Emergency Management Research Articles

EVALUACIÓN EN LA NUBE DE LA CAPACIDAD DE GESTIÓN DE EMERGENCIAS DEL GOBIERNO ANTE CATÁSTROFES POR INUNDACIONES URBANAS: DATOS DE CHINA

A relevant evaluation index system was established in this study for the objective measurement of emergency management capability for urban flood disasters based on the four stages of emergency response, namely, “prevention, early warning, response, and recovery.” The weight distribution of different evaluation indices was calculated by using the CRITIC method, which generated an evaluation cloud and a result cloud based on the cloud model. A case study on the emergency management of Zhengzhou City in Henan Province of the “7.20 Flood Disaster” was conducted, and the evaluation results were displayed intuitively as the digital features of the cloud model and in the computational cloud diagrams. The evaluation results of the emergency management capability of Zhengzhou City for the “7.20 Flood Disaster” were obtained, and a new direction for emergency management capability improvement was proposed based on a capability enhancement priority matrix. Results showed that Zhengzhou City exhibited only the “simple level - system management mode” in coping with the “7.20 Flood Disaster.” Zhengzhou City can improve its emergency management capability against flood disasters by improving the reliability of its monitoring and communication systems, the effectiveness of its publicity and education measures, and the timeliness of its provision of postdisaster information statistics and reports. The conclusions disclose a new direction for the scientific judgment of emergency management capability for flood disasters and the formulation of capability enhancement strategies. Key Words: Flood disasters; emergency management capability; cloud model; CRITIC method; capability enhancement matrix

Policy Note: Special Taxes for Special Times? A Critical Analysis of Fiscal Crisis Responses with an Earmarking Feature in the Context of EU Law

Do special times require special taxes? The answer may not be the same from a legal, political, or economic perspective. One type of answer that legislators in Europe – both on the national and the supranational level – have given to the crises that make our times special are fiscal measures targeting extraordinary profits, revenues, or even assets while reserving the collected revenue for specific purposes. This article discusses the arguments for and against such earmarked crisis response measures in the context of their implications in the framework of EU law. It argues that specific earmarks may be attractive for reasons of political psychology such as health expenditure or inflation relief for households and firms. However, they may have unintended legal consequences by putting the respective measure into the scope of other legal regimes such as social security or banking regulation. The article contributes to the current debate about appropriate fiscal measures in times of crisis by pointing to examples of such direct and indirect interactions with primary or secondary EU law based on earmarking.

Pneumothorax at the Onset of Robot-Assisted Laparoscopic Treatment for Pelvic Endometriosis: Emergency and Definitive Management

Pneumothorax at the Onset of Robot-Assisted Laparoscopic Treatment for Pelvic Endometriosis: Emergency and Definitive Management

Exploring influential components and indicators in hospital resilience assessment: a scoping review protocol

IntroductionHospitals are vital infrastructures that provide health services during emergencies and disasters. However, in recent years, disasters have led to hospital losses and interruptions in medical services. Consequently, the concept of resilience has garnered significant attention. Despite extensive research, the lack of clarity in explaining hospital resilience poses challenges in effective assessment and identifying key priorities for enhancing disaster risk management. Recently, the WHO’s Eastern Mediterranean Regional Office (EMRO) introduced a conceptual framework for the conceptualisation of hospital resilience, defining it through six interconnected components and four resilience capacities. Identifying specific indicators and characteristics for hospital resilience components based on the EMRO framework. This protocol outlines the method for conducting a scoping review to identify such indicators and characteristics to develop a comprehensive hospital resilience assessment tool.Methods and analysisThis scoping review will adhere to the six-step protocol proposed by Arksey and O’Malley. It aims to comprehensively understand current knowledge about resilient hospital characteristics and identify effective components and indicators for assessing hospital resilience. The review will encompass available articles indexed in PubMed, Scopus and Web of Science. Additionally, searches will explore the grey literature on Google Scholar, the WHO’s website and regional offices. There will be no publication date restrictions applied to the search. Quantitative and qualitative content analyses will assess and categorise the study results. Our protocol was drafted using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols extension for scoping reviews.Ethics and disseminationThis protocol describes a scoping review within a doctoral thesis focused on health in emergencies and disasters, specifically hospital resilience. The study, associated with ethics code number (IR.USWR.REC.1402.120), aims to develop a comprehensive assessment tool for hospital resilience. Once peer-reviewed and published, the findings will inform experts, policymakers and relevant organisations in emergency and disaster management.

A Semantic Augmented Approach to FEMA P-58 based Dynamic Regional Seismic Loss Estimation Application

Regional seismic loss estimation (RSLE) is a crucial process in both immediate post-earthquake emergency response and long-term reconstruction endeavors. Over the years, significant progress has been made in RSLE: sensing approaches such as field investigation and remote sensing offers a comprehensive overview necessary for real-time disaster response, while simulation techniques such as the methodology proposed in Federal Emergency Management Agency (FEMA) P-58 series provide insights into the mechanism of disaster development and its potential long-term impacts on urban assets. Nonetheless, challenges persist in the realm of practical RSLE applications. Firstly, a dynamic understanding of a disaster event and its influence is deemed important for effective emergency responses while challenging to achieve in current approaches. Secondly, stakeholders with varying roles, including administrators, rescue teams and ordinary citizens have distinct information requirements for RSLE. Thirdly, the complexity of seismic loss estimation, involving diverse data sources such as building information models, performance models, fragility data and sensor observations, poses interoperability issue. To tackle these issues, this article introduces a dynamic, multi-granularity, ontological representation scheme tailored for RSLE decision-supporting systems. This scheme operates across various scales, from individual building components to broader regional scales by synergistically employing FEMA P-58 guidelines and Semantic Web technologies. Upon the corresponding semantics, a question-and-answer agent powered by large language model is further developed to facilitate interaction requirements within the RSLE process via FEMA P-58 pipeline. The practical efficacy of this approach is validated through a prototype deployed under a real earthquake event, demonstrating its value in real-world scenarios.

Impact of on-hours versus off-hours admission on outcome in pediatric patients with testicular torsion

ObjectivesTesticular torsion (TT) is an emergency requiring timely surgery to prevent testicular loss. There is a lack of reports on the clinical significance of the time of admission (on-hours vs. off-hours) on the long-term surgical outcome of TT. MethodsWe retrospectively reviewed all consecutive patients <18 years who were admitted to the hospital and treated for TT during the ten years. Patients were classified according to their admission time: weekday (on-hours), outside working hours, and weekends (off-hours). They were also classified based on their testicular outcome: salvaged and non-salvaged testis. ResultsSeventy-two patients were included. Their median age was 14.2 years. Thirty-three patients (46 %) were admitted during on-hours, whereas 39 patients (54 %) were admitted during off-hours. Forty-three patients (59.7 %) required orchidopexy and, out of those, during the long-term follow-up, only 27 (37.5 %) had definitive testicular salvage. Forty-five patients (62.5 %) were with no testicular salvage. On-hours vs. off-hours admission had no impact on the clinical outcome (p = 0.25). However, significant differences in the duration of symptoms (DoS) between the orchidopexy and orchidectomy groups were observed (p < 0.001). ConclusionTesticular torsion is a time-dependent diagnosis, and any delay in treatment could cause testicular loss. Our data suggest that the DoS before admission, rather than the admission time, influences the testicular outcome. The efficient management of emergencies regardless of the time of day is a key factor for the reduced probability that admission timing affects outcomes.

Climate change, climate disasters and oncology care: a descriptive global survey of oncology healthcare professionals.

Climate disasters and climate change have implications for healthcare globally. As the number and intensity of climate disasters increase, it is important to understand the effects on healthcare. We conducted a global survey of oncology healthcare providers to identify awareness, experiences, and educational needs related to climate change. An existing climate and health survey was adapted to oncology. This IRB- approved, 30-item survey measured demographics, climate disaster awareness, effects on cancer care and educational needs. Healthcare professionals employed in oncology settings (practice, research, or academic) were eligible. The survey was disseminated via social media and professional organizations. Descriptive statistics were computed using SPSS. 154 responses from 26 countries were received from nurses (56%), physicians (19%), and other healthcare professionals (25%). Common climate change-related events impacting oncology care were extreme heat (63.8%) and heavy rains (52.2%). Respondents reported their workplace has a disaster plan for climate-related weather events (50.4%) or has taken steps to prepare for a climate-related weather event (48.5%). Respondents were aware that the planet has warmed significantly (98.7%), that healthcare contributes to greenhouse gas emissions (98.6%) and reported wanting to learn more about how climate change affects cancer care (88.3%). Preferred educational modalities include webinars (69%), e-learning (55%), journal articles (48.3%), conferences (46.3%) and podcasts (38.9%). This global survey is the first to identify the awareness, experiences, and educational needs of oncology healthcare professionals related to climate change and climate disasters. Healthcare providers are positioned to take leadership roles related to climate and health.

A review of risk analysis and accident prevention of blowout events in offshore drilling operations

A review of risk analysis and accident prevention of blowout events in offshore drilling operations

A Hybrid Simulation‐Based Workshop Improves Knowledge and Confidence in the Management of Hemorrhagic Conversion of Stroke Among Interventional Neurology Trainees

Background Mechanical thrombectomy is the standard of care in acute ischemic stroke with anterior large vessel occlusion presenting within 6 hours of symptom onset, but complications do exist. We assessed the feasibility of a hybrid simulation‐based workshop at a national meeting for interventional neurology trainees focused on the management of acute ischemic stroke and tissue‐plasminogen activator‐related hemorrhage. Methods In this prospective, observational, hybrid simulation‐based study at a fellows’ workshop at a national conference, participants were asked to manage a patient with acute ischemic stroke in the neurointerventional suite followed by thrombolytic‐related hemorrhage leading to cerebral herniation during mechanical thrombectomy. We evaluated the participants’ ability to complete critical actions that were developed based on best practices and relevant American Heart Association guidelines and the Neurocritical Care Society's Emergency Neurological Life Support protocols. The primary outcome was the improvement in knowledge from a precourse to postcourse test. Secondary outcomes included participant reactions. Results Sixty trainees completed the simulation session in 8 groups. The mean sum of critical actions completed by trainees was 9.75/14 (70%). There was a moderate effect of the intervention on trainees’ knowledge from pretest (mean 3.8, SD = 0.3) to posttest (mean 4.3, SD = 0.3). The simulation scenario was described as moderately realistic, very engaging, and extremely satisfactory. Following the workshop, all fellows endorsed an increase in proficiency and confidence in neurological emergency management. Conclusion Simulation‐based workshops at national conferences are feasible and a potentially useful tool for safely educating a large audience of trainees who may not have access to high‐fidelity simulation platforms at their institutions.

IMPLEMENTING AND EVALUATING A PAEDIATRIC EMERGENCY MANAGEMENT TRAINING PROGRAM FOR PRIMARY HEALTHCARE WORKERS IN ZARIA

Nigeria continues to grapple with alarmingly high under-five mortality rates, with approximately 2,300 children dying daily due to preventable and treatable diseases such as pneumonia, malaria, and diarrheal illnesses. This crisis is particularly pronounced in rural areas, where childhood mortality rates are significantly higher than in urban centres. For many rural communities, primary healthcare (PHC) centres serve as the sole access point to medical services, making these centres critical to addressing this public health challenge. Despite their importance, PHC centres often face significant challenges, including inadequate infrastructure, limited access to essential medications, and a shortage of adequately trained health personnel. This study aimed to implement and evaluate a Paediatric Emergency Management Training Program for healthcare workers at PHC centres in Zaria, Kaduna State. The primary objective was to assess the effectiveness of the training in improving the competency of health workers in managing common paediatric emergencies, thereby enhancing the overall quality of care provided at these centres. A cross-sectional descriptive study was conducted involving 139 healthcare workers from selected PHC centres in Sabon Gari and Zaria Local Government Areas, utilizing a multi-stage random sampling technique. Data collection was performed using a pre-tested, semi-structured, self-administered questionnaire designed to evaluate the participants' baseline knowledge, followed by an assessment after the training intervention. The data were analysed using SPSS version 21, with chi-square tests employed to examine the associations between variables. Results were presented using tables and charts for clarity. The findings revealed a generally low baseline competency in managing common paediatric emergencies among the healthcare workers. Specifically, 66 (48.5%) of the respondents demonstrated very poor knowledge regarding the causes of common paediatric emergencies, 32 (23.5%) had poor knowledge, 34 (25.0%) had good knowledge, and only 4 (2.9%) of the respondents exhibited excellent knowledge. Similarly, knowledge regarding the treatment of these emergencies was also lacking, with 46.7% of respondents showing very poor understanding, 34.1% having poor knowledge, 16.3% demonstrating good knowledge, and only 3.0% showing excellent knowledge. A statistically significant relationship was observed between academic qualifications and knowledge levels in both causes (p = 0.004) and treatment (p = 0.000) of paediatric emergencies. The low baseline knowledge underscores the critical need for targeted training interventions. The study highlights the importance of establishing a sustained partnership between the Department of Paediatrics at Ahmadu Bello University Teaching Hospital and the Departments of Primary Health Care in Zaria and Sabon Gari Local Governments. Regular training workshops, held quarterly, are recommended to continuously equip PHC workers with the necessary skills to effectively manage paediatric emergencies, ultimately contributing to a reduction in childhood mortality rates in the region.

An evacuation model considering pedestrian group behavior under violent attacks

In recent years, violent attacks have garnered significant attention from the international community and gradually evolved into a global issue. In responding to such emergencies, effective emergency evacuation is an essential means to ensure public safety. In order to explore the pedestrian evacuation dynamics in violent attacks and understand the behavioral characteristics of individuals and the dynamic interactions of groups during the evacuation process, this paper proposes an agent-based cellular automata evacuation model. First, each agent is assigned several internal attributes such as life value, panic value, and movement speed, and the assignments fully take into account the heterogeneity of individuals. Next, by setting the attack strategy of attackers and the evacuation mechanism of pedestrians, the complex system is modeled from a microscopic perspective. Finally, the effects of critical factors on the pedestrian evacuation process, such as panic coefficient, crowd structure, group ratio, attack distance and intensity, attacker location and number, and counterattack probability, are discussed through simulation. The results show that the tension caused by moderate panic is beneficial, but excessive panic will lead to increased evacuation time and fatalities. Meanwhile, the group behavior among pedestrians causes them to move relatively lagging, and the evacuation efficiency decreases as the group scale increases. Additionally, increases in attack intensity, attack distance, and attacker number all result in more casualties, and the consequences are most severe when multiple attackers operate separately, but counterattacks by pedestrians can significantly improve the overall safety of evacuation. Our study can provide some reference and basis for emergency management under violent attacks.

Short-term inbound passenger flow prediction at high-speed railway stations considering the departure passenger arrival pattern

Accurate prediction of short-term inbound passenger flow at high-speed railway stations is of great significance for the refined operation of stations, the formulation of emergency plans, and the provision of intelligent services. The arrival of passengers traveling on the same train at the same station shows a similar pattern, which is called the departure passenger arrival pattern (DPAP). The short-term inbound passenger flow at the station is composed of the short-term inbound passenger flow of all waiting trains within the same period. Inspired by this, this paper develops an ensemble prediction model based on the time series decomposition modeling strategy to introduce the DPAP to the short-term inbound passenger flow prediction at stations. Firstly, we propose a new framework for studying the DPAP to calculate the fitted station short-term inbound passenger flow, which is only affected by the DPAP. During this process, we find that 7minutes is the optimal time granularity. Secondly, based on the singular spectrum analysis, we prove that the DPAP is the determining factor affecting the station short-term inbound passenger flow. Finally, we propose an ensemble prediction model that considers the DPAP to achieve short-term inbound passenger flow prediction at stations. The model consists of two parts: the deterministic and stochastic components prediction, where the former is predicted by the fitted station short-term inbound passenger flow, and the latter is achieved by the combination of historical stochastic components and weather type with the help of the Seq2Seq model based on time attention mechanism. Using real inbound passenger flow data, we compare the proposed model with 13 benchmark models and the results show that under different training and prediction steps, our model achieves optimal prediction performance, whether in all-day period and the busiest period of the station. Through further ablation experiments, it has been proven that the introduction of the DPAP effectively improves the prediction accuracy. Our model can provide scientific support for the intelligent operation of stations and the refined management of passenger flow.

Estimation of Earthquake-Induced Direct Economic Losses of Portfolio Buildings Based on Seismic Fragility Surface

Regional seismic loss assessment is crucial for developing earthquake emergency plans, which can significantly reduce casualties and socioeconomic losses in urban communities. Due to the complex types of building structures in a region, it is not possible to accurately measure the damage state of building structures using a single scalar ground motion intensity measure (IM). To more accurately reflect the responses of structures under earthquake excitations, the seismic fragility surface models for 4 typical RC frame structures are developed based on the vector ground motion IMs. The results indicate that the fragility surface model offers a superior level of precision in capturing the inherent uncertainty of ground motion and subsequently determines a more precise probability of structural failure, outperforming traditional single scalar ground motion IM fragility curve models. This enhanced accuracy holds significant implications for regional loss assessment. To fully consider the spatial cross-correlation of vector ground motion IMs, based on the established ground motion database of 8778 records, principal component analysis (PCA) and geostatistical analysis methods are used to construct a spatial cross-correlation influence field that simultaneously considers multiple ground motion IMs to simulate more realistic earthquake scenarios. Considering the impact of uncertainty in loss ratio on earthquake-induced direct economic loss estimation results, the maximum entropy technique is used in conjunction with an improved Latin Hypercube Sampling (LHS) to achieve spatially uniform sampling of loss ratio (LR). This study proposes an assessment framework for regional seismic direct economic loss for portfolio buildings based on the seismic fragility surface model considering spatial cross-correlation and uncertainty of loss ratio. The proposed framework is verified by numerical examples, and it is proven that the regional portfolio buildings considering multiple ground motion IMs is more reliable and robust than those merely considering a single ground motion IM, and when spatial cross-correlation is not considered, the probability of serious economic losses will be underestimated.

Protecting nutrition in a food crisis.

Food insecurity and malnutrition are rising worldwide due to disruptions in food systems related to interconnected health-, climate- and conflict-related crises. Although governments globally are committed to addressing nutritional challenges, policy responses have increasingly focused on food security and, particularly, on food affordability. However, these short-term measures often overlook the necessity of integrating nutritious foods into the food system to ensure improved long-term nutrition. By drawing on the United Nations Committee on World Food Security's Voluntary guidelines on food systems and nutrition, this article outlines opportunities for policy-makers to integrate nutrition into key elements of the crisis response. Key policy areas where nutrition could be further integrated include social protection, agricultural investment, trade policy and urban planning. Strengthening the focus of nutrition in these measures will be essential to establish long-term incentives that support food systems transformation for improved nutrition. Drawing on theories of the policy process, I propose that stronger governance and cross-sectoral dialogue will be critical to achieve sustained nutritional outcomes. Health policy-makers can play a leadership role in supporting cross-sectoral policy change by carefully framing the policy issues, advocating for institutional structures that promote collaboration across sectors to prioritize nutrition, and strengthening the management of conflicts of interest in food system policy-making.

Social media‐enabled crisis response in Vietnam: A tương thân tương ái perspective

AbstractA growing amount of information systems (IS) research is examining the use of social media to enable effective crisis response. However, existing studies have overlooked the impact of indigenous concepts, which play an important role in crisis response. Our study intends to offer an indigenous perspective to this research stream by examining how social media‐enabled crisis response is enacted in Vietnam. We used COVID‐19 as the focal crisis and collected a rich set of discussion threads from social media. By analysing the data through the grounded theory method, our study identifies the indigenous theoretical concept of tương thân tương ái. We further unveil a process model consisting of six mechanisms through which tương thân tương ái inspires crisis response on social media and three roles assumed by social media during this process. Our study contributes to the literature on social media‐enabled crisis response by providing an indigenous perspective and a context‐specific explanation. It also enriches IS theory in the Association of Southeast Asian Nations (ASEAN) by investigating how the indigenous concept of tương thân tương ái influences Vietnam's crisis response on social media. Our findings also provide guidelines that can help communities beyond Vietnam to promote the values of tương thân tương ái during crisis response.

The Double Mediating Effect of Safety Motivation and Safety Behavior in the Relationship Between Construction Site Workers' Emotional Safety Culture Awareness and Accident Prevention

The Double Mediating Effect of Safety Motivation and Safety Behavior in the Relationship Between Construction Site Workers' Emotional Safety Culture Awareness and Accident Prevention

Archetypes and change in wildfire risk perceptions, behaviours and intentions among adults in Tasmania, Australia

Background Anthropogenic climate change globally increases wildfire risk. Understanding how wildfire threats impact community-wide risk perceptions and response options will critically inform resilience education strategies. Aim To gain an increased understanding of wildfire risk perceptions and self-evacuation intentions among residents in the wildfire-prone state of Tasmania, Australia. Methods We co-designed survey questions with stakeholders from emergency management, health and community recovery, using a computer-aided telephone interview to survey residents over 18 years of age. Numerical classification analysis, linear regression and descriptive statistics were used to analyse survey data. Results We identified four archetypes – the ‘immediate leaver’, ‘prepared stayer’, ‘unprepared leaver’ and ‘informed leaver’, each with distinct sociodemographic characteristics. Key variables were gender, age, location and income, with women most likely to leave and lower-income householders from rural areas most likely to stay. Previous wildfire experience and owning a home were significantly associated with increased preparedness actions. Compared to 2016, we found a significant increase in the proportion of residents intending to leave their property, with rural men least likely and urban women most likely to leave. Implications Recent education campaigns have likely driven increases in wildfire threat-related self-evacuation, yet the existence of distinct archetypes argues for more tailored messaging and education programs.

Accident Prevention System for Cars, Buses, Trucks

Driver drowsiness is a significant factor in road accidents, contributing to a large number of crashes annually. To enhance road safety, the development of a Drivers Drowsiness Detection System is essential. This system builds to detect early signs of lazyness in drivers and provide timely alerts to prevent accidents. The proposed system uses to track key indicators of drowsiness, such as eye closure, head position, yawning, and blink rate. By utilizing a camera-based real-time monitoring system, it continuously analyzes the driver’s facial expressions. The system employs cadcade algorithms to distinguish a featurebased object detection algorithm to detect objects from images between alert and drowsy states based on collected data. When drowsiness is detected, the system triggers alerts like audio warnings, seat vibrations, or even vehicle slowing mechanisms, depending on the integration. This technology has the potential to significantly reduce the number of road accidents related to driver fatigue and could be applied in both personal vehicles and commercial fleets. The implementation of such systems represents a critical step toward improving road safety and decreasing driver-related incidents. Nowadays it is very challenging to stay active all the time due to busy schedules. Falling asleep while driving can lead to serious consequences, accidents, and even death. This situation is much more common and therefore it is very important to solve this problem. So, to solve this problem, we developed a sleep alarm system for drivers. This system alerts the user when he falls asleep at the wheel, thus the main concern is preventing accidents and saving lives. This system is useful for long- distance travelers and late-night drivers.

Development of Database-Based Pedestrian Accident Scenarios and Analysis of Accident Prevention Effects from V2X Application

Development of Database-Based Pedestrian Accident Scenarios and Analysis of Accident Prevention Effects from V2X Application

Development of an Optimized Accident Prediction Model for Construction Safety Using Big Data Analysis

Background and objective: The objective of this study was to develop an intuitive accident prediction model that can be readily applied at construction sites to effectively reduce the incidence of accidents through the analysis of construction accident data.Methods: These accidents significantly contribute to the construction industry's overall accident rate. Accident types were categorized into fatalities, injuries, and material damages to construct the accident prediction model. A total of 24 factors were considered across eight major variables, which were identified during the first and second phases of data preprocessing to analyze construction accident big data. Machine learning techniques were employed, specifically supervised learning and ensemble learning, to identify the optimal predictive model.Results: Among the models tested, XGBoost emerged as the most effective due to its highly balanced accuracy, even in the presence of class imbalance.Conclusion: The implementation of the XGBoost accident prediction model, along with the feature importance codes developed in this study, enables the prediction of accident types for specific tasks performed at construction sites. This predictive capability is expected to inform the implementation of targeted accident prevention measures, such as enhancing safety protocols or adjusting work procedures based on the prediction outcomes.