issue, there seems to be three major categories of research questions. The first one is to investigate disaster statistics and/or global disaster-related databases. The articles of the first category contribute to the clarification of the characteristics specific to disaster statistics. The second one is to utilize disaster statistics in order to develop the existing discipline-based research. The articles of the second category are quite beneficial for establishing a new possibility of applying disaster statistics for the research so far. The third one is to analyze a variety of issues by means of questionnaire surveys. The articles of the third category are issue-oriented and interdisciplinary. Last but not least, the guest editors hope that the special issue would certainly contribute to the literature of disaster statistics and accelerate their development.
After the Sendai Framework for Disaster Risk Reduction is adopted, a global database as a tool to monitor disaster loss and damage databases is required. Several disaster loss and damage databases are in use globally. This paper aims to explore how the existing databases vary in three aspects of threshold, spatial resolution, and data quality control, as well as the limitations of the existing databases. We review previous studies comparing the existing global databases and extract the differences and limitations. The threshold of EM-DAT is clear, but its threshold results in ignoring small-scale disasters that DesInventar captures. The differences in disaster threshold create different pictures of disaster losses and/or risks. Regarding spatial resolution, only DesInventar provides disaster impact data at a municipal level, while others provide information at a country level. The limitations of the existing global database are categorized into four aspects, as follows: lack of disaggregated data, limited spatial coverage and resolution, insufficiency of completeness and reliability of data, and insufficient information on indirect loss. The implication from our findings is that, in order to complement the limitations of the existing disaster loss databases to use for decision making on disaster risk reduction, the following are required: cross-checking of data across different databases; complementary disaster loss data; and collection of an exhaustive and firsthand dataset with a transparent and internationally consistent methodology by policy makers.
Even typical system development models considered to be optimal for individual conditions are not always flawless. It is preferable to have clearly defined requirements of the end users when constructing a system. However, to construct the present Global Database (GDB) system, it was necessary to identify these requirements while conducting a status survey and analysis of the country that provided the data and drawing up suitable response guidelines, and to carry out system development at the same time. In this environment of continually changing system requirements, we selected the spiral model, which is used for system development, and applied it to the present construction task. We recognized various issues during the construction of the GDB, including the granularity of the collected data, the validity of the computed results, and the need for data other than disaster data. It was thus necessary to adopt an approach, based on the spiral model, in which the requirements were identified from the prototype. To follow up this study, it will be necessary to consider matters such as securing more flexibility, storing various data types (realizing an “iron stomach”), examining the issue of data access rights, examining the contents of the GDB’s automatic computation function, and creating added value to personnel charged with disaster response in each country. It will also be necessary to verify the validity of the approach of digging up unknown requirements from collected data.
The Statistical Database on the Great East Japan Earthquake (SDJE) has been developed as an information resource to assist in research and preparations for future disasters in Japan and other countries. The SDJE was initiated in January 2016 by the International Research Institute of Disaster Science (IRIDeS) of Tohoku University. As a university in the affected area of the Great East Japan Earthquake (GEJE), Tohoku University acknowledges with gratitude the participation in GEJE relief and recovery activities of organizations and people from elsewhere in the country and abroad, and in response has undertaken a number of initiatives to provide scientific information and the lessons from the GEJE. For example, IRIDeS hosts and acts as the secretariat of the Global Centre for Disaster Statistics and has now developed this new database. The SDJE provides comprehensive data on the GEJE in both English and Japanese, drawing widely on data originally provided by the national and local governments and private organizations, including considerable contents taken from the white papers of Japan’s Cabinet Office and other national ministries. The data coverage extends from the time of the GEJE to currently produced materials. In addition, a “Link Collection” of Japanese statistics related to disasters is provided to support statistical analysis of the social and economic effect of the GEJE, for example through correlation analysis, and to assist researchers to better understand the context of the disaster and the disaster statistics. It is hoped that many people worldwide will find the content of the database useful for disaster risk reduction activities.
This study aims to examine common hidden factors in disaster loss statistics and identify clues for verifying the fitness of the global targets of the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) to rule countries’ effort in reducing disaster risks. In this study, we first conducted an exploratory factor analysis (EFA), followed by a confirmatory factor analysis (CFA) using structural equation modeling (SEM). As a result of the EFA, we were able to extract three factors, namely Housing, Casualties or Education, and Relocation. In the analysis of SEM, we assumed three latent variables based on the results of the EFA. The relationship between the latent and observed variables was established in a manner that conformed to the implications of the EFA. According to the SEM results, we eventually identified three latent variables, namely Housing, Education and Relocation, as hidden common factors. Based on this identification, our judgment indicates that the latent variables appeared to be related to the following global targets of SFDRR: (b) those concerning the number of affected people and (d) those concerning damages to infrastructure and disruptions to basic services. It was found that relationships between variables could be clearly illustrated by using the path diagram. This study can be considered as a good example of introducing SEM to visualize hidden common factors and their relationships in an intelligible manner. Based on the results, we propose a starting point for discussing the fitness of SFDRR’s global targets by utilizing EFA and CFA (SEM) techniques. The path diagram can indicate the extent to which the indicators contribute to global targets that will be represented as latent variables. In the end, explicit reference should be made to the material data’s limitations in the disaster loss statistics. An effort to elaborate the input data themselves must be made in the near future.
Regional disaster data are important for understanding the characteristics of disasters and for identifying potential mitigation measures. However, many countries have no official disaster database that includes information such as numbers of deaths or damaged buildings for each disaster event. The Global Centre for Disaster Statistics (GCDS) was established to assist countries and organizations in the collection of disaster data. At present, a significant amount of tsunami disaster data are available from Indonesia, which will be used to demonstrate its application for analyzing vulnerability characteristics of historical tsunamis. There are 53 data points covering 13 tsunami events between the year 1861 and 2014. Based on data availability, five tsunami events, namely the 1977 Sumba, the 2004 Indian Ocean, the 2006 Java, the 2010 Mentawai, and the 2011 Great East Japan, were selected. Numbers of deaths and damaged buildings were used in combination with hazard data to estimate vulnerability, defined as the ratio between maximum flow depth against death and building damage ratios. Numbers of evacuees were initially used to estimate actual numbers of exposed population but it was later discovered that this parameter overestimated the exposed population in certain cases. As a result, this study presents the vulnerability characteristics of people and buildings in Indonesia, exposed to unusual or extreme tsunamis, mostly in a condition without or with limited access to official warnings. In brief, a maximum flow depth of 5 m caused an approximate 100% death ratio in the majority of Indonesian tsunamis in this study. On the other hand, death ratio in the 2011 Japan tsunami was limited to 10% because of the early warning and high disaster awareness. Effective disaster risk reduction activities such as official warnings, evacuations, and tsunami education were observed for certain locations. Lastly, adding hazard and population data at the village level is recommended for improving the collection of future tsunami disaster data for the GCDS database.
A healthy community is a community resilient to disaster. The Sendai Framework for Disaster Risk Reduction considers disaster impacts on health and encourages the implementation of disaster medicine and access to mental health services. Life expectancy (LE) is a basic statistic that indicates public health achievements and social development, including the health system, infrastructure, and accurate vital statistics. Thus, we hypothesized that LE corelates with disaster risk and strategies to achieve long LE can help achieving disaster risk reduction. We compared the disaster risk obtained from Index for Risk Management (INFORM) with the LE of both genders at birth to identify which component of INFORM risk correlates with LE. A correlation analysis revealed that overall INFORM risk negatively correlated with LE. The natural hazard category did not correlate with LE, but the human hazard category, vulnerability, and lack of coping capacity negatively correlated with LE. In the vulnerability dimension, indicators of socioeconomic vulnerability, health conditions, and children U5 negatively correlated with LE. In the lack of coping capacity dimension, indicators of communication, physical infrastructure, and access to health care negatively correlated with LE. Japan has achieved the longest LE and a low INFORM risk because of its lower vulnerability and reduced lack of coping capacity, including healthrelated indicators. In a cluster analysis of LE and INFORM categories of risk, we divided countries into four clusters and found categories that could be improved. Compared with another global disaster risk index, the Word Risk Index (WRI), the INFORM risk index seems to represent the overall disaster risk better, though they have different aspects of risk evaluation. The WRI is also negatively correlated with LE, supporting our hypothesis. In conclusion, LE is an important indicator of disaster risk and strategies to achieve long LE can be effective and important strategies in disaster risk reduction.
During recent years, the possibility that damage at the time of earthquake could change depending on the deterioration condition of infrastructure has been noted through analytical analyses. Faced with such a possibility, management policy should be optimized by internalizing the external elements of earthquake damage, evaluating the appropriateness of management policy for infrastructure, and optimizing the system. In this study, the deterioration process for infrastructure was modelled using the Markov process model, and a methodology to determine the optimal management policy is proposed by considering the two risks: i) the risk that infrastructure fails because of deterioration independent of external elements such as an earthquake, and ii) the risk that changes due to deterioration fails the infrastructure at the time of earthquake. Using an example of the application the following two points are demonstratively shown: i) the optimal management policy would change in the case in which earthquake risk is not considered, and ii) the optimal management policy would change depending on the earthquake occurrence probability in the case in which earthquake risk is considered.
This study conducts a statistical analysis of the impact of disasters on inter-prefectural migration in Japan over 41 years (1973–2013), and estimates the change in emigration and immigration after disasters of different magnitudes. The result reveals that emigration decreases and immigration increases after a modest-sized disaster, while the opposite is observed following a huge disaster. It also shows a disaster threshold requiring external assistance for recovery and quick decision-making afterwards.
Perceptions of volcanic hazard-related information relevant to volcano tourism areas in Japan were investigated using an Internet questionnaire survey. This study focused on the possibilities of tourism activities as a method of disseminating disaster information not only to residents but also to visitors. We evaluated the effects of educational programs (EP) including recreational activities at geopark, for the purpose of further enhancing information content and establishment of cooperation system. The survey focused on the roles and perspectives of residents, the tourism industry, scientists, and the government in volcanic disaster mitigation, as well as the dissemination of volcanic information with regard to daily activities and the actions to be taken in the event of an emergency. Hazard perceptions tended to be actuate in areas where knowledge dissemination activities were active, but this did not lead to evacuation awareness. Evacuation awareness was correlated with disaster awareness, specifically regarding the degree of interest in a volcano, eruption frequency and style, perceptions of eruption predictability, and trust in information source. Disaster awareness correlated somewhat with eruption style and with the time elapsed science the most recent eruption. Our results showed that the perceptions of residents living near volcanoes depended on eruption frequency, their experience during previous eruptions, and local government assessments of the severity of the volcanic hazard. Despite advances in tools of social media, that is not yet to take advantage under disaster circumstances. A disaster prevention system that incorporates disaster prevention education and open lines of communication among scientists, government, media, residents, and the tourism industry is necessary to improve the disaster resilience of communities in volcanic areas.
This study aimed to examine actual situations and problems involving evacuation activity during the Mt. Agung eruption in the autumn and winter of 2017. It also clarified (from the viewpoints of administrative information, individuals, families, local residence organizations, and simple notification services) the factors that promoted evacuation based on an examination of data from evacuees and supporters as provided by administrative agencies, questionnaires, and surveys. There were two main results. The first involved the relationship between alert recognition and recognition of the call for evacuation. When people received the volcanic eruption alert from real media sources, they also recognized the call for evacuation from other people or parties within those sources. When people received the alert through virtual media, they also recognized the call for evacuation from the same media. The information recognition path available through real media was narrower than that involving virtual media. Second, only the factor of “alert recognition” realized “group evacuation.” Factors such as “prior action” and “recognition of eruption in 1963” were not directly related to “group evacuation.”
This study investigates the relationship among peacetime human relations, that is, formation of networks, social capital accumulated as a result of human relations, and group evacuation (in units of neighborhood groups, Tonari-gumi) in Numanouchi ward. Located in Iwaki City, in Fukushima Prefecture, Japan, Numanouchi ward was partially destroyed by the Great East Japan Earthquake. The study found that there are differences in the formation of networks, social capital, and group evacuation between the Numanouchi and Suwahara areas. The study also found that there is a (slight) difference in the processes followed in group evacuation and the factors influencing the choice of processes in both areas.
As of spring 2018, evacuation orders have been lifted from the entire area of Naraha Town and most of Tomioka, except for certain areas. While many evacuees have chosen their evacuation destinations as their permanent residences, some have returned to their former towns. This paper examines the factors involved in the “differentiation” and “integration” of Naraha and Tomioka residents before and after the disaster and the various forms they assume, based on the results of questionnaire surveys conducted in 2012 and 2015 as well as interviews conducted on a continuing basis since the disaster. In this process, it has become apparent that a split exists between Naraha, whose residents are moving toward “integration” with the lifting of the evacuation order, and Tomioka, whose residents are progressing toward “differentiation.”
This paper conducted a questionnaire survey of evacuees (residents of public-funded rented housing, home buyers, etc.) from Tomioka Town, who were displaced because of the nuclear accident in Fukushima in 2011. It aimed to understand the characteristics of the wide area residents’ associations as the “Third Place” by examining the relationship among the neighborhood association before and after the disaster, the neighborhood association at the evacuation district, and wide area residents’ associations. It was revealed that wide area residents’ associations could function as a relative Third Place, because the evacuees had a weak connection with the places they live in after evacuation, although they continue to have strong links with the neighborhood associations in the places where they lived before the disaster.