Showing papers in "International journal of disaster risk reduction in 2020"

How is COVID-19 pandemic impacting mental health of children and adolescents?

Abstract: The coronavirus disease (COVID-19) affected virtually all countries. Uncertain about the health risk and an increasing financial loss will contribute to widespread emotional distress and an increased risk of psychiatric disorders shortly. Posttraumatic, anxiety, and depression disorders are expected during and aftermath of the pandemic. Some groups, like children, have more susceptibility to having long term consequences in mental health. Herein, we made a comprehensive and non-systematic search in four databases (PubMed, Scopus, SciELO, and Google Scholars) to answer the question: What are children's and adolescents' mental health effects of the pandemic? Furthermore, which features are essential for mental health in a pandemic? Results: Seventy-seven articles were selected for full text read, and 51 were included. Children answer stress differently, depending on the development stage. High rates of anxiety, depression, and post-traumatic symptoms were identified among children. Discussion: Symptoms were as expected. New supportive strategies have appeared during this pandemic, but there is no measure of its effectiveness. Some groups seem to be more vulnerable to the mental health burden of the COVID-19 pandemic, and the mitigation actions should prioritize them. The school's role appears to be revalued by society. This review seems to pick good targets to prioritize mitigation actions aiming to spare children not only from the severe cases of COVID-19 but also to help them to deal with the mental health burden of the pandemics.

Catastrophic tailings dam failures and disaster risk disclosure

Abstract: The global mining industry produces billions of tonnes of mine tailings each year. This slurry of waste material is often contained in dams, which are among some of the world’s largest engineered structures. Several recent and catastrophic tailings dam disasters bring the complex interaction between a mine and its local operating context into plain sight. The absence of public, timely, multi-scalar information about the multiple dimensions of this interaction is a normalised feature in the management of tailings dams. This article highlights the importance of establishing and sharing diverse knowledge about tailings dam disaster risk. We argue that the assessment and disclosure of “situated” disaster risk ought to be prioritised; that is, the combined risk of a hazard bearing structure situated within a local context with inherent vulnerabilities. We present a method for examining situated disaster risk of tailings dams by utilising Environmental, Social and Governance (ESG) indicators to screen for risk across eight categories: waste, water, biodiversity, land uses, indigenous peoples’ lands, social vulnerability, political fragility, and approval and permitting. Applied to a global sample of operating mines, the method shows disaster risk potential of existing tailings dams globally. Future application could be used to generate a more complete inventory that includes both established and newly constructed facilities.

Policing in Pandemics: A Systematic Review and Best Practices for Police Response to COVID-19

Abstract: The COVID-19 pandemic has created a range of unforeseen and unprecedented challenges for police departments worldwide In light of these challenges, the goal of this review is to understand the potential short- and long-term effects of disasters and public health emergencies on policing organisations and officers A total of 72 studies were eligible for inclusion, based on their focus on policing and police work during and in the aftermath of natural disasters and public health emergencies Through an extensive review, we compile and analyse the most common issues and best practices identified in the literature, and discuss ‘what works’ in the context of policing such emergencies The literature reveals four categories of issues predominantly raised in this context, namely police-community relations, the mental health and wellbeing of officers, intra-organisational challenges, as well as inter-agency collaboration and cooperation Based on our review and analysis, we offer a list of recommendations relevant for policing the current COVID-19 outbreak The findings of this review have immediate implications for policing during COVID-19 but also cover long-term effects, providing valuable recommendations for after the crises has passed

Determining disaster severity through social media analysis: Testing the methodology with South East Queensland Flood tweets

Abstract: Social media was underutilised in disaster management practices, as it was not seen as a real-time ground level information harvesting tool during a disaster. In recent years, with the increasing popularity and use of social media, people have started to express their views, experiences, images, and video evidences through different social media platforms. Consequently, harnessing such crowdsourced information has become an opportunity for authorities to obtain enhanced situation awareness data for efficient disaster management practices. Nonetheless, the current disaster-related Twitter analytics methods are not versatile enough to define disaster impacts levels as interpreted by the local communities. This paper contributes to the existing knowledge by applying and extending a well-established data analysis framework, and identifying highly impacted disaster areas as perceived by the local communities. For this, the study used real-time Twitter data posted during the 2010–2011 South East Queensland Floods. The findings reveal that: (a) Utilising Twitter is a promising approach to reflect citizen knowledge; (b) Tweets could be used to identify the fluctuations of disaster severity over time; (c) The spatial analysis of tweets validates the applicability of geo-located messages to demarcate highly impacted disaster zones.

Vulnerability and vulnerable groups from an intersectionality perspective

Abstract: In general, the identification and protection of vulnerable groups in the case of hazards or when a crisis unfolds is an issue that any crisis and disaster risk management should address, since people have different levels of exposure to hazards and crises. In this article, we promote the application of the intersectionality perspective in the study of vulnerable groups, and we call for intersectionality as a guiding principle in risk and crisis management, to provide a better and more nuanced picture of vulnerabilities and vulnerable groups. This can help national and local authorities and agencies to formulate specific guides, to hire staff with the skills necessary to meet particular needs, and to inform vulnerable groups in a particular way, taking into account the differences that may coexist within the same group. Intersectionality allows us to read vulnerability not as the characteristic of some socio-demographic groups. It is rather the result of different and interdependent societal stratification processes that result in multiple dimensions of marginalisation. In this vein, we argue that research should focus on 1) self-perceived vulnerability of individuals and an intersectionality approach to unpack vulnerable groups; 2) cases of crises according to the level and/or likelihood of individual exposure to hazards, to better nuance issues of vulnerability.

Multi-hazard disaster studies: monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques

Abstract: Every year man-made and natural disasters impact the lives of millions of people. The frequency of occurrence of such disasters is steadily increasing since the last 50 years, and this has resulted in considerable loss of life, destruction of infrastructure, and social and economic disruption. A focussed and comprehensive solution is needed encompassing all aspects, including early detection of disaster scenarios, prevention, recovery, and management to minimize the losses. This survey paper presents a critical analysis of the existing methods and technologies that are relevant to a disaster scenario, such as WSN, remote sensing technique, artificial intelligence, IoT, UAV, and satellite imagery, to encounter the issues associated with disaster monitoring, detection, and management. In case of emergency conditions arising out of a typical disaster scenario, there is a strong likelihood that the communication networks will be partially disrupted; thus the alternate networks can play a vital role in disaster detection and management. It focuses on the role of the alternate networks and the associated technologies in maintaining connectivity in various disaster scenarios. It presents a comprehensive study on multiple disasters such as landslide, forest fire, and an earthquake based on the latest technologies to monitor, detect, and manage the various disasters. It focuses on several parameters that are necessary for disaster detection and monitoring and offers appropriate solutions. It also touches upon big data analytics for disaster management. Several techniques are explored, along with their merits and demerits. Open challenges are highlighted, and possible future directions are given.

The role of social capital on proactive and reactive resilience of organizations post-disaster

Abstract: With disruptive events of higher magnitudes increasing globally, building resilience has become a priority for many organizations. Existing studies have prioritized the contribution of internal factors to building organizational resilience. This study examines social capital emanating from supply chain partners as an external factor building organizational resilience. Using social capital theory, we develop a conceptual model that postulates three dimensions of social capital (cognitive, structural and relational) as antecedents of both proactive and reactive organizational resilience. The model is tested on a sample of Chinese firms that survived the 2008 Sichuan earthquake. The findings show that not all facets of social capital contribute to the development of organizational resilience. While stronger structural capital improves proactive organizational resilience, relational capital only improves reactive organizational resilience. The findings have both theoretical and managerial implications for post-disaster resilience building.

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

Abstract: Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control Iran is one of the most seismically active countries in the world The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1 The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95% A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

AHP-GIS analysis for flood hazard assessment of the communities nearby the world heritage site on Ayutthaya Island, Thailand

Abstract: Thailand faced the worst flooding in half a century in 2011. A previous flood had harshly affected the UNESCO World Heritage Site (WHS) and the surrounding communities. The aims of this study were to assess the spatial distribution of flood hazards and analyze how past experience contributed to community flood readiness. Both GIS analysis and household surveys (n = 405) were systematically performed. According to the Analytic Hierarchy Process (AHP) technique, approximately half of the whole community area (52.63%) and the WHS (44.8%) were at high risk of flooding. Pratuchai, the most populated subdistrict, was at the highest flood hazard level. Runoff and road density were the main contributors to flooding in a community. Regression analysis found that there was a negative correlation between past flood experience and residents’ flood readiness. According to the cluster analysis, there were two groups of respondents: i) those who had more experience with both flood hazards and the inaccessibility of urban services during a flood and were less likely to prepare themselves for future floods (n = 313) and ii) those who had less experience with floods and the inaccessibility of urban services and were more likely to prepare for future floods (n = 92). This implies, in short, that the local populace had not learned much from past experiences of a flood disasters. Advance urban flood management, multi-hazard zoning, and effective flood risk communication are urgently needed to improve flood resilience in the WHS communities.

Recovery from the COVID-19 pandemic: Distress and resilience

Abstract: The current study analyzed repeated responses to the coronavirus. Data for the first phase was gathered during the peak of the COVID-19 pandemic crisis in Israel (T1), which included the overall lock-down of the Israeli society. The repeated measurement was conducted approximately two months later, on the initial phase of lifting the lock-down (T2). The sample size was 300 people. Results indicated four significant differences between the first and the second measurements: Sense of danger, distress symptoms, and national resilience significantly decreased, while perceived well-being increased at T2. No significant differences were noted between the two measurements regarding individual and community resilience and economic difficulties. The data indicated that the highest decrease in national resilience was accounted for by low respondent trust in governmental decisions during the COVID-19 crisis. The negative impact of the COVID-19 pandemic on the participants was determined by two indicators: level of distress symptoms and sense of danger. Path analyses showed that five variables significantly predicted these two indicators. Their best predictor at T1 and T2 was well-being followed by individual resilience, economic difficulties due to the pandemic crisis, community resilience, and gender. It was concluded that psychological attributes may help in decreasing the impact of the threats of the COVID-19 pandemic.

Hazard and vulnerability in urban flood risk mapping: Machine learning techniques and considering the role of urban districts

Abstract: Urban flood risk mapping plays a decisive role in urban management and planning, especially in reducing flood damages. In this study, a flood risk map was produced for Kermanshah city (Iran) by combining flood hazard and flood vulnerability maps. Based on effective factors of urban flooding, flood hazard maps were generated using two machine learning models: Maximum Entropy (MaxEnt) and Genetic Algorithm Rule-Set Production (GARP). These models were developed on 117 flood sites which were identified on the reports and field surveys for Kermanshah city, and 163 non-flooded points. Economic, social, and infrastructure criteria were considered to analyze flood vulnerability. The sub-criteria were defined based on social and cultural structure in developing countries and urban infrastructure facilities involved in the floods. Fuzzy Analytical Hierarchical Process method (FAHP) was applied to determine the overall weight vector. The results demonstrated that the MaxEnt model had a better performance than the GARP model based on two common indices which are the area under the receiver-operator characteristic curve (AUC-ROC = 96.76–98.32%) and kappa statistic (Kappa = 0.82-0.86). These findings showed that machine learning models provide reliable results for areas where data access is challenging, especially in developing countries. The results also indicated that infrastructure criterion has the highest impact weight on the vulnerability. In general, population, urban texture, and distance to the major drainage channels are the most important factors in increasing flood risk. Also, the vulnerability of an urban neighborhood greatly increases the risk of flooding.

Evaluating solutions to overcome humanitarian supply chain management barriers: A hybrid fuzzy SWARA – Fuzzy WASPAS approach

Abstract: This study intends to explore humanitarian supply chain management barriers (HSCMBs) and evaluate solutions for overcoming these barriers to improve humanitarian supply chain management (HSCM) implementation. This study aims to evaluate the solutions to overcome HSCMBs using a hybrid framework that consists of fuzzy step-wise weight assessment ratio analysis (SWARA) and a fuzzy weighted aggregated sum product assessment (WASPAS). This study identifies 29 HSCMBs and 20 solutions to overcome these HSCMBs through a literature review and brainstorming session conducted among experts. Fuzzy SWARA is applied to compute the weight of HSCMBs and evaluate the relative importance of each HSCMB. Fuzzy WASPAS is applied to rank the solutions to overcome HSCMBs for efficient and effective HSCM implementation. The outcome of this study suggests that “Long term strategic planning for humanitarian operation” is the highest-ranked and most immediate solution, followed by “Collaboration, cooperation, and coordination among humanitarian supply chain actors” to overcome HSCMBs. Disaster relief aid agencies and stakeholders may focus on the solutions to overcome HSCMBs for effective humanitarian aid operations and to improve strategies of HSCM. This study helps humanitarian logisticians to formulate improved strategies for better operational performance in pre and post-disaster phases.

Use of social media in crisis management: A survey

Abstract: Emergency situations arising out of natural disasters like tsunami, earthquakes, floods, hurricanes or man-made ones like terror strikes, riots, accidents, etc. cause tremendous social and economic loss and badly affect the poor in low-income economies, in particular. In this paper, we attempt to see and analyze the relationship between emergencies and online social media, especially Twitter, Facebook, and Youtube. Specifically, we look at three important issues. First, we try to see the effect of occurrence of emergencies on social media. Second, when there is a sudden surge of posts in social media due to the occurrence, how that deluge of data can be effectively extracted and processed to create situational awareness and minimize the damage due to the disaster. Third, how different social media posts can help different government and other agencies to get prepared and to take necessary steps to manage emergencies in order to minimize the loss. In this survey, the papers centered around emergencies and its effect on social media and different organizations related to crisis management are considered that are published in the past decade.

Leveraging a Bayesian Network approach to model and analyze supplier vulnerability to severe weather risk: A case study of the U.S. pharmaceutical supply chain following Hurricane Maria

Abstract: The United States government has identified the health care sector as part of the critical infrastructure for homeland security to protect citizens against health risks arising from terrorism, natural disasters, and epidemics. Citizens also have expectations about the role that health care plays in enjoying a good quality of life, by providing response systems to handle emergencies and other illness situations adequately. Among the systems required to support desired performance levels is a robust and resilient pharmaceutical supply chain that is free of disruption. Shortages of drugs place undue pressure on healthcare providers to devise alternative approaches to administer patient care. With climate change expected to result in increasingly severe weather patterns in the future, it is critical that logistics engineers understand the impact that a catastrophic weather event could have on supply chain disruption to facilitate the design of supply systems that are robust and resilient. This study investigates the main causal and intermediate events that led to risk propagation in, and disruption of, the U.S. pharmaceutical supply chain following Hurricane Maria. A causality Bayesian model is developed to depict linkages between risk events and quantify the associated cumulative risk. The quantification is further examined through different advanced techniques such as predictive inference reasoning and sensitivity analysis. The general interpretation of these analyses suggests that port resilience is imperative to pharmaceutical supply chain performance in the case of Puerto Rico.

A place-based socioeconomic status index: Measuring social vulnerability to flood hazards in the context of environmental justice

Abstract: This paper proposes a national-level socioeconomic status (SES) index to measure place-based relative social vulnerability and socioeconomic inequalities across Canada. The aim is to investigate how disparities in overall socioeconomic status influence environmental justice outcomes for Canadian flood risk management planning and funding structures. A micro-dataset of the 2016 Canadian census of population was used to derive a comprehensive SES index over 5739 census tracts. The index comprises 49 theoretically-important and environmental policy-relevant indicators of vulnerability that represent diverse aspects of socioeconomic, demographic, and ethnicity status of Canadians. Bartlett's test of sphericity, Kaiser-Meyer-Olkin measure of sampling adequacy, Cronbach's alpha scale reliability, and goodness-of-fit for factor's solution were employed to assess validity, reliability, and consistency in the dataset before applying principal components analysis. Our data revealed 11 statistically-significant multidimensional factors, which together explained 80.86% of the total variation. Levene's homogeneity of variance test disclosed a considerable socioeconomic disparity across census tracts, census metropolitan areas (CMAs), and provinces/territories in Canada. Social vulnerability tends to be geographically stratified across Canada. For example, Drummondville, Saguenay, and Granby CMAs (all in Quebec) had the lowest SES scores, whereas Vancouver and Toronto CMAs had the highest SES scores. Prevalence of spatial variations in the SES scores has significant implications for appraising overall social well-being and understanding the relative social vulnerability of population subgroups. The new place-based SES index has potential for assessing environmental justice outcomes in flood risk management at the census tract level.

Public perception and attitudes to disaster risks in a coastal metropolis of Saudi Arabia.

Abstract: Disaster risk reduction is an increasingly important policy issue, especially in developing countries that suffer most of the global human and economic losses associated with disasters. Indeed, public awareness and attitudes can help in disaster risk reduction and management efforts toward reducing mortality and economic losses. In Saudi Arabia, many cities have been recently experiencing incidences of disasters, such as floods, disease epidemics, and sandstorms. However, studies on public perception of disaster risk in the country are few and nascent. Therefore, based on a questionnaire survey (n = 683), this paper explores public perception and attitudes to disaster risks in Dammam, a coastal metropolis in Saudi Arabia. The findings indicate that although almost two-thirds (64.7%) of the participants are aware of disasters, and 81% are concerned about disaster risks, less than half (47.3%) believe that their settlements could be at risk. While 37% opine that disasters are caused by both natural factors and human activities, about half (54%) indicate that they can personally contribute to reducing disaster risks. Chi-square analysis indicates a significant positive relationship between place of residence and perception of disaster risks (χ2 (6) = 56.18, p

Flood management in India: A focussed review on the current status and future challenges

Abstract: Despite massive investments and continuous flood-control efforts in India, the socio-economic damages and death toll continue to remain high. Undoubtedly, the process of flood management in India is very complex due to the influence of several socio-hydroclimatological factors, such as climate change, sea level rise, and socio-economic dynamics. While these factors influence the intensity and frequency of flood events, factors explicitly related to the process of flood management, such as the improper execution of traditional structural measures, the lack of the proper implementation of schemes, lackadaisical execution of traditional structural measures and end-to-end management of the flood management programs/practices, ensure only partial protection. This review article identifies the region-specific flood problems in India and discusses the initiatives undertaken by major Indian flood management agencies, with an emphasis on the current ongoing flood management practices. The effectiveness of these practices in the long term is discussed, and specific gaps are identified. The recommendations provided in this article may be useful to guide stakeholders and policymakers in formulating and implementing sustainable flood management plans for improved flood resilience.

Knowledge management practices in disaster management: Systematic review

Abstract: Examples of knowledge management (KM) practices are common in a disaster context. However, disaster management is a system with many components, and it is not clear how KM practices can be applied in all major phases of disaster management cycle. In this context, this research will answer the following questions: i) What are some of the KM practices used in disaster management? and ii) What are some of the implications of KM practices on disaster management performance? Moreover, the key findings of this study acknowledge the recognition of research gaps that need to be addressed and they can provide future researchers with a research agenda. This article provides a systematic review of the 72 selected papers from SCOPUS databases on KM in the context of disaster management to evaluate the state of the art, finding existing gaps and establishing a direction for further studies. This review explores the use of KM in all phases of disaster management to confirm the advantages of knowledge management in reducing disaster impacts and enhancing disaster resilience.

The fiqh of disaster: The mitigation of Covid-19 in the perspective of Islamic education-neuroscience.

Abstract: Fikih Kebencanaan (Coping with Disaster) is a product of Muhammadiyah's ijtihad to respond to contemporary problems, especially geological and non-geological disasters, which later become the normative foundation for the mitigation of health disasters such as the Covid-19 pandemic. The paradigm of the present research is a transdisciplinary qualitative type with a phenomenological approach. The research analyzed the reasoning of Fikih Kebencanaan and its actualization in Covid-19 mitigation, the medical health movement and the reconstruction of fiqh of worship during an emergency in particular, and how to deal with the disaster theologically in general. The results showed that the reasoning of Fikih Kebencanaan was expanded in terms of medical, theological, and educational movements. Medical movement is a health movement in the form of providing 74 Covid-19 Standby Hospitals capable of accommodating 3917 patients or 36.15% of the total number of cases in Indonesia, followed by the distribution of masks, gloves, and foods to 401,209 Covid-19 affected victims. The theological movement was in the form of religious provision in which Muhammadiyah attempted to reconstruct classical Islamic jurisprudence of the rule of worship to adapt to an emergency. In contrast, the Indonesian Council of Ulema (MUI) applied zoning. The educative movement was a preventive effort to counter narration stemming from micro-celebrity Da'i (Islamic preacher) & Influencers (religious preachers) tried to circumvent religious provisions with their viral statements on social media. This effort was realized by developing neuroscience Islamic education with learning media in visualization that combined modern comics and contemporary cartoons with cinematic narratives. The neuroscience Islamic education movement tried not to use the dogmatic-monolithic approach as in classical education.

Integrated ANN-cross-validation and AHP-TOPSIS model to improve earthquake risk assessment

Abstract: The current study presents a novel combination of artificial neural network cross-validation (fourfold ANN-CV) with a hybrid analytic hierarchy process-Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) method to improve the earthquake risk assessment (ERA) and applied it to Aceh, Indonesia, to test the model. Recent studies have suggested that neural networks improve probability mapping in a city scale. The network architecture design with probability index remains unexplored in earthquake-based probability studies. This study explored and specified the major indicators needed to improve the predictive accuracy in probability mapping. First, probability mapping was conducted and used for hazard assessment in the next step. Second, a vulnerability map was created based on social and structural factors. Finally, hazard and vulnerability indices were multiplied to produce the ERA, and the population and areas under risk were calculated. Results show that the proposed model achieves 85.4% accuracy, and its consistency ratio is 0.06. Risk varies from very high to high in the city center, approximately covering an area of 23% (14.82 km2) and a total population of 54,695. The model's performance changes on the basis of the input parameters, indicating the selection and importance of input layers on network architecture selection. The proposed model is found to generalize better results than traditional and some existing probabilistic models. The proposed model is simple and transferable to other regions by localizing the input parameters that contribute to earthquake risk mitigation and prevention planning.

Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model

Abstract: The prerequisite for earthquake risk estimation is vulnerability assessment. Therefore, estimating vulnerability is necessary to reduce future fatalities. This study aims to evaluate the earthquake vulnerability assessment (EVA) in Banda Aceh by using the multi-criteria decision-making approach through an analytical hierarchy process and VIseKriterijumska Optimizacija I Kompromisno Resenje method using a geographical information system. Banda Aceh City is located close to the Great Sumatran Fault in North Sumatra. Several factors were used to produce social vulnerability, structural vulnerability, and geotechnical vulnerability indices. Subsequently, the adopted approaches were integrated and applied to estimate the criteria weight, priority ranking, and alternatives of criterion by applying the pair-wise comparison at all levels. Finally, vulnerability layers were superimposed to estimate the earthquake vulnerability index and produce the vulnerability map. Results showed that the central part of the city exhibits high to very high vulnerability. A tiny part of the northern–central part is under severe vulnerability conditions. The consistency ratios for all three vulnerability layers were 1.9%, 4.6% and 5.5%. The consistency ratios for the final EVA was 1.9%. The developed map revealed that 3.39% of Banda Aceh City falls under very high, 11.86% high, 23.73% medium, 28.82% low, and 32.20% of very low vulnerability areas. The proposed method for the EVA provides useful information that could assist in earthquake disaster mitigation.

A prioritization RVS methodology for the seismic risk assessment of RC school buildings

Abstract: The seismic vulnerability assessment of critical facilities, such as hospital and school buildings, is of paramount importance to avoid the collapse in ordinary conditions and to guarantee their immediate functionality in the post-earthquake emergency. Due to the high number of school buildings, and to the need to perform the assessment in a short time, a simple methodology for ranking the more vulnerable buildings through a seismic risk index is highly desirable. In this study, a Rapid Visual Screening (RVS) methodology is proposed. The method aims to prioritize the buildings prone to higher seismic risk and to assist decision-makers in the implementation of seismic risk reduction strategies. The methodology allows to assess the seismic risk of reinforced concrete (RC) school buildings through the compilation of a factsheet. The main sources of structural and non-structural vulnerability are considered in the survey form. The influence of the hazard and exposure are also accounted for in the calculation of the safety index through simplified parameters. The proposed RVS method can be quickly applied to a large number of buildings to identify those that require more accurate analyses. The proposed methodology has been applied to a sample of typical school buildings in Apulian Region, Southern Italy. The results obtained using the proposed RVS method were compared with those of more advanced numerical analyses in order to assess its effectiveness.

A two-stage stochastic model for location planning of temporary medical centers for disaster response

Abstract: Devastating effects of disasters and global crises on people increase the importance of humanitarian logistics studies for pre and post-disaster stages. Location planning of Temporary Medical Centers/field hospitals is one of the most important problems for disaster response. We aimed to determine the location and number of temporary medical centers in case of disasters by considering the locations of the existing hospitals, casualty classification (triage), capacities of medical centers and possibilities of damage to the roads and hospitals. Besides, we aimed to assign different casualty classes to these medical centers for emergency medical response by considering the distances between disaster areas and medical centers. For this purpose, a two-stage stochastic programming model was developed. The proposed model finds an optimal TMC location solution while minimizing the total setup cost of the TMCs and the expected total transportation cost by considering casualty types, demand, possibilities of damage to the roads and hospitals, and distance between the disaster areas and the medical centers. In the model, α-reliability constraints for the expected number of unassigned casualties were also used. Besides, the model was reformulated without triage, in order to understand the impact of casualty classification on the solution of the problem. We performed a real case study for the district of Kartal expected to be widely damaged in the possible Istanbul earthquake, and a sensitivity analysis was made. The analysis of the results offer some managerial insights associated with the number of temporary medical centers’ needed, their locations, and additional hospital capacity requirements.

Factors affecting flood-induced household vulnerability and health risks in Pakistan: The case of Khyber Pakhtunkhwa (KP) Province

Abstract: In recent years the adverse impacts of climate change on the natural environment and the multiple threats it poses to human health, especially in the Global South, have become increasingly evident and these are likely to increase in the near future, with more people likely to be risk. This study investigates households' vulnerability to public health risks in disaster-prone areas of Pakistan. It uses a dataset of 600 households, based on structured questionnaire with household heads from two severely flood-affected districts (Nowshera and Charsadda) in Khyber Pakhtunkhwa (KP). Household vulnerability to flooding and related health problems are assessed through a logistic regression model. The results reveal that respondents' socio-economic and demographic attributes, such as age, gender, education, income, the materials out of which their house is constructed, past experience of floods and social networks are the key factors influencing their flood vulnerability. Households' health vulnerability is affected by their access to information and health facilities, their sanitary arrangements, distance from the main health facility and previous damage to water supply and health facilities from the flood in 2010. The findings suggest the need to overcome households' flood and health vulnerability through capacity building, training and sustainable mitigation efforts. At the governmental level, a comprehensive and realistic stakeholder analysis is needed to ensure the active involvement of all stakeholders, to generate their commitment and support and to identify what actions are most needed. Any actions to minimize household health risks will require an integrated, multi-sector, approach which would increase efficiency through pooling resources and skills.

Benefits, barriers, and incentives for improved resilience to disruption in university teaching.

Abstract: Pandemics, earthquakes, fire, war, and other disasters place universities at risk. Disasters can disrupt learning and teaching (L&T) for weeks to months or longer. Some institutions have developed business continuity plans to protect key organisational services and structures, allowing L&T to continue. However, little research touches on how academics, learners, and communities of practice might respond before, during, and after disasters and how their resilience to disruption can be fostered to reduce impacts on L&T. In this research, we investigated academics' perceptions of building resilience to major L&T disruptions in the New Zealand context. Specifically, we explored how academics characterise a resilient academic and institution, and identified the benefits, barriers, and incentives to building resilience. We used a pragmatic theoretical approach with a mixed methods methodology, to categorise the results within three distinct levels (individual, school/department, and institution), supporting the design and implementation of resilience-building strategies for academics and institutional leaders. We found that support, community, leadership, and planning at universities are critical in building and inhibiting resilience. Participants reported several 'high impact' incentives, addressing multiple barriers, that could be used to kick-start resilience. Online and flexible learning are key opportunities for resilience-building, but universities should not underestimate the importance of face-to-face interactions between staff and learners. Our results provide a strong starting point for practitioners and researchers aiming to understand how universities can foster resilience to major disruptions and disasters on university teaching.

Disaster resilience through big data: Way to environmental sustainability

Abstract: Disaster management is a growing concern and priority throughout the world and “resilience” is increasingly viewed as a key capacity related to disaster and post-disaster management and development. Recent research highlights how resilience is enhanced through the use of “big data” technologies that improve the speed and effectiveness of linkages between disaster information and systemic response. Summarizing and discussing this research, this study highlights and substantiates the potential of big data strategies to help mitigate the risks and impact of socio-ecological vulnerability. Based on a qualitative desk review and analyses of secondary data, resilience is framed as a function of the adaptive, absorptive and transformative capacity of socio-political systems to withstand and cope with the adverse effects of disaster. In addition, this study emphasizes the major principles and components of effective big data use; e.g., open source tools, strong infrastructure, local skill development, context-specific data sources, ethical data sharing and experiential learning. This study reveals some important big data technologies that can be easily used in the different phases of disaster management and enhancing resilience such as remote sensing imagery, social media data, crowdsourced data, geographic information system (GIS), and mobile metadata. The findings hold major relevancy for policymakers, administrators, and related stakeholders responsible for taking action before, during and after disasters through training, early warning systems, emergency evacuation, relief distribution and other key infrastructural components.

Endurance or decline of emergent groups following a flood disaster: Implications for community resilience

Abstract: Previous social psychological research has shown that new group relationships can emerge among disaster survivors due to a shared sense of common fate, facilitating the provision of social support and collective coordination. Emergent groups and the support they mobilize over time can be crucial for the recovery period and overall community resilience, but such communities decline over time. What is not known are the psychological group processes that might contribute to or mitigate this decline. In this interview study with 19 flood-affected residents from the city of York, UK, conducted 15 months after the 2015 floods, we explored the factors that affected the decline or persistence of emergent groups in a post-flood community. Through a theoretical thematic analysis, we show how emergent groups can decline due to a lack of common fate, post-flood identity shifts, or perceived inequality. However, we also show that a sense of togetherness can be maintained through past shared adversity, due to the persistence of secondary stressors, intentional collective acts such as commemorations, and through the ongoing provision of social support. Implications for policy and practice are discussed.

Comparative analysis of Multi-Criteria Decision-Making methods for flood disaster risk in the Yangtze River Delta

Abstract: Nowadays, floods are occurring frequently around the world, and the Yangtze River Delta in China is one of the most vulnerable areas. This study used the Yangtze River Delta as the research object, established the flood disaster risk analysis model, calculated the indicator weights using the entropy weight method, and used three Multi-Criteria Decision-Making (MCDM) methods to compare and analyze the flood disaster risk in four administrative units of Yangtze River Delta (Shanghai City, Jiangsu Province, Zhejiang Province, and Anhui Province). Based on the weight estimation results, vegetation coverage was the priority in all evaluation criteria, followed by the proportion of the illiterate population aged 15 and over, drainage density, proportion of crop sown area, and building density. The ranking results show that the flood disaster risk is highest in Jiangsu, followed by Anhui. Shanghai and Zhejiang ranked third and fourth, respectively. Furthermore, a sensitivity analysis of the indicator weights was conducted considering that the ranking results mainly depend on the criteria weight. The results of the sensitivity analysis show that the main factors influencing the flood disaster risk level in the Yangtze River Delta are agricultural factors, followed by population density, drainage density, and the number of medical and health institutions. Also, in terms of meteorological and geographical conditions, exposure, vulnerability, and disaster loss, Jiangsu has the highest flood disaster risk, while Anhui has the highest flood disaster risk in terms of emergency and recovery capabilities. The findings can provide useful information on disaster prevention and mitigation managers.

An Integrated Approach to Sustainable Development, National Resilience, and COVID-19 Responses: The Case of Japan

Abstract: The COVID-19 pandemic has led to historic economic fallout. To protect public health and stabilize incomes, governments have implemented massive fiscal stimulus packages. These fiscal supports are crucial, though there is concern that sustainable and resilient development will be sacrificed in the rush to preserve incomes and industries. The aim of the paper is to review whether the Japanese governments' responses in terms of financial stimulus considers longer term resilience and sustainability. This paper reviews pertinent academic literature and publicly available data from governments and organisations. The research is a rapid analysis of emerging information provided by the government of Japan and other international organisations. Using the case of Japan, this paper suggests that it is possible both to protect public health and essential services, while also promoting resilience and sustainability. Japan's integrated solutions show that pandemic response can include accelerated decarbonization and resilient, sustainable development. The paper also warns also that failure to act on long-term sustainability risks increased inequality, higher opportunity costs, cascading hazards, and further retreat from planetary thinking and globalism.

Hazards, food insecurity and human displacement in rural riverine Bangladesh: implications for policy

Abstract: This paper examines the impacts of climate-induced hazards, especially riverbank erosion, on livelihoods and food security, and the ways in which susceptible households respond. The study uses survey data collected from 380 riverbank erosion-prone rural households in Bangladesh, along with data from focus group discussions involving household heads from severe erosion-prone areas. A Food Security Index (FSI) has been developed to improve understanding of the extent of households' food insecurity where 3 indicates food security and 1 minimal security. Over the past 10 years, about a third of households have lost their homestead more than three times and 57% have lost at least once. The overall FSI value of 2.06 indicates households' difficulties in managing family food requirements throughout the year. Migration co-exists with vulnerable households' food security with households that have no or limited agricultural land, coupled with inadequate employment opportunities, are more inclined to migrate. Households that are struggling to make a living through farming are responding by coping and adaptation. Interventions such as access to institutions and credit facilities, human capital development and a package of technologies through agro-ecological based research for emerging char land (sandbars) are required to build resilience of the riparian households as well as improve their food security and livelihoods.