Human-made Disasters Research Articles

Assessment of Urban Resilience to Floods: A Spatial Planning Framework for Cities

Urbanization-led economic growth drives infrastructure investments and population accumulation in cities, hence exploiting natural resources at an extreme rate. In this context, coastal cities have become vulnerable to climate change-induced extreme weather events and human-made disasters in recent history, where effective measures to improve the resilience of cities are pivotal for developing sustainable living environments. This study proposes a framework for assessing urban resilience to natural disasters (floods) using bottom-up spatial interactions among natural, physical, and social systems within cities and regions. It is noted that seminal studies focus on either the mitigation or adaptation strategies within urban environments to assess disaster resilience, where limited multidisciplinary and operational models hinder evaluations at the city scale. Therefore, urban system interactions and quantifiable parameters proposed in this framework are essential for policymakers and disaster management agencies in the timely allocation of resources to optimize the recovery process. Moreover, spatial planning agencies can adopt resilience mapping to identify the potential risk zones and orient sustainable land use management. Urban resilience can be embodied in spatial strategies with the operational framework proposed here, and future urban growth scenarios can be tested in multiple disaster conditions.

Emergency budgeting for resilience during the war. The case of Ukraine

IMPACT The article provides insights into the dynamics of emergency budgeting and budget resilience in nations facing human-made disasters, taking the Russian full-scale invasion of Ukraine as a case study. These insights are crucial for policy-makers in both Ukraine and other countries facing socio-economic disruption due to armed conflicts. The research emphasizes the importance of adapting budgeting practices to respond to the challenges and uncertainties of the war, the critical role of international aid in sustaining national budgeting resilience and the need for transparency and accountability in the budgeting processes. As global conflicts and geopolitical tensions continue to rise, the principles of resilience and emergency budgeting discussed in this article have broader implications for the international community—particularly for nations vulnerable to conflict, economic crisis or other human-made disasters.

Evaluation of priority index for enhancing the seismic resilience of tunnels

Tunnels are essential infrastructure elements, offering significant economic, social, and environmental benefits. However, they are particularly vulnerable to seismic risks, especially in regions with high seismic activity. Given their importance in terms of safety, economy, and social factors, it is crucial for the relevant authorities to prepare for natural and human-made disasters by enhancing the seismic resilience of tunnels. In Algeria, where the number of tunnels is high, this necessity is particularly urgent.This article proposes a prioritization model aimed at improving the seismic resilience of tunnels, based on the expertise of specialists and structured into three main steps. The first step involves identifying key criteria, including the tunnel's condition, design phase, availability of alternative routes, social importance, geometric shape, and seismic zone. The second step applies the Analytic Hierarchy Process (AHP) to calculate the weights of the criteria and incorporates expert opinions through the Euclidean Distance-Based Aggregation Method (EDBAM). Finally, the third step establishes the Priority Index for Tunnel Seismic Resilience Improvement (PIT).The model was tested on five tunnels, and the classification obtained based on the priority index was found to be well aligned with the observed reality on the ground.

Building Back Better: Exploring the Resilience of Schools in Disaster Recovery

As natural and human-made disasters escalate globally, the urgency to rebuild resilient communities is increasingly evident. With this study, Building Back Better: Exploring the Resilience of Schools in Disaster Recovery explores the experiences, disaster recovery, challenges, coping mechanisms, and insights of three school administrators and four teachers designated as school Disaster Risk Reduction coordinators in the Monkayo East District of Davao de Oro. This study utilized qualitative phenomenological study to delve into the lived experiences of educational professionals during post-disaster recovery. This research aims to gain a deep understanding of the challenges, coping mechanisms, and insights from a purposive sample of four teachers designated as school Disaster Risk Reduction coordinators and three school administrators who have directly engaged with the recovery processes following natural disasters. The data were gathered through an in-depth face-to-face interview and used an audio recorder to record the discussion. The significant finding from the study is the multifaceted and long-lasting impact of disasters on students' learning environments. This finding highlights how disasters not only cause physical damage to school infrastructure but also disrupt the educational process, widen achievement gaps, and affect the emotional well-being of students. The disruption of normal routines and the psychological stress experienced by students underscore the critical need for comprehensive recovery strategies, including academic support and mental health resources, to help students regain stability and continue their education effectively. This emphasizes the importance of preparedness and resilience in educational institutions to mitigate the impact of such crises. This study highlights the need for timely assessments, repairs, and coordination with local authorities to ensure the structural integrity of school facilities. It underscores the importance of disaster preparedness and the implementation of robust recovery strategies to mitigate the impact on the educational environment and maintain a safe and conducive learning space. This focus on infrastructure is foundational, as it directly influences the ability of schools to function effectively post-disaster. Teachers and school heads are pivotal in disaster risk reduction within educational institutions. They create safety plans, organize drills, and educate students on emergency procedures, fostering a culture of preparedness. School heads provide leadership, while teachers act as first responders, guiding students to safety and offering necessary care. Collaboration between teachers, school heads, and stakeholders is crucial for a resilient school environment. By involving the entire school community in planning and implementing safety measures, schools can effectively respond to disasters, ensuring the safety and well-being of everyone involved. This partnership promotes a proactive approach to disaster preparedness, making safety a priority in all school activities.

Requirements Engineering for a Drone-Enabled Integrated Humanitarian Logistics Platform

The pursuit of ameliorating humanitarian logistics (HL) through the integration of cutting-edge technologies has received significant attention in recent years. AIRDROP is a visionary platform conceived to offer a cohesive disaster management approach spanning from preparedness to recovery of a wide range of natural and human-made disasters. AIRDROP aims to be a scalable, modular and flexible solution, employing an array of drones of different sizes and payload capabilities, able to provide different HL services to first responders and operational decision-makers. This study aims to elicit, specify and validate the requirements for AIRDROP to ensure their applicability across a broad spectrum of disaster scenarios and the entire disaster management continuum. This research utilized a thorough literature review and expert consultations to systematically elicit and specify the AIRDROP requirements, ensuring they were grounded in both academic foundations and practical industry standards. The validation process involved a questionnaire survey administered to 26 participants from various professional backgrounds. The requirements were prioritized using the MoSCoW methodology, and significant differences among participant groups were identified through the Kruskal–Wallis H and Mann–Whitney U tests. Furthermore, two critical requirements emerged from open-ended responses. As a result, 276 out of the initially defined 335 requirements in total advanced to the design phase. It is worth noting that the dynamic nature of requirements in HL necessitates ongoing assessment and adaptation to keep AIRDROP at the forefront and aligned with evolving needs.

The causal effect of mental health on labor market outcomes: The case of stress-related mental disorders following a human-made disaster

As disasters increase due to climate change, population density, epidemics, and technology, information is needed about postdisaster consequences for people's mental health and how stress-related mental disorders affect multiple spheres of life, including labor-market attachment. We tested the causal hypothesis that individuals who developed stress-related mental disorders as a consequence of their disaster exposure experienced subsequent weak labor-market attachment and poor work-related outcomes. We leveraged a natural experiment in an instrumental variables model, studying a 2004 fireworks factory explosion disaster that precipitated the onset of stress-related disorders (posttraumatic stress disorder, anxiety, and depression) among individuals in the local community (N = 86,726). We measured labor-market outcomes using longitudinal population-level administrative data: sick leave, unemployment benefits, early retirement pension, and income from wages from 2007 to 2010. We found that individuals who developed a stress-related disorder after the disaster were likely to go on sickness benefit, both in the short- and long-term, were likely to use unemployment benefits and to lose wage income in the long term. Stress-related disorders did not increase the likelihood of early retirement. The natural experiment design minimized the possibility that omitted confounders biased these effects of mental health on work outcomes. Addressing the mental health and employment needs of survivors after a traumatic experience may improve their labor-market outcomes and their nations' economic outputs.

Crisis2Sum: An Exploratory Study on Disaster Summarization from Multiple Streams

Automatic summarization of natural and human-made disaster events is an important area to increase situational awareness for human response organizations and disaster management. However, the incorporation of multiple data sources poses a challenge to current summarization systems, as the typically large document collections exceed the input limits of neural models. Additionally, Large Language Models (LLM) often omit key information present at different positions in long context inputs. Furthermore, disaster reporting requires fine-grained information content and therefore relaxes the restriction to high compression rates, resulting into rather long summaries. In this work, we study different extractive and LLM-based abstractive baselines and highlight shortcomings in present approaches. Our experimental results on the CrisisFACTS datasets show that LLM-based approaches tend to fail in generating long informative summaries. Taking these limitations into account, we propose a disaster summarization framework and introduce query-focused extensions, which demonstrate advantages and superior performance over the baseline methods.

Knowledge-ing as a response-able practice in the Anthropocene: Re-turning (to) the research events like an earthworm

This paper began with the assumption that the habitual practices of knowledge-creation, which have shaped the day-to-day contexts of teachers and researchers, are not greatly different from the practices that have led to human-made catastrophes in the Anthropocene. I pondered over my experiences as a researcher in an attempt to gain insights for thinking about and engaging in knowledge-creation differently to become more response-able in the Anthropocene. Inspired by post-qualitative research practice, I re-turned, like an earthworm, (to) two research events. A theoretical framework informed by critical posthumanism and feminist new materialism guided the process. Through these re-turns, I came to understand that creating knowledge is a complex and indeterminate process that always accompanies the ‘more-than’. Attending to the notion of knowledge-ing, I discussed the ways in which knowledge emerged as a flow that was neither fully graspable nor static through more-than-human intra-actions. What I propose in this paper is not a methodological technique, but rather, a mode of practice that might disrupt our sense of Cartesian self. I offered some suggestions for teachers and researchers to reimagine the practices of knowledge-creation as a way of reinventing their subjectivity and responding to the damaged earth more responsibly.

A MOBILE-BASED LOCALIZATION SYSTEM FOR INFRASTRUCTURE-INDEPENDENT EMERGENCY COMMUNICATION

After natural or human-made disasters, determining the locations of individuals needing urgent assistance is critical and time-sensitive. This paper introduces a novel ad-hoc infrastructure-less communication system for emergency scenarios, relying solely on basic mobile device capabilities. The proposed approach estimates mobile device coordination using multilateration, incorporating path loss theory to transform receiving signal strength into distance. A least square optimization algorithm is also applied to enhance localization accuracy. The system facilitates coordination and communication among citizens and first responders by strategically positioning a few emergency mobile devices as temporary base stations. Mobile devices search for neighboring base stations and transform into temporary base stations upon finding at least four. Those temporary base stations assist farther mobile devices in localization, creating a cascading effect until no more mobile devices are discovered. Simulation demonstrates robustness with a 97% discovery rate, maintaining accuracy even in environmental noise. While promising, real-world validation is essential to assess performance under diverse conditions and practical feasibility.

A MOBILE-BASED LOCALIZATION SYSTEM FOR INFRASTRUCTURE-INDEPENDENT EMERGENCY COMMUNICATION

After natural or human-made disasters, determining the locations of individuals needing urgent assistance is critical and time-sensitive. This paper introduces a novel ad-hoc infrastructure-less communication system for emergency scenarios, relying solely on basic mobile device capabilities. The proposed approach estimates mobile device coordination using multilateration, incorporating path loss theory to transform receiving signal strength into distance. A least square optimization algorithm is also applied to enhance localization accuracy. The system facilitates coordination and communication among citizens and first responders by strategically positioning a few emergency mobile devices as temporary base stations. Mobile devices search for neighboring base stations and transform into temporary base stations upon finding at least four. Those temporary base stations assist farther mobile devices in localization, creating a cascading effect until no more mobile devices are discovered. Simulation demonstrates robustness with a 97% discovery rate, maintaining accuracy even in environmental noise. While promising, real-world validation is essential to assess performance under diverse conditions and practical feasibility.

Fire and Artificial Intelligence (AI): How AI Anticipates Human Behaviour in Fire Situations- Case Study of the Colectiv Fire

Abstract The catastrophic fire at Bucharest’s Colectiv Club marks a profoundly tragic event in Romania’s history, being one of the most significant human-made disasters the country has faced in recent decades. This study seeks to meticulously reconstruct the events of that fateful night through the use of advanced simulation software applications. By doing so, it aims to provide a detailed analysis of the factors leading to the tragedy, which claimed the lives of 64 individuals and caused injuries to 185 others. The objective is to understand better the dynamics and consequences of the fire, potentially leading to improvements in safety protocols and emergency response strategies to prevent such disasters in the future.

A Decision Support Model for Barriers and Optimal Strategy Design in Sustainable Humanitarian Supply Chain Management

Sustainable humanitarian supply chain (SHSC) management enables effective and efficient responses to natural and human-made disasters. Existing literature falls short of offering decision support (DS) models to address the barriers and strategies to designing SHSC. To this end, this study develops a DS model that identifies and prioritizes the barriers to SHSC and determines optimal strategies for mitigating those barriers. This study adopted both qualitative and quantitative approaches. As part of the qualitative approach, a field study was applied using in-depth interviews to determine the barriers and corresponding strategies, while under the quantitative approach, a quality function deployment (QFD) integrated optimization technique was used to prioritize barriers and determine optimal strategies to mitigate the SHSC barriers. The study found that a lack of contingency planning, the prevalence of corruption and political interference, and a lack of social and environmental awareness are the most important barriers, while logistics outsourcing, supply chain (SC) performance management, and SC flexibility are the most essential strategies. We also found that our DS model is highly flexible and can be adapted under different scenarios, which makes the model applicable to different contexts. This study has a significant contribution to literature and practice. We developed a novel decision model that captured cost savings and leveraged both cost and time savings from interrelated strategies to determine the best optimal strategy while applying QFD-integrated optimization modeling. The paper’s findings will assist humanitarian SC managers in designing an effective, efficient, and sustainable humanitarian SC.

Budgeting for the human-made disaster of war: US aid to Ukraine

IMPACT This article examines the USA’s efforts to support Ukraine in its war with Russia. The USA’s ex ante mitigation efforts were insufficient to prevent the invasion but likely enabled Ukraine to survive the initial attack. Preparation efforts produced large amounts of weapons stocks that could be sent to Ukraine once the war began. Ex post response efforts provided Ukraine with the means to continue defending itself, although the sustainability of such efforts is questionable. The authors’ findings indicate that more effective deterrence measures, such as a defence pact, may have discouraged the invasion, while building weapons stocks during times of peace are essential given that dollars cannot be converted quickly into the means of war.

The Effect of Disasters on Altruistic Behavior and its Mechanisms

Disasters, characterized by sudden and catastrophic events causing extensive damage to communities, come in various forms, including natural and human-made catastrophes. Disasters can change people's behavior. The present study explores the relationship between disasters and altruistic behavior and its mechanism. It delves into how disasters evoke altruistic responses in individuals, examining mechanisms including heightened empathy, the influence of the public atmosphere, group selection tendencies, and the impact of positive prior experiences. The study draws upon research studies that illuminate the connection between disasters and increased altruism, shedding light on the psychological and social factors that drive people to selflessly assist others during times of crisis. Understanding the relationship between disasters and altruistic behavior is critical to enhancing disaster response and fostering a sense of solidarity within communities. The results of this study promote people's understanding of how disasters affect people's altruistic behavior, and deepen people's understanding of people's altruistic behavior in disaster situations.

A novel framework for identifying causes of forest fire events using environmental and temporal characteristics of the ignition point in fire footprint

BackgroundForest fire is a very common natural or human-made disaster, which not only burns precious forest resources, but also further alters the forest ecosystem structure and functions as well as global climate. Accordingly, effective information extraction, data management, and modeling of historical fire events are imperative for forecasting and mitigating the onset and progression of forest fires. Traditional remote sensing-based forest fire detection and risk prediction operate at the pixel scale, overlooking the integrity of fire behaviour. Moreover, fire cause records typically stem from ground reports, not fully leveraging the advantages of high temporal resolution thermal infrared remote sensing products. MethodsWe proposed a framework to identify the causes of forest fire events, experimenting with fire incidents from 2001 to 2020 in the Daxing'anling region of Northeast China. Initially, the Jenk-DBSCAN model was employed to acquire fire footprints representative of forest fire events from MODIS MCD64A1 product, and footprint-based fire event attribute information such as ignition locations and timings. Fire footprints matching ground surveys were subsequently filtered, and corresponding environmental variable datasets (including meteorological, topographical, fuel, and human activity factors) were derived in consideration of the spatio-temporal differences of footprint origin and center points. Finally, the optimal variable combinations of the two datasets were fed to three binary classification models including Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM) respectively to identify natural fires or human-induced fires, followed by assessing the accuracy of the fire cause identification models. ResultsResults revealed that there was a high spatio-temporal consistency of those matched fire footprints between the model-extracted and the ground-recorded fire events, evidenced by an overall R2 of 0.87 derived from their area validation. The ignition dates extracted from fire footprints often preceded those reported by local agencies. Among all the selected variable combinations for fire cause identification, the meteorological variables dominated, with daily mean dew point (DEWP) and daily mean visibility (VISIB) being preferentially selected by most models. Across the six models, the model training AUC values were almost greater than 0.8, with the LR model demonstrating superior validation accuracy over RF and SVM. Notably, the accuracy of the LR model using the origin point based dataset surpassed that of the center point-based dataset. The best model achieved an overall accuracy of 90.48%, with the user’s accuracies for human-made fire and natural fire being at 92.86% and 85.71%, respectively. ConclusionsThe proposed framework offers a reliable method for enriching attribute information in forest fire management databases. The resulting fire footprints and origin points can assist in better characterizing the progression of forest fire events. Such endeavours help devise targeted forest fire prevention regulations, fostering sustainable forest management.

The spatial effects of the household's food insecurity levels in Ethiopia: by ordinal geo-additive model.

Food insecurity and vulnerability in Ethiopia are historical problems due to natural- and human-made disasters, which affect a wide range of areas at a higher magnitude with adverse effects on the overall health of households. In Ethiopia, the problem is wider with higher magnitude. Moreover, this geographical distribution of this challenge remains unexplored regarding the effects of cultures and shocks, despite previous case studies suggesting the effects of shocks and other factors. Hence, this study aims to assess the geographic distribution of corrected-food insecurity levels (FCSL) across zones and explore the comprehensive effects of diverse factors on each level of a household's food insecurity. This study analyzes three-term household-based panel data for years 2012, 2014, and 2016 with a total sample size of 11505 covering the all regional states of the country. An extended additive model, with empirical Bayes estimation by modeling both structured spatial effects using Markov random field or tensor product and unstructured effects using Gaussian, was adopted to assess the spatial distribution of FCSL across zones and to further explore the comprehensive effect of geographic, environmental, and socioeconomic factors on the locally adjusted measure. Despite a chronological decline, a substantial portion of Ethiopian households remains food insecure (25%) and vulnerable (27.08%). The Markov random field (MRF) model is the best fit based on GVC, revealing that 90.04% of the total variation is explained by the spatial effects. Most of the northern and south-western areas and south-east and north-west areas are hot spot zones of food insecurity and vulnerability in the country. Moreover, factors such as education, urbanization, having a job, fertilizer usage in cropping, sanitation, and farming livestock and crops have a significant influence on reducing a household's probability of being at higher food insecurity levels (insecurity and vulnerability), whereas shocks occurrence and small land size ownership have worsened it. Chronically food insecure zones showed a strong cluster in the northern and south-western areas of the country, even though higher levels of household food insecurity in Ethiopia have shown a declining trend over the years. Therefore, in these areas, interventions addressing spatial structure factors, particularly urbanization, education, early marriage control, and job creation, along with controlling conflict and drought effect by food aid and selected coping strategies, and performing integrated farming by conserving land and the environment of zones can help to reduce a household's probability of being at higher food insecurity levels.

Prevalence of cardiovascular diseases following man-made disasters; a systematic review

Objective: Disasters increase the incidence of infectious and contagious diseases, non-communicable diseases, and trauma. This systematic review aims to investigate the impact of man-made disasters on cardiovascular diseases (CVDs).
 Methods: This is a systematic review conducted following the PRISMA protocol. The population, intervention, control, outcome (PICO) framework utilized for this research is as follows: P: people with CVDs; I: various man-made disasters; C: no intervention is being compared; O: prevalence, treatment, and management of the disease. In the present study, English-language articles published until November 9, 2022 that investigated CVDs in human-made disasters were included. We conducted an extensive search in Medline, Web of Science, Embase, and SCOPUS.
 Results: The primary search of the databases resulted in 1878 articles, from which 1219 non-duplicate records. Finally, 18 articles were included; 13 studies were in the area of nuclear and atomic accidents, four studies were related to the sulfur mustard gas, and one was related to methyl chloride.
 Conclusion: CVDs increased in prevalence after man-made disasters, particularly among high-risk individuals. The likelihood of developing CVDs is higher with increasing dose, intensity, and duration of exposure.

CBRN Hazard Management in Malaysian Healthcare: A Review of the Literature and Implications for Practice

The occurrence and intensity of both natural and human-made disasters are bound to increase, posing significant risks to humanity. In Malaysia’s healthcare setting, a variety of procedures and practices for managing safety, health, and emergency management are implemented to ensure the comfort and protection of hospital personnel, patients, and visitors. The presence of chemical, biological, radiological, and nuclear (CBRN) hazards pose a grave risk to the health and well-being of healthcare personnel in Malaysia. The aim of this review article is to draw attention to practical implications and provide a thorough summary of the literature on CBRN hazard management in Malaysian healthcare.

Separatist and Terrorist Movements in Papua: The Challenges of Social Disaster Management and the Important Role of Human-Made Disaster Intelligence

The Papua secessionist movement hinders Indonesia's stability efforts. The government has implemented measures, deploying intelligence for managing social crises as defined by Law 24 of 2007 on Disaster Management. The present study examines the separatist movement in Papua, its resultant societal upheaval, and the crucial role of intelligence in mitigating this societal crisis. The study explores applying Human-Made Disaster Intelligence, using AI and data tech, to mitigate risks in the Papua case. This study employs a literature review with 26 sources to explore challenges posed by separatist and terrorist movements in Papua. Data is gathered from official sources, excluding personal websites and social media. The study was conducted from January to March 2023. Data analysis utilizes descriptive narratives to qualitatively explore separatist and terrorist movements, social disasters, intelligence, and the Papua region. The research findings demonstrate that the separatist movement in Papua has resulted in a significant societal calamity, causing conflicts, casualties, and economic challenges. Man-made disaster intelligence is proposed to manage social disasters by collecting and analyzing data related to separatist activities. Intelligence plays a crucial role in detecting and mitigating risks associated with separatism, offering preventive and remedial measures. Challenges include limited resources and the need for collaboration among intelligence agencies. Strategic measures to enhance intelligence involve increased resources, collaboration, transparency, and the integration of Artificial Intelligence (AI) for data analysis. The complexity of using AI in countering separatist movements requires careful consideration of data sources, collection methods, and reliability measures.

Features of upper ocean and surface waves during the passage of super typhoon Hinnamnor (2022)

Scientific understanding of super typhoons (STYs) is essential for environmental and human-made disaster prevention. The interactive processes among the atmosphere, ocean, and surface waves have an intimate relationship within the STY system. This study chose STY Hinnamnor (2022) as an example and used multi-source data to investigate how it affected the upper ocean. First, Argo floats data at two positions were collected to investigate the variation of sea surface temperature (SST), sea surface salinity (SSS), isothermal layer depth (ILD), mixed layer depth (MLD), barrier layer thickness (BLT), and eddy viscosity (EV) during pre- and post-STY. The STY passed through two Argo floats; hence, the SST, ILD, and BLT significantly decreased post-STY, whereas the MLD and EV increased. The SSS decreased by 0.26 psu where the STY passed southwestward, whereas it increased by 0.11 psu where the STY began to move northward. Subsequently, the remote sensing data and re-analysis data were used to study the evolution of the SST, precipitation, runoff, and profiles of the upper ocean pre- and post-STY. The results reveal that intensive vertical mixing and upwelling occurred in the region where the direction of the STY movement switched. It also revealed that the runoff and heavy precipitation increased the water salinity in this area. In addition, the reanalysis data indicated that the significant wave height (SWH) and the mean wave period (MWP) near the cyclone center became longer than in other areas. The temporal evolution of the spectral peak period (SPP) demonstrated the generation of a swell zone on the right side of the typhoon track when the STY moved northward.