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Background Methods Results Conclusion The predicted rise in weather‐related disasters indicates that many Australian children and their families will be affected by these events in the future. Play therapy, an emerging profession in Australia, may provide valuable support to children exposed to these events.A scoping review was designed to map the existing literature and the role of the play therapist in supporting children (aged 3–12 years) and families following natural disasters, and to formulate a model to guide play therapists in the future.A systematic search of the literature was performed and a total of 25 articles were identified as relevant to the role of the play therapist in response to natural disasters.Play therapists must be mindful of the different phases of natural disaster response and how their role may vary across these phases. In the early stages post‐disaster, a play therapist may be involved in psychoeducation, facilitating therapeutic play and community involvement. More formal clinical play therapy interventions that focus on the individual child or family are better suited to the latter stages of disaster response. There is a need for further research into the impact of natural disasters on children and families and interventions that aid mental health and well‐being, especially for children who may be more vulnerable and potentially overlooked in the wake of such disasters. Further research is also needed into the effectiveness of play therapy as a post‐disaster intervention for children. [ABSTRACT FROM AUTHOR]

The occurrence of natural disasters, accelerated by climate change, has become a continuous menace to the environment and consequently impacts the socioeconomic well-being of people. Flood events are natural disasters resulting from excessive rainfall duration, intensity, and snow melt. Flood disaster management systems that are machine learning-based have been increasingly suggested and applied to forestall the impacts of floods on the environment in terms of monitoring and warning. This study aims to critically review various studies conducted on flood management systems to identify applicable data sources and machine learning models. The study applied Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to source data from an academic database using some selected keywords, which were identified for the review process after filtering a total number of forty-two pertinent research papers was used. The review identified different combinations of flood data, flood management techniques, flood models, application of machine learning in flood predictions, optimization techniques, data processing techniques, and evaluation techniques. The study concluded that a standard approach should be applied in building robust and efficient flood disaster management systems. Lastly, informed future research directions on using machine learning for flood prediction and susceptibility mapping are provided. [ABSTRACT FROM AUTHOR]

Cold waves, as a common natural disaster, have a significant impact on economic development and living environment in coastal areas, especially in estuary regions. This paper utilizes the Delft3D software based on a rectangular grid, driven by the eight major tidal harmonic constituents of M2, S2, N2, K2, K1, O1, P1, and Q1, to construct a hydrodynamics and sediment numerical model. The study focuses on the morphodynamic changes in the Yellow River Delta (YRD) during a severe cold wave and strong wind event. By simulating the intense cold wave from November 28 to 30, 2022, the effects on the sedimentation in the YRD were analyzed. Results show that the cold wave process increases the water levels in the nearshore areas, with a general rise of more than 0.2 m in the YRD waters, particularly severe at the old Yellow River (YR) estuary and the northwest part of Laizhou Bay, reaching 0.25-0.35 m. This increase leads to intensified erosion and sedimentation in different areas near the YR estuary, especially near the old YR estuary and in the northwest part of Laizhou Bay. After a cold wave process, the erosion and sedimentation increase significantly by 0.05-0.1m. Furthermore, by comparing the flow speed differences and tidal-induced Eulerian residual currents with and without cold waves, it was found that around the YRD, from the current river estuary to the old YR estuary, the maximum flow speed increased by more than 0.35 m/s during the cold wave, and the maximum Eulerian residual currents also increased by 0.13 m/s. The direction of the residual currents changed from northwest-southeast to southnorth, further confirming the significant impact of cold waves on the morphodynamic evolution of the YRD. This study provides new perspectives and methods for understanding and predicting morphodynamic changes in estuarine regions during cold waves, which is significant for disaster prevention, mitigation, and management of estuarine areas. [ABSTRACT FROM AUTHOR]

Natural disasters are becoming more frequent and more severe as a result of global warming. It is critical to take precautions before disasters, to gather and analyze information simultaneously while they are happening, and to make accurate assessments after them given that the deaths and injuries brought on by such disasters both leave lasting traumas in the life of society and damage the economy. Internet of Things (IoT) technology, is a young field that can assist intelligent safety-critical systems with data collection, processing in cloud edge data centers, and application of prediction methodologies for discovering key points and unexpected patterns using 5G technology. With the use of a cloud-based prediction algorithm for disaster management in the IoT environment, this study seeks to quickly process the data that is gathered during disasters and to speed up the analysis that will be done both during and after the disasters. An Optimized Ensemble Bagged Tree (OEBT) algorithm with ANOVA-based feature selection is developed for this aim. The experimental results show that accuracy, F1-Score, precision, and recall of the proposed OEBT algorithm utilizing the US Natural Disasters Dataset are 97.9%, 78.3%, 98.7%, and 78.9%, respectively. Comparisons with decision tree, logistic regression, and the traditional ensemble techniques are made. The suggested algorithm outperforms them all in terms of success rates. [ABSTRACT FROM AUTHOR]

Background: On 6 February 2023, an Mw 7.8 earthquake struck southern and central Türkiye and north-western Syria, affecting the lives of 4.6 and 2.5 million children, respectively. In such crises, infants who are dependent on commercial milk formula (CMF) face increased vulnerability to diseases and malnutrition as safe preparation of CMF becomes difficult and sometimes impossible. The Operational Guidance on Infant and Young Child Feeding in Emergencies (OG-IFE) provides guidance on protecting and supporting recommended infant and young child feeding and minimizing the risks that come with CMF feeding. In addition, the International Code of Marketing of Breastmilk Substitutes (the Code) ensures adequate nutrition for infants by protecting and promoting breastfeeding and ensuring the proper usage of CMF. This study aims to document violations of the Code and the OG-IFE during the earthquake relief efforts to help strengthen infant and young child feeding emergency responses and inform future disaster relief policies. Methods: Data was collected from 6 February to 10 March 2023 through Internet sources. Social media, news websites, and the Emergency Nutrition Network forum were used for data collection. Turkish content was translated into English for analysis, with a focus on donation-related information and Code violations related to baby food and infant feeding. Results: A total of 40 reports on CMF, complementary food, and feeding equipment donations were collected. Three main types of violations of the OG-IFE and the Code were identified, with the majority of them being incidences of individuals, humanitarian organizations, and government agencies seeking or accepting donations. Infant formula companies continued to violate the Code by donating large quantities of CMF and feeding equipment to the Turkish Red Crescent, government agencies, and disaster relief infant and young child feeding (IYCF) coordination authorities. Conclusions: These incidents reflected a systematic violation of the Code and non-compliance with the OG-IFE. Globally accepted IYCF standards and recommendations were not consistently followed due to fragmented early responses. There is a critical need to step up efforts to ensure appropriate and safe IYCF practice protecting and supporting breastfed and non-breastfed infants in emergencies. [ABSTRACT FROM AUTHOR]

Comparing with cities, rural communities especially those declining rural communities have become vulnerable to natural disasters owing to their backward socioeconomic conditions. Taking Xun County of China's Henan Province as the study area, the paper aims to evaluate rural community resilience to flood by unveiling the connection between individuals' cognition, follow-up actions and the community resilience. Research results show that: (1) The logic chain exists as individual's cognition to disaster leads to their constructive actions to cope with disaster, which contribute to community resilience. (2) At the cognition dimension, individual's knowledge reserve of disaster prevention and their recognition to local authority are playing an important role in their decision making and follow-up behaviors when disaster occurs. (3) At the action dimension, individual's familiarity with the disaster preparedness, efficient information transmission when disaster occurs and villagers' following order and their unity of action all contribute to community resilience to disaster. The paper proposes ways to improve rural community resilience to disasters based on the research findings. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate individuals' disaster literacy levels, their thoughts on disaster management services, and related factors. Method: The descriptive research was conducted with a total of 480 individuals between the ages of 18 and 60 living in a province in the first‐degree earthquake zone in Turkey. The data were collected with the Disaster Literacy Scale and the Disaster Management Services Evaluation Form. Results: In this study, it was found that more than half of the participants had inadequate/moderate disaster literacy. The total disaster literacy score and all subscale scores were found to be higher in individuals who had an earthquake kit at home, had an emergency plan, and had received disaster‐related training (p <.05). The majority of the participants found the services provided for disaster management inadequate or very inadequate. Conclusions: In this study, it has been found that a significant portion of the society lacks the desired level of disaster literacy, and the services provided for disasters are deemed insufficient therefore, there is a need for multi‐disciplinary national prevention programs to enhance disaster literacy and preparedness in the community, as well as urgently supporting policies to improve disaster‐related services. Additionally, due to their comprehensive knowledge of the general structure of society, public health nurses need to play an active role in disaster preparedness and increasing disaster literacy levels. [ABSTRACT FROM AUTHOR]

Disaster operations management (DOM) seeks to mitigate the harmful impact of natural disasters on individuals, society, infrastructure, economic activities, and the environment. Due to the increasing number of people affected worldwide, and the increase in weather-related disasters, DOM has become increasingly important. In this survey, we focus on the post-disaster stage of DOM that involves response operations. We review studies that propose optimization models to supporting the following four relief logistics operations: (i) relief items distribution, (ii) location of relief facilities and temporary shelters, (iii) integrated relief items distribution and shelter location, and (iv) transportation of affected population. Optimization models from 127 articles published between 2013 and 2022, focusing on relief logistics operations during natural disasters, are categorized by disaster type and thoroughly analyzed. Each model provides a case study illustrating its application in addressing key relief logistics operations. We also analyse the extent to which these studies address the critical assumptions and methodological gaps identified by Galindo and Batta (Eur J Oper Res 230:201–211, 2013), Caunhye et al. (Socio-econ Plan Sci 46:4–13, 2012), and Kovacs and Moshtari (Eur J Oper Res 276:395–408, 2019) and the neglected research directions noted by the authors of other relevant review papers. Based on our findings, we provide avenues for potential future research. Our analysis shows a slow increase in the total number of papers published until 2018–2019 and a sharp decrease afterwards, the latter most likely as a consequence of the COVID-19 pandemic. More than half of the papers in our selection concern earthquakes while less than ten papers deal with wildfires, cyclones, or tsunamis. The majority of the stochastic optimization models consider uncertainty in the demand and supply of relief items, while some other crucial sources of uncertainty such as funding availability and donations of relief items (e.g., blood products) remain understudied. Furthermore, most of the papers in our selection fail to incorporate key characteristics of disaster relief operations such as its dynamic nature and information updates during the response phase. Finally, a large number of studies use exact commercial software to solve their models, which may not be computationally efficient or practical for large-scale problems, specifically under uncertainty. [ABSTRACT FROM AUTHOR]

Background: In May 2023, Romagna, Italy, faced a devastating flood resulting in 16 fatalities, forced displacement of 26,000 citizens, and significant economic losses. Due to potential water contamination, implementing public health strategies became imperative for the Local Health Authority to mitigate the health consequences, analyze the flood's impact on the local population's health, and detect early anomalies requiring timely public health interventions. Methods: Between June and July 2023, general practitioners who were part of the RespiVirNet surveillance network completed weekly structured forms. These forms collected data on individuals exposed or not to floodwaters and clinical syndromes. Rates per 1000 resident population aged > 14 were stratified by district, week of observation, and symptomatology. Missing data were addressed by imputation using second-order autoregressive modeling. Results: An incidence of 3.52 syndromes potentially related to flood water exposure per 1000 individuals (95% CI 2.82–4.35) was estimated. Ravenna, the city most affected by the flood, recorded the highest rate (6.05 per 1000, 95% CI 4.59–7.82). Incidence decreased in the weeks post-event. Anxiety, or trauma and stress symptoms, exhibited higher rates among the exposed, diminishing over weeks. The incidence for the non-exposed (12.76 per 1000, 95% CI 10.55–15.29) showed no significant territorial differences compared to the exposed ones. Conclusions: Syndromic surveillance provided timely information on the flood's health impact, revealing a higher incidence of individual syndromes among the non-exposed. This study contributes to guiding the implementation of future public health preparedness and response strategies for populations facing similar natural disasters. [ABSTRACT FROM AUTHOR]

Accurate and timely information on building age is essential for mitigating the impacts of natural disasters such as earthquakes and floods. Traditional methods for collecting these data are often inefficient and costly. This study leverages remote sensing and machine learning to classify building age and integrate this information into a comprehensive flood hazard map for Al Ain City. By combining building age with elevation, topography, land use, population density, and other factors, we generated a flood hazard map that effectively identifies high-risk areas. Our results show that a significant portion of the city is has low potential for flooding (61%), while others face moderate (32%), high, or very high flood hazards. This study provides crucial information for informed decision-making regarding future urban planning, disaster management, and development strategies in Al Ain City. By identifying vulnerable buildings in advance, it supports efforts to reduce disaster risks, protect lives, and optimize resource allocation. [ABSTRACT FROM AUTHOR]

This study investigates the intricate relationship between natural disasters and regional entrepreneurship in Türkiye, a developing nation highly vulnerable to earthquakes, floods, and other hazards. The study extends Hierarchical Multiple Regression (HMR) analysis (1990–2020, 81 NUTS-III regions), beyond existing literature focused on physical damage. Our findings reveal a counterintuitive effect: while the number of disasters and total property damage correlate positively with regional entrepreneurship, human life loss has a negative impact. This suggests a complex interplay between destruction and entrepreneurial spirit. Further analyses using Discriminant Function Analysis (DFA) and MANOVA-ANOVA for robustness check explores regional characteristics that contribute to entrepreneurial resilience against natural disasters. By comparing regions categorized by entrepreneurial performance and disaster exposure, the study identifies key differentiators. Regions with supportive business environments demonstrate greater resilience, highlighting the crucial role of fostering a strong entrepreneurial ecosystem in mitigating disaster effects. This research fills a critical gap by examining the understudied relationship between natural disasters and regional entrepreneurship, going beyond individual firm-level studies. By analysing interregional disparities and resilience factors, this paper provides valuable insights for both regional development and entrepreneurship & resilience literature. It emphasizes the importance of human capital alongside disaster preparedness and institutional quality in building regional resilience. [ABSTRACT FROM AUTHOR]

Floods are significant natural disasters that have wide-ranging social, economic, and environmental consequences on a global scale. They lead to land degradation and increased erosion, which in turn negatively impacts water quality. In the present study, the Söğütlü stream watershed in the Eastern Black Sea Region of Turkey was chosen as the study area to create a flood risk map using Analytical Hierarchy Process and Weighted Overlay tools in the ArcGIS. The raster maps, including soil type, rainfall, landuse, slope, aspect, elevation, and distance to the stream, were utilized as the foundation for the analysis. The flood risk map generated from this analysis reveals five risk zones that is very high, high, moderate, low, and very low-risk zones. Statistical analysis was performed to evaluate the obtained data. The study results indicate that low and moderate areas encompass 95.98% of the watershed, while high-risk and very high-risk areas account for 4.02% of the watershed in the flood risk map of the Söğütlü watershed. It was observed that areas in close proximity to rivers, low slope end elevation were more susceptible to flooding. This study is great importance as it allows for the development of preventive, preparatory, and post-disaster plans before flood events occur by providing a flood risk map. Moreover, the creation of a flood risk map at the watershed scale helps planners in undertaking soil and water conservation efforts during watershed planning. [ABSTRACT FROM AUTHOR]

Natural disasters occur frequently worldwide, causing serious harm to people, resources, and the environment. The disaster mitigation capacity is very important in reducing disaster-caused losses and in informing natural disaster prevention and mitigation plans. However, the disaster mitigation capacity frameworks in recent studies are inconsistent and lack the careful consideration of natural disaster occurrence process, and it remains unclear to what extent the model parameters may affect the robustness of assessment results. To solve this problem, with typhoons as an example, an assessment framework of typhoon disaster mitigation capacity (TDMC) based on the entire process of disaster prevention–resistance–rescue was developed in this study. The TDMC framework was applied in Hainan, China, as a case study, and the associated uncertainty was assessed by analyzing indicator selection and weighting and synthesis methods. The TDMC was very high in Haikou and Sanya but very low in Lingao, Ledong, and Dongfang. Iterative sensitivity analysis of the indicators revealed that the removal of different indicators had little effect on the percentage change in average TDMC of Hainan. The sensitive indicators were warning systems, emergency shelters, and insurance, suggesting that specific strategies for those indicators could improve regional TDMC. The assessment results with different indicator weighting and synthesis methods were generally robust, especially in counties with very low or high TDMC. However, the counties with medium TDMC showed higher sensitivity, which led to changes in TDMC indices. Assessments were more sensitive to changes in weighting method than to changes in synthesis method. This study demonstrated the importance of quantifying uncertainties in assessment model parameters to provide credible TDMC information and to further the effective design of disaster prevention and mitigation strategies. [ABSTRACT FROM AUTHOR]

Floods are one of the most common natural calamities and the disastrous action of flood becomes stringent when the floods are caused by dam failures. It is quite difficult to predict the failure of dam however the technique of dam break analysis provides an effective way to understand the flood wave generated due to assumed failure of dam. The present work focuses on dam break analysis of Ajwa dam constructed on river Surya, a tributary of river Vishwamitri. The work is divided into two parts. The first part consists of hydrological modeling of Vishwamitri basin using SWAT model and estimates the flood for 20-year return period and further calibrating and validating the model in SWATCUP 2019 using SUFI2 algorithm. The maximum flood calculated from SWAT model is taken as lateral inflow in dam break model setup. The breach parameters have been adopted as per the guidelines provided by Central Water Commission. Time of arrival of dam break flood at important locations downstream of Ajwa dam has been identified. The results reflect the potential of such a study to encompass the emergency action plans to safeguard the public and property in case of the possible flood event due to dam break. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of four historical tropical storms on the Colonial Bank's operations in the British Caribbean between 1922 and 1927. By employing a high-frequency data set of bank transactions, this study reveals how these severe shocks influenced the banking activities of clients. The findings reveal a multifaceted and significant impact of tropical storm strikes on the banks' operations, particularly a surge in borrowing via overdrafts of current accounts. Moreover, the study reveals the multifaceted nature of such storms' impact on the bank's functionality, with affected branches demonstrating an uptick in deposits and savings as a strategy to mitigate funding shocks. The results of the econometric analysis indicate that the impact of such storms on banks' functionality during the early 20th century was significant and multidimensional. It highlights the critical role that the Colonial Bank plays in facilitating recovery from these devastating events and contributes to the existing literature by studying multiple shocks at different geographical locations and time frames. [ABSTRACT FROM AUTHOR]

Objective Methods Results Conclusions We consider how the Peruvian government's responses to natural disaster events shaped political violence patterns from 1989 to 2020.We gather data on government disaster response and compare the effect of positive disaster responses, such as reconstruction and regulation of domestic/international aid, and negative disaster responses, such as neglect or placing restrictions on movement near the affected areas, on violent conflict. To address the endogeneity between armed conflict and disaster responses, we estimate a structural equation model where we allow armed conflicts and disaster responses to be fully endogenous.Using a structural equation model at the province‐year level, we show that negative disaster responses increase the risks for political violence, while positive disaster responses do not affect the risks for armed conflict. Armed conflict in turn makes negative policy responses to disasters more likely but has no effect on positive disaster responses.The results suggest that poor government response to natural disasters can foster grievances and aid rebel recruitment, increasing the risks for armed conflicts. [ABSTRACT FROM AUTHOR]

Background: Identifying factors associated with post-disaster youth substance use is a crucial element of developing evidence-based prevention and intervention efforts. Hurricane María struck Puerto Rico in September of 2017 and the wide-spread impact from this disaster, including exposure to trauma, displacement, and disrupted social supports had the potential to negatively impact levels of substance use among youth across the archipelago. However, post-disaster substance use remains under-investigated in this context. The current study sought to identify risk and protective factors associated with substance use among Puerto Rican youth in the aftermath of Hurricane Maria. Methods: Cross-sectional, secondary data analyses were conducted using school-based survey data collected at all schools in Puerto Rico between February 1 and June 29, 2018 (5–9 months after Hurricane María). Social supports, substance use, and trauma symptoms were assessed. An ordinal regression analysis was conducted to identify student factors associated with greater likelihood of post-disaster substance use. Results: A total of 36,485 participants (50.7% female, grades 7–12), were included in an ordinal regression analysis that compared the likelihood of respondents endorsing high, low, or no substance use after Hurricane María based on reported adult social support, counselor/teacher social support, peer social support, ptsd symptomatology, and gender. Findings showed that, when compared to students that endorsed low or no substance use, those who reported having adult social support demonstrated a 58% reduction in odds (OR = 0.42, 95% CI: 0.34-0.53) of reporting high substance use after Hurricane María, while students who reported having teacher/counselor social support demonstrated a 21% reduction in odds (OR = 0.79, 95% CI: 0.69-0.89) of reporting high substance use. Additionally, those that reported having peer social support demonstrated a 31% increase in odds (OR = 1.31, 95% CI: 1.10 to 1.58) of reporting higher substance use, compared to those that reported low or no substance use. Conclusions: While social support was generally protective, prevention efforts to build positive family and community connections may be indicated. Evidence-based school screenings of substance use and trauma may help direct intervention to those most at risk for co-occurring issues. [ABSTRACT FROM AUTHOR]

Data and reports indicate an increasing frequency and intensity of natural disasters worldwide. Buildings play a crucial role in disaster responses and damage assessments, aiding in planning rescue efforts and evaluating losses. Despite advances in applying deep learning to building extraction, challenges remain in handling complex natural disaster scenes and reducing reliance on labeled datasets. Recent advances in satellite video are opening a new avenue for efficient and accurate building extraction research. By thoroughly mining the characteristics of disaster video data, this work provides a new semantic segmentation model for accurate and efficient building extraction based on a limited number of training data, which consists of two parts: the prediction module and the automatic correction module. The prediction module, based on a base encoder–decoder structure, initially extracts buildings using a limited amount of training data that are obtained instantly. Then, the automatic correction module takes the output of the prediction module as input, constructs a criterion for identifying pixels with erroneous semantic information, and uses optical flow values to extract the accurate corresponding semantic information on the corrected frame. The experimental results demonstrate that the proposed method outperforms other methods in accuracy and computational complexity in complicated natural disaster scenes. [ABSTRACT FROM AUTHOR]

This document is an editorial from the journal Frontiers in Earth Science titled "Prevention, Mitigation, and Relief of Compound and Chained Natural Hazards." It discusses the increasing frequency of extreme natural disasters due to global climate warming and frequent earthquakes, which pose significant threats to human life and property. The editorial highlights the importance of preventing, mitigating, and relieving compound and chained natural hazards, and the role of technological advancements in addressing these hazards. The document provides an overview of nine published papers that focus on earthquakes, geological hazards, earthquake-triggered landslides, and landslide susceptibility. It concludes by emphasizing the need for continued research on comprehensive natural hazards and disaster chains, beyond earthquakes and geological disasters, such as meteorological events, floods, droughts, wildfires, and tsunamis. [Extracted from the article]

The frequency of natural disasters has increased recently, posing a huge threat to human society. Rapid, accurate, authentic, and comprehensive acquisition and transmission of disaster information are crucial in emergency response. In this paper, we propose a design scheme for an aerial remote sensing platform based on real-time satellite communication. This platform mainly includes a civilian heavy-duty unmanned aerial vehicle, ground observation system with the self-developed orthographic image stabilization device, wireless communication system with an airborne mobile communication device using Ku band, ground satellite information receiving station, and data processing and application analysis system. The image stabilization capability of the ground observation system and the communication capability of the wireless communication system were verified through ground and flight tests respectively. The results showed that the stability accuracy of the platform was better than the theoretical threshold, the system transmission rate was not less than 2 M bandwidth, the data packet loss rate was low, and the time delay was not more than 2 s. The images captured in the experiment were clear, with a resolution of less than 1cm and an overlap rate of more than 70%. These all results meet the emergency observation requirement, which indicates that the aerial remote sensing platform based on real-time satellite communication has great potential for application in natural disaster emergency response. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to investigate personal preparedness among patients on haemodialysis (HD) and to examine the relationship among sociodemographic characteristics, attitudes toward disaster preparedness and personal preparedness behaviours during natural disaster incidents. Design: A cross‐sectional survey was conducted. Methods: A convenience sampling method was used. A total of 446 participants from six areas of Sichuan province completed the online questionnaire study from February 27 to March 13, 2022. Sociodemographic characteristics, attitudes toward disaster preparedness and personal preparedness behaviours were measured. Descriptive statistics were used to analyse sociodemographic characteristics and attitudes toward disaster preparedness. The relationship among sociodemographic characteristics, attitudes toward disaster preparedness and personal preparedness behaviours were assessed using ordinal regression. Statistical significance was defined as p < 0.05. Results: A total of 446 participants completed the survey. Of these, 42.15% (N = 188) were poorly prepared, 26.23% (N = 117) were moderately prepared and 31.61% (N = 141) were highly prepared. Ordinal regression showed that knowing about disaster preparedness (Odds Ratio (OR) = 1.691, 95% Confidence Interval (CI) = 1.081–2.644, p = 0.021), participating in disaster evacuation exercises (OR = 2.519, 95% CI = 1.595–3.977, p < 0.001) and learning about disaster preparedness (OR = 2.421, 95% CI = 1.542–3.802, p < 0.001) were associated with high preparedness. Compared to patients with a university degree or higher, patients with a junior high school education or lower (OR = 3.491, 95% CI = 1.760–6.925, p < 0.001) and senior high school degree (OR = 2.052, 95% CI = 1.038–4.057, p = 0.039) were associated with high preparedness. Patients who felt very confident and could deal with all their needs (OR = 3.878, 95% CI = 2.904–7.181, p < 0.001) or patients who felt confident and could meet some of their needs (OR = 1.949, 95% CI = 1.124–3.379, p = 0.017) had higher preparedness than those who felt less confident and were not well prepared to take care of their needs. Patient or Public Contribution: After obtaining each participant's consent, they filled out the online questionnaire using their own or a relative's cell phone while undergoing HD. Implication for Practice: It is essential that patients should be educated not only on medical specialty topics, but also on general disaster preparedness. Medical institutions should improve and reinforce preparation training among targeted populations. The low level of preparedness is partly due to the lack of participation of patients in disaster preparedness programs. Dialysis center managers should be urged to implement such programs at their centers. [ABSTRACT FROM AUTHOR]

The Indo-Pacific Region, a hotbed for geographical and hydro-climate disasters such as cyclones, tsunamis, floods, and typhoons, presents both direct and indirect threats to human and national security. This research seeks to bolster both forms of security by enhancing the management of these natural disasters within the region. Employing a qualitative research method, this case study is both explanatory and analytical. Data, collected through primary and secondary resources, is presented in both quantitative and qualitative forms. The research is framed from the perspective of the human security approach. The Sri Lanka Navy and Coast Guard, as the agencies responsible, strive to mitigate the effects of these disasters and provide humanitarian assistance within their jurisdictions. Their participation in humanitarian assistance and disaster relief (HADR) exercises with regional and international actors underscores their commitment to human and national security. [ABSTRACT FROM AUTHOR]

Landslide disasters comprise the majority of geological incidents on slopes, posing severe threats to the safety of human lives and property while exerting a significant impact on the geological environment. The rapid identification of landslides is important for disaster prevention and control; however, currently, landslide identification relies mainly on the manual interpretation of remote sensing images. Manual interpretation and feature recognition methods are time-consuming, labor-intensive, and challenging when confronted with complex scenarios. Consequently, automatic landslide recognition has emerged as a pivotal avenue for future development. In this study, a dataset comprising 2000 landslide images was constructed using open-source remote sensing images and datasets. The YOLOv7 model was enhanced using data augmentation algorithms and attention mechanisms. Three optimization models were formulated to realize automatic landslide recognition. The findings demonstrate the commendable performance of the optimized model in automatic landslide recognition, achieving a peak accuracy of 95.92%. Subsequently, the optimized model was applied to regional landslide identification, co-seismic landslide identification, and landslide recognition at various scales, all of which showed robust recognition capabilities. Nevertheless, the model exhibits limitations in detecting small targets, indicating areas for refining the deep-learning algorithms. The results of this research offer valuable technical support for the swift identification, prevention, and mitigation of landslide disasters. [ABSTRACT FROM AUTHOR]

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Climate change risk is becoming a big threat to humanity across the globe, as it disrupts the socio-ecological systems, thereby making communities more vulnerable. Consequently, researchers dealing with disaster risk and climate change have conceptualized vulnerability and resilience as essential ideas for environmental management. These ideas have now been used in various disciplines to present the system's risk and ability to cope and recover. Nevertheless, there is still a huge debate about the use of these concepts in the literature. Hence, this study intends to contribute to the debate by clarifying the concept of vulnerability and resilience in the context of natural hazards. To this end, a PRISMA approach-guided systematic review was undertaken to identify the pertinent documents to corroborate the argument. This study argues that the two notions of resilience and vulnerability are conceptually intertwined, but one is not the polar opposite of the other. Although communities and the social groups that make up those communities can be highly vulnerable, that does not mean that they are also vulnerable in other ways. Vulnerability focuses on how well systems' units (people, organizations, and societies) can deal with the consequences of stressors and is comprised of three major components, namely exposure, sensitivity, and adaptability. While the exposure and sensitivity components are positively related with vulnerability, adaptability exhibits a negative correlation with vulnerability. This study also argues that resilience is an ability of a socio-ecological system to bounce back to the preceding form after facing any shock, risk, and uncertainties by utilizing adaptive, absorptive, and transformative capacities. Adaptive capacity is the common component of vulnerability and resilience concepts, as low adaptive capacity places a system or unit in vulnerability, while high adaptive capacity promotes resilience. This study identifies several indicators and pillars recommended for a comprehensive understanding of vulnerability and resilience from various sources and analyzed them from different angles. The findings of this paper will be an important guideline for policymakers, practitioners, service providers, and environmental scientists. [ABSTRACT FROM AUTHOR]

Climate change and extreme weather events have led to a surge in natural hazards in Pakistan that have escalated into humanitarian disasters. While remittances are often central to the livelihood of the most vulnerable, research has produced limited knowledge regarding the role of remittances in time of disaster. This paper investigates the reaction of Pakistani migrants to five major natural disasters via remittances from 1972 to 2023. Using an event‐study methodology, the paper compares the responses of remittances in different host countries namely Gulf Cooperation Council (GCC), Europe & the UK and North America. We provide evidence that remittances intensify in response to climate‐induced disasters, thus representing a reactive mechanism in time of hardship. The response is significant two (one) months after the events for GCC (Europe & the UK and North America) and tends to dissipate 5 months from the disaster occurrence (except for GCC). The intensity and the persistence of remittances' responsiveness (abnormal returns and volatility) depends on the nature of disasters, host countries' features and the economic conditions of migrants. Our findings highlight the need for further understanding the role of remittances as a coping mechanism in the face of environmental hazards to better inform policies geared toward disaster risk reduction. [ABSTRACT FROM AUTHOR]

This study examines patterns of interorganizational collaboration for hazard mitigation in metropolitan regions. Metropolitan regions whose populations reside in vulnerable places may experience extreme events. Facilitation of collective actions among organizations is critical for building resilient urban communities. Although the literature highlights the importance of interorganizational collaboration in disaster management, patterns of interorganizational collaboration for hazard mitigation in urban settings has been underexamined. Building on an institutional collective action framework, this study argues that hazard mitigation efforts tend to be localized. We tested this hypothesis using survey data collected in the Busan and Ulsan metropolitan regions, where natural disasters are problematic. An exponential random graph model confirmed the presence of a bonding strategy, which builds trust with municipalities and organizations within the region and creates interorganizational collaboration. We found that local public agencies tend to collaborate with organizations in the same jurisdictions or at higher levels of government. Practical Applications: In the context of emergency management, hazard mitigation plays a crucial role in building resilient communities. Public agencies implement hazard mitigation actions by collaborating with other agencies and groups. Local agencies may require financial or logistical support from regional or national governments to effectively implement hazard mitigation actions. Agencies can foster collaborative relationships and strengthen their commitment to hazard mitigation efforts through regular interactions and by forming collaborative groups. Furthermore, collaboration among agencies within a region allows for shared interests in hazard mitigation and the strengthening of commitments. These strategies will help public agencies to implement hazard mitigation actions that utilize resources from a broad range of organizations. [ABSTRACT FROM AUTHOR]

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Background Aim Methods Findings Conclusions Implications for nursing and health policy Turkey has faced a notable escalation in earthquake disasters in the last two decades. Despite initiating a health and disaster management system, nurses' pivotal roles and experiences in handling such crises have been disregarded.This qualitative study analyzed nurses' experiences before, during, and after deployment in response to the 2023 Turkey earthquakes to enhance disaster‐response efforts.This descriptive qualitative study was conducted between March and May 2023 using semistructured interviews with 15 nurses purposively  sampled among those who volunteered to work in the earthquake zone. The MIRACLE and COREQ guidelines were followed for reporting qualitative research.The analysis exposed five main themes for pre‐tasking: moral obligation, motivation, insufficient experience, balancing responsibilities, and preparation challenges. The peri‐task themes include responsibilities, skills, bravery and characteristics, workload management, teamwork, and outcomes. Post‐tasking has three themes: competence assessment, career goals and aspirations, and support. Training and coping with anxiety and stress are common themes for all phases.Disaster relief requires a comprehensive and coordinated response from healthcare organizations, government agencies, and support systems. Providing adequate training, ensuring safety protocols, offering mental health support, and fostering a fair and supportive work environment are crucial steps in mitigating the adverse effects on nurses and, by extension, the patient care process in earthquake‐affected areas.Nurse training in disaster preparedness should cover various response methods and involve multiple disciplines. Managers can help by arranging drills, simulations, online courses, and workshops and promoting partnerships for improved collaboration. Psychological support should be included to address emotional challenges. Regularly updating response policies based on past experiences is crucial for preparedness and efficiency. [ABSTRACT FROM AUTHOR]

Saudi Arabia is threatened by recurrent flash floods caused by extreme precipitation events. To mitigate the risks associated with these natural disasters, we implemented an advanced nationwide flash flood forecast system, boosting disaster preparedness and response. A noteworthy feature of this system is its national-scale operational approach, providing comprehensive coverage across the entire country. Using cutting-edge technology, the setup incorporates a state-of-the-art, three-component system that couples an atmospheric model with hydrological and hydrodynamic models to enable the prediction of precipitation patterns and their potential impacts on local communities. This paper showcases the system's effectiveness during an extreme precipitation event that struck Jeddah on 24 November 2022. The event, recorded as the heaviest rainfall in the region's history, led to widespread flash floods, highlighting the critical need for accurate and timely forecasting. The flash flood forecast system proved to be an effective tool, enabling authorities to issue warnings well before the flooding, allowing residents to take precautionary measures, and allowing emergency responders to mobilize resources effectively. [ABSTRACT FROM AUTHOR]

Introduction This study is a scoping review to identify literature pertinent to the question: "What are the criteria for deployment of the United States National Guard (USNG) to domestic sudden-onset natural disasters (SODs)?" As this question relies on factors across many disciplines—legal, medical, technical, cultural—and as there is no foundational body of academic literature or unified governmental or USNG policy addressing this question, a scoping review was designed to identify the body of literature on which further research and policy decisions surrounding this question may be based. Materials and Methods On January 23, 2023 a modified PRISMA-ScR search was performed using an online search engine of the following databases: Academic Search Premier, Google Scholar, JSTOR, PubMed, Web of Science, and WorldCat. The inclusion criteria included the involvement of the USNG response to U.S. domestic SOD. Non-SOD results were excluded. Results from all years and of any type of literature were considered and were limited to the English language. First, titles and abstracts were screened by 2 independent reviewers. Then, a full-text review was performed by 2 independent reviewers. Finally, data were extracted from included texts by 2 independent reviewers. A third reviewer resolved any discrepancies at each stage. This study did not require approval of an institutional review board. Results Out of the 886 results identified by the original search, after the complete review process, 34 sources were relevant to the research question. Fifteen criteria for the deployment of the USNG to SODs were identified. Overwhelmed local responders, utility failure, the need for the provision of security, and the need for logistical coordination were the most commonly identified criteria. Hurricanes were the most common SOD addressed in the included literature, and most results were event reports. Conclusions This modified PRISMA-ScR identified a foundation on which elected officials, USNG leadership, and the larger disaster response community may develop policies and disaster response plans to optimize available resources through the activation of the USNG when responding to SODs. [ABSTRACT FROM AUTHOR]

This study was conducted to determine relationship between disasters and sleep problems in adolescents. In this descriptive and cross-sectional study, 407 adolescents aged 10–18 years were included. The data were collected with Descriptive Characteristics Form, Disaster Fear Form, and Bergen Insomnia Scale. 86.5% of the adolescents had experienced at least one disaster. It was found that 67.3% of adolescents experienced sleep problems after disasters. A positive correlation was found between the mean scores of Fear Disaster Form and Bergen Insomnia Scale. In addition, mean Bergen Insomnia Scale scores of adolescents who experienced earthquakes, pandemic disease, traffic accidents, and floods were statistically higher than those who did not (p < 0.05). By screening for sleep problems in adolescents who have experienced disasters and planning and implementing appropriate interventions, adolescents who are already at risk for sleep problems can develop healthy sleep habits and prevent physiological, mental, and cognitive problems due to sleep problems. [ABSTRACT FROM AUTHOR]

More than one billion people worldwide are living in urban informal settlements where flood risks are high. Positive collective efficacy beliefs can facilitate community‐level adaptive action. This sub‐study of the Revitalizing Informal Settlements and their Environments (RISE) trial, aimed to identify social and contextual factors influencing residents' collective efficacy appraisals about their settlement's ability to implement community‐level flood prevention, protection and response measures. Forty‐two in‐depth interviews were conducted in 10 settlements in Suva, Fiji using a photovoice methodology. Thematic analysis was used to elicit key themes, which were then interpreted and contextualized collaboratively with the local field team. The most salient influencing factors were formal leadership, shared needs or benefits, collective identity (whether via shared religion, ethnicity or regional/kinship group), past performance experiences and expectations around collective action. While the data revealed some between‐settlement variation on these factors, there was also a large degree of within‐settlement variation concerning perceptions of these factors. Community‐based flood programming should not be undertaken without first assessing the degree to which participants believe that programme objectives reflect shared needs or will yield shared benefits and whether those objectives warrant collective action according to the community's social expectations for participation and contribution. [ABSTRACT FROM AUTHOR]

This note illustrates some of the new roles that armed forces are taking on in developed countries, highlighting the structure, capabilities, and missions developed by the Spanish Military Emergency Unit (UME). The note describes some of these new roles assumed by UME, such as its response to the COVID-19 pandemic, and shows, using official temporal and georeferenced data, the growing use of the military to support civilian authorities in response to natural disasters, man-made disasters, and other emergencies alike. In addition, we also analyze public opinion survey data to argue that this is helping to improve society's perception of the armed forces even in a country like Spain where, due to its recent history, a significant part of its population is reluctant to the military. In short, the military is taking on more emergency roles as needs arise and these new roles can help to improve its perception by citizens. [ABSTRACT FROM AUTHOR]

The mountain communities of Karakorum and the Himalayas in Pakistan are frequently experiencing climate change-induced natural disasters, which are inflicting irreparable losses to their generation's old value system and socio-economic life. Focusing on the value system, this small-scale study explored the change in values and perceptions of a disaster-affected mountain community about natural hazards and its implications for their future lives. Twenty participants from the affected community, including local political activists, religious leaders, teachers, and youth activists, were thoroughly interviewed. The study explored significant deviations from their traditional values of connectedness to each other and with their ancestors' land. The emergence of new values like local wisdom for disaster management and the education of their children was also noted. The fading of the values of connectedness to the region and the values of helping each other have serious implications for the breaking of generational old cultures and values that may trigger mass migrations from such regions that will result in the abandonment of mountain villages. [ABSTRACT FROM AUTHOR]