Incidence Of Disasters Research Articles

Adaptation Of Climate Change In Cimangeunteung Village Lebak District In The Framework Of Improving Regional Resilience

Climate change causes an increase in the incidence of natural disasters which, if not handled seriously, will threaten regional resilience. Lebak Regency is one of the areas in Indonesia which is not spared from the impacts of climate change. In 2019 there were many drought disasters in Lebak Regency, but there was one village that was not affected by drought, namely Cimangeunteung Village. This becomes interesting for further research by researchers. The data was taken based on the results of interviews, observations, and documents using the interactive model qualitative research methods belonging to Miles, Hubermen, and Saldana (2014). The purpose of this study is to determine the impact of climate change on potential disasters in Lebak Regency and to analyze the adaptation efforts made by the people of Cimangeunteung Village. The results of this study are 1) Climate change has caused the number of disasters due to climate change such as floods, droughts and landslides to increase in Lebak Regency. 2) The implementation of fostering climate change adaptation in Cimangeunteung Village is carried out through the activity of creating a waste bank; construction of walls of spring wells; and the formation of the Women Farmers Group. Climate change adaptation activities in Cimangeunteung Village have been well implemented and have succeeded in increasing public awareness in caring for the environment. Routine monitoring by the Lebak local government of Cimangeunteung Village is still being carried out to date.

Risk perception and travel behavior under short-lead evacuation: Post disaster analysis of 2020 Beirut Port Explosion

Human-made disasters continue to be the most dangerous of all types of disasters due to their suddenness and unpredictability. This calls for a thorough examination of people’s evacuation behavior due to its impact on the evacuation procedure and its significance for evacuation planning. This study aims to provide a comprehensive understanding of the decision-making process of residents in case a human-made disaster occurs with an application to Beirut, Lebanon. This study is essential for pre-disaster planning, which mitigates potential damage from such disasters. Using structural equation modeling (SEM), the current study uses the Protective Action Decision Model (PADM) framework to explain intention toward evacuation behavior before a human-made disaster in three situations: being at home with all family members, having absent family members, and being at work or university when the event occurs. The findings of this study show that the PADM framework is relevant to explaining evacuation behavior intentions prior to a human-made disaster incident. Results indicate that knowledge perception does not trigger the intended behavior of evacuating immediately in the studied situations. Besides, the results indicate low confidence in the government’s emergency plans and the unreliability of the official government warnings about human-made hazards. Overall, the findings of this study may contribute to a better understanding of evacuation behavior from disasters with less lead warning time. Besides, they may aid the Disaster Risk Management unit of Lebanon in developing emergency evacuation strategies that: understand the public’s evacuation behavior; customize city-specific evacuation logistics; optimize the dissemination of evacuation information.

Use of Mobile Crowdsensing in Disaster Management: A Systematic Review, Challenges, and Open Issues.

With the increasing efforts to utilize information and communication technologies (ICT) in disaster management, the massive amount of heterogeneous data that is generated through ubiquitous sensors paves the way for fast and informed decisions in the case of disasters. Utilization of the big "sensed" data leads to an effective and efficient management of disaster situations so as to prevent human and economic losses. The advancement of built-in sensing technologies in smart mobile devices enables crowdsourcing of sensed data, which is known as mobile crowdsensing (MCS). This systematic literature review investigates the use of mobile crowdsensing in disaster management on the basis of the built-in sensor types in smart mobile devices, disaster management categories, and the disaster management cycle phases (i.e., mitigation, preparedness, response, and recovery activities). Additionally, this work seeks to unveil the frameworks or models that can potentially guide disaster management authorities towards integrating crowd-sensed data with their existing decision-support systems. The vast majority of the existing studies are conceptual as they highlight a challenge in experimental testing of the disaster management solutions in real-life settings, and there is little emphasis on the use cases of crowdsensing through smartphone sensors in disaster incidents. In light of a thorough review, we provide and discuss future directions and open issues for mobile crowdsensing-aided disaster management.

Validation of Gender Identification by “Alu” Insertion on Y Chromosome for Forensic Mass Disaster

Background: Gender determination of human samples is critical in forensic identification. The most popular forensic kit AmpliFlSTR® is based on Short Tandem Repeat (STR), and gender determination is performed on a single copy Amelogenin gene with X and Y homologous chromosomes. This method is not sufficiently sensitive for degraded and a small number of samples and requires a lengthy time. Furthermore, this method needs fragment analysis by a genetic analyzer and an analytical kit for sample preparation, which is costly and not available for public support in developing countries. Aim: Thus, it is urgent to have an alternative, quick, and cost-effective gender identification method during mass disasters. Objective: We proposed to use an alternative PCR method with a single AluSTYa primer and compare it with our designed primer to identify male and female DNA samples in mass disasters when identification is crucial. Method: In the current research, we scanned 16 samples from the fire incidence area known as Mohammadpur slum of Dhaka city in different time frames, where bodies were partially burnt. Patients were admitted to the burn unit of Dhaka Medical College, Dhaka. Thirty-six unknown samples from the healthy cohort were included from the Dhaka University campus for comparison. Modified Alu primer was used in addition to known commercial AluSTYa primers. Results: This study revealed that our designed primer and commercial AluSTYa primer could identify Alu insertion by a simple PCR method into a non-recombinant Y homologous region. The results showed the high quality of DNA extracted from the burnt specimens and a 100% difference in the number of bands in X and Y chromosomes by a simple, robust, and cost-effective PCR and agarose gel electrophoresis method for gender identification. Conclusion: This method can be applied to mass disaster incidents where rapid gender identification of unknown persons is urgent for forensic purposes.

United States Federal Emergency Management Agency regional clustering by disaster exposure: a new paradigm for disaster response.

The Federal Emergency Management Agency (FEMA) divides the United States (US) into ten standard regions to promote local partnerships and priorities. These divisions, while longstanding, do not adequately address known hazard risk as reflected in past federal disaster declarations. From FEMA's inception in 1979 until 2020, the OpenFEMA dataset reports 4127 natural disaster incidents declared by 53 distinct state-level jurisdictions, listed by disaster location, type, and year. An unsupervised spectral clustering (SC) algorithm was applied to group these jurisdictions into regions based on affinity scores assigned to each pair of jurisdictions accounting for both geographic proximity and historical disaster exposures. Reassigning jurisdictions to ten regions using the proposed SC algorithm resulted in an adjusted Rand index (ARI) of 0.43 when compared with the existing FEMA regional structure, indicating little similarity between the current FEMA regions and the clustering results. Reassigning instead into six regions substantially improved cluster quality with a maximized silhouette score of 0.42, compared to a score of 0.34 for ten regions. In clustering US jurisdictions not only by geographic proximity but also by the myriad hazards faced in relation to one another, this study demonstrates a novel method for FEMA regional allocation and design that may ultimately improve FEMA disaster specialization and response.

Hydro-Meteorological Disaster Incidents and Associated Weather Systems in Sri Lanka

This paper presents a comprehensive seasonal analysis of disaster incidents with their associated weather systems happened in Sri Lanka since 1907 to 2019. Disaster incidents and weather records were collected from different reliable sources and analysed with the observed weather systems to understand the formation and development of the weather systems. According to the observations, frequent hydro-meteorological hazards experienced by the country are extreme winds, floods, and landslides. The seasonal analysis shows that majority of these hydro-meteorological disasters have occurred during the southwest monsoon, where the weather was mainly dominated by the monsoon winds entering from the southwest of Sri Lanka which creates torrential rainfall mainly in the wet zone of the country. The frequency of formation of depression and deep depression, from 1907 to 2019 shows that most of these are formed in the Bay of Bengal (BoB), North Indian Ocean, from October to January while having the highest frequency in November followed by December. The study will help to understand the possible damages, and thereby help the community to be prepared for such future hazards. The need for a central platform for generating timely impact-based warnings and helping the community to act was also identified. Further, the census block can be suggested as the smallest; Micro-Geographic Incident Response Unit (MG-IRU) to grant the decision-making power and connect the institution and community in the disaster risk management process.

Spatio-Temporal Distribution of Earthquake Disasters in Qinghai Province of China Based on GIS

Qinghai Province is located in the northwest part of China, is part of Qinghai-Tibet Plateau, its special location, abnormal climate, is the frequent occurrence of earthquake disaster area. Under the background of global climate change, earthquake disaster research in Qinghai province is of great significance for ecological protection and disaster prevention. In this paper, the data of earthquake disaster with MS ≥ 5 in Qinghai Province from 1960 to 2022 are collected statistically, and the risk grade distribution map of earthquake disaster is made by using GIS technology with the county and city as the unit. The spatial and temporal distribution law of earthquake disaster is illustrated from the distribution of earthquakes over the years and the annual occurrence frequency. The results show that the earthquake disasters in Qinghai Province are mainly concentrated in the northwest and southwest areas, the central and northern areas are also relatively high distribution, among which Geermu city and Yushu City are more affected. In terms of time, earthquake disasters occurred frequently from 1990 to 2010, and the frequency of disasters decreased slightly from 2010 to 2020, but in the past two years, the geological activity is more frequent, and the disaster incidence is high.

Carbon emissions modeling for smarter carbon footprint decisions: A systematic review

Climate change and environmental deterioration due to greenhouse gas emissions are a major concern around the globe today. This article aims to highlight how various authors have carried out carbon emissions modeling for smarter carbon footprint management and also proffer solutions to the greenhouse gas emissions issue, which is giving rise to global warming and natural disasters across the globe. This study makes use of the Systematic Literature Review (SLR) methodology for identifying, analyzing, and synthesizing articles published from 2015 to 2020, a period of 6 years, on the topic of carbon emissions modeling. The SLR results indicated that there has been a rising interest in the issue of carbon emissions from the period of 2015 to 2020, as seen by the evolution of publications in the area. This can be explained by the increased incidence of natural disasters occurring as a result of the global warming phenomenon due to greenhouse gas emissions. The various ways in which different models have been used for carbon emission analysis and management have been described, while explaining various means by which greenhouse gas emissions can be curtailed to stop the alarming rate of global warming and maintain a sustainable and habitable planet for all.

Assessing Knowledge, Attitudes, and Perceptions of Medical Students Toward Emergency Preparedness and Disaster Medicine in Singapore.

Despite rising incidences of global disasters, basic principles of disaster medicine training are barely taught in Singapore's 3 medical schools. The aim of this study was to evaluate the current levels of emergency preparedness, attitudes, and perceptions of disaster medicine education among medical students in Singapore. The Emergency Preparedness Information Questionnaire (EPIQ) was provided to enrolled medical students in Singapore by means of an online form, from March 6, 2020, to February 20, 2021. A total of 635 (25.7%) responses were collated and analyzed. Mean score for overall familiarity was low, at 1.50 ± 0.74, on a Likert scale of 1 for not familiar to 5 for very familiar. A total of 90.6% of students think that disaster medicine is an important facet of the curriculum, and 93.1% agree that training should be provided for medical students. Although 77.3% of respondents believe that they are unable to contribute to a disaster scenario currently, 92.8% believe that they will be able to contribute with formal training. Despite low levels of emergency preparedness knowledge, the majority of medical students in Singapore are keen for adaptation of disaster medicine into the current curriculum to be able to contribute more effectively. This can arm future health-care professionals with the confidence to respond to any potential emergency.

Training Suggestions for Japanese Head Nurses with Inaccurate Understanding of their Roles and Responsibilities in Initial Phases of Disaster Incidents

Background: During large-scale disasters, hospitals must respond immediately. In such situations, different levelsof nurses have different roles and responsibilities. Head nurses in Japan have two types of responsibilities basedon the shift, day or night. Assuming that head nurses do not clearly recognized these differences due to their lackof appropriate institutional education, this study aimed to clarify actual conditions of institutional education andhead nurses’ level of understanding.Methods: Three questionnaires were developed: one for nursing directors regarding departments’ implementationbased on the disaster response manual and two true/false questionnaires for head nurses regarding theirrecognition of roles and responsibilities in disaster response. Twenty hospitals in a national hospital organizationin Japan, located in two regions, were studied.Conclusion: Of the 17 hospitals that responded, 52.2%–35.3% had written roles, responsibilities, and actionprocedures for head nurses on the day and/or night shift. Education, including orientation and training, wasprovided for the two shifts in 35.3%–23.5% of the hospitals. In terms of the true/false questions, 154 head nursesfrom both shifts responded with high accuracy; however, they did not appear to understand that they werecommanders of the ward on the day shift and of the hospital on the night shift. The results indicate the need tostipulate head nurses’ roles, responsibilities, and action procedures in the disaster response manual and implementinstitutional education and the provision of action assistant tools.

Comparison of Rain Gauge Network and Weather Radar Data: Case Study in Angra dos Reis, Brazil

This paper presents a comparison between rain gauge network and weather radar data in Angra dos Reis city, located in the State of Rio de Janeiro (RJ), Brazil. The city has a high incidence of natural disasters, especially associated with heavy rains in densely populated areas. In this work, weather radar data with a spatial resolution of 1 km were obtained from dual-polarimetric S-band radar operated by the Environmental State Institute of Rio de Janeiro (INEA), located in the Guaratiba neighborhood in Rio de Janeiro city, Brazil; the rain gauge measurements were provided by the National Center for Monitoring and Warning of Natural Disasters (CEMADEN), which is composed of a network with 30 rain gauges covering the studied area. The comparison between the two datasets enables the analysis of which radar products better fit the rain gauge network’s accumulated rainfall by quantifying the uncertainties in precipitation estimates at radar pixels where rain gauges are located. The results indicated that radar products generated with the help of regression techniques obtained from the relation between radar reflectivities and rain gauge measurements were a better fit, constituting essential information while dealing with efficient regulation for rainfall monitoring and forecasting to minimize the risks associated with extreme events.

Identifying Evacuation Needs and Resources Based on Volunteered Geographic Information: A Case of the Rainstorm in July 2021, Zhengzhou, China

Recently, global climate change has led to a high incidence of extreme weather and natural disasters. How to reduce its impact has become an important topic. However, the studies that both consider the disaster's real-time geographic information and environmental factors in severe rainstorms are still not enough. Volunteered geographic information (VGI) data that was generated during disasters offered possibilities for improving the emergency management abilities of decision-makers and the disaster self-rescue abilities of citizens. Through the case study of the extreme rainstorm disaster in Zhengzhou, China, in July 2021, this paper used machine learning to study VGI issued by residents. The vulnerable people and their demands were identified based on the SOS messages. The importance of various indicators was analyzed by combining open data from socio-economic and built-up environment elements. Potential safe areas with shelter resources in five administrative districts in the disaster-prone central area of Zhengzhou were identified based on these data. This study found that VGI can be a reliable data source for future disaster research. The characteristics of rainstorm hazards were concluded from the perspective of affected people and environmental indicators. The policy recommendations for disaster prevention in the context of public participation were also proposed.

Preference reversals in dynamic decision‐making under uncertainty based on regret theory

AbstractThis research aims at preference reversals in dynamic adjusting decisions made by decision‐makers who have regretful emotions. Our model incorporates a utility function that includes the regretful feeling into outcomes under uncertainty. Then, by using the process of backward induction, it analyzes differences in the decisions of three types of decision‐makers with perfect rationality, partially anticipated regret, and fully anticipated regret. Finally, we apply this dynamic adjusting model to emergency plans in which decision‐makers need to choose the best action from multiple selections quickly to reduce the loss caused by disaster incidents and uncertainty. This model allows to compare decisions made by rational and irrational agents, which is a more realistic estimate and measure of several applications in the real life, such as medical services and emergency management.

Brief overview of the factual and onto-epistemological developments of the idea of “civil society” in Japan

In the context of post-industrial societies, there are few resources left to ordinary citizens to respond to the totalizing logic of systemic dynamics characterized by the expansion of economic and formal subjectivity. Likewise, the damage done to the environment and the increasing incidence of natural disasters, both driven by anthropogenic action, make a more complex response from society necessary and, in turn, pose the need to find collective answers to transnational issues. This global situation leads us to consider how civil society can generate community cohesion, leverage common interest and respond to environmental problems. After several ethnographic investigations focused on social change in Japan, we identified some things that, together with the shocking initial images spread globally after the catastrophe of March 11, 2011 in Tōhoku, have helped us take the pulse of the associative Japanese world. These images highlighted some of the fundamental characteristics of Japanese civil society, contributing to the spread throughout the world of a series of constructs that are as typical of a society socially exemplary as they are culturally totalizing. It might seem the eleven years that have elapsed since the Triple Disaster of March 2011 in Japan have provided us with a broad perspective from which to interpret the dynamics of Japanese civil society and public administration in the face of these events. However, we consider that the analysis of socio-historical developments that embody Euro-Atlantic modernity, with indigenous cultural constructs and with globalization, is essential. For this reason, in this article, from the perspective of intellectual history and historical sociology, we will analyse the adaptability of the concept of civil society in Japan and a whole series of social processes that have been gestating for decades and whose development is brought together in entities of great factual importance for the future.
 Received: 31 May 2022Accepted: 25 July 2022

Humanitarian logistics challenges in disaster relief operations: A humanitarian organisations’ perspective

Background: The number of disasters affecting the world has climbed dramatically over the previous decade, from around 220 per year in the mid-1990s to around 350–400 per year now. The rising frequency of natural calamities encouraged the author to conduct a study on humanitarian logistics (HL) and its role in mitigating the consequences of any disaster incidence. Thus, this study aims to outline the issues and challenges affecting HL in disaster relief.Objectives: The purpose of this study is to emphasize the critical role of HL in disaster management and to identify the issues that humanitarian organizations (HO) face while managing their logistics and supply chains during disaster relief operations.Method: The study employed a qualitative approach to investigate the problems affecting HL and supply chains by conducting a literature analysis on disaster management/disaster supply chain. The literature related to HL was reviewed, analyzed, and accordingly, the findings are presented.Results: The results of a thorough evaluation of the basic and contemporary literature on HL identified various challenges, reinforcing the necessity for additional research in HL operations to better the present situation. Additionally, it will lay the groundwork for various stakeholders such as humanitarian/non-profit organizations, governments, and policymakers to plan and develop appropriate solutions.Conclusion: As natural disasters occur often throughout the world; it is critical to handle logistical operations properly and efficiently during disaster relief operations. While none of the disaster situations can be prevented, their impact can be minimized by adequate preparation and response during humanitarian logistical operations.

The effect of natural disasters on household economic hardship during a pandemic

AbstractThe year 2020 provided a rare opportunity to examine how US households experience economic hardship when natural disasters occur during a large‐scale public health crisis, such as the COVID‐19 pandemic. Using a nationally representative sample of adults, this study examines the effect of natural disasters on household economic hardships during a pandemic, measured by food insecurity, mortgage or rent delinquency, and unemployment. The study estimated individual fixed‐effect models after controlling for time trends and time‐variant covariates. We find that while a disaster incident in the community during a pandemic is not associated with household economic hardships in aggregate, its effects are experienced differently by people according to the community‐level severity of COVID‐19 and the individual‐level factors characterized as vulnerability and resilience. Our findings have implications for targeted disaster relief and for building resilience among residents to adverse events.

Effects of changes in UV-B radiation levels on biofilm-forming organisms commonly found in cultural heritage surfaces

Accurate measuring and monitoring methods available since the 1980s have shown that the amount of Ultraviolet B (UV–B) radiation reaching the Earth's surface has increased as a result of degradation of the ozone layer. Since the adoption of the Montreal Protocol in 1987, ozone levels have been recovering successfully. However, in the context of the current climate change, other factors such as changes in cloud patterns and an increased incidence of natural disasters (e.g. fires) may be disrupting this recovery. The present study aimed to investigate the effects of different UV-B radiation levels on biofilms colonising heritage monuments. For this purpose, the effects of current UV-B levels on a biofilm composed of Synechocystis sp. (a cyanobacterium), Bracteacoccus minor (a green alga) and Fusarium sp. (a fungus) were compared at three points along a South-North transect: Portugal, Galicia (NW Spain) and Ireland (from highest to lowest UV-B radiation, respectively). Increased levels of UV-B radiation caused changes in the growth, physiological state and composition of subaerial biofilms, with cyanobacteria being more resistant than green algae to high levels of UV-B. A reduction of fungal growth and extracellular polymer substances (EPS) production was also observed, related to the reduction of biofilm aggregation at high UV-B levels.

The obstacles hierarchy of school disaster preparedness implementation in Mount Sinabung area, Indonesia

The incidence of natural disasters has an impact on various sectors of life, including the education sector. Schools as educational facilities are considered vulnerable areas that need handling steps to reduce disaster risk. As one of the most vulnerable countries to natural disasters, Indonesia already has several policies and programs from the government to address these problems. However, several studies have shown that the implementation did not go according to plan. These studies also reveal that this implementation lies in the local context in which the program or policy is implemented. That is why the study aims to examine the school disaster preparedness implementation in the Mount Sinabung area as one of the disaster-prone areas in Indonesia. This research utilizes the Interpretative Structural Modeling approach to build a hierarchy and classification of obstacles in implementing school disaster preparedness around that area. Data are collected through a combination of observation, interview, and survey techniques in 2017 and 2018 that involved a total of 35 participants. The result showed 14 sub-elements identified as limiting factors of school preparedness implementation in the Mount Sinabung area. Three elements serve as the first level (or the basis/key element) of the obstacles hierarchy: Integration of subject, school policy, and school curriculum. Intervention at the base level will trigger changes and give impact the other upper-four levels of elements. This hierarchy and classification are relevant to the context of the Mount Sinabung eruption and cannot be applied in other areas. This research did not measure the numeric data per sub-element in disaster preparedness. Therefore, the limitations of this study can be directions for future research to examine the implementation in another area by using numeric data. The results of this study also provide major recommendations to several stakeholders. The existing policies regarding school disaster preparedness and their implementation need to be reviewed to improve the result.

Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China.

The Yellow River Basin in Shaanxi (YRBS) has a relatively fragile ecological environment, with severe soil erosion and a high incidence of natural and geological disasters. In this study, a river basin landscape ecological risk assessment model was constructed using landscape ecology principles to investigate the temporal and spatial evolution, as well as the spatial autocorrelation characteristics of landscape ecological risks in the YRBS over a 20-year period. The main findings from the YRBS were that the land use types changed significantly over the span of 20 years, there was spatial heterogeneity of the landscape pattern, and the ecological risk value was positively correlated. The threat of landscape ecological risks in YRBS is easing, but the pressure on the ecological environment is considerable. This study provides theoretical support administrative policies for future ecological risk assessment and protection, restoration measures, and control in the Yellow River Basin of Shaanxi Province.

Pengembangan Sistem Peringatan Dini Cuaca Ekstrem Terintegrasi Berbasis Y-Model Webgis Development Methodology (Y-WDM)

The incidence of hydrometeorological disasters in Indonesia is in the largest percentage for the last 10 years. The development of an integrated extreme weather early warning system is one of the initial processes in a series of hydrometeorological disaster mitigation efforts. Data models, observation and remote sensing become the database in early warning of extreme weather, the officers who carry out early detection of hazards so that they have sufficient waiting time to prepare an effective emergency response plan. In this study, an early warning system was built by implementing the Y-Model WebGIS Development Methodology (YWDM) which is a combination of geographic information systems and web-based application development context. Spatial data processing is carried out using the python programming language, including radar and weather satellite data, surface observation, lightning detection, storm detection and identification, and nowcasting models. Web GIS visualization is built by using JavaScript and php programming language, database management managed using PostgreSQL. The results of the implementation are in the form of a SPACE (Spatial Based Extreme Weather Warning System) framework which Sidarma-Nowcast is a system within the framework. The development of this system shows an increase and the level of improvement in the process of producing and disseminating early warning information.