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Located within the seismically active Pacific Ring of Fire, California's transportation infrastructure, especially in the Bay Area, is susceptible to earthquakes. A review of current research and stakeholder interviews revealed a growing awareness of emergency preparedness among local jurisdictions and transit agencies in recent years. However, many have yet to formalize and publish their recovery plans. This study introduces an agent-based multimodal transportation simulation tool to enhance post-earthquake transportation resilience. Integrating a road network simulator with a metro system simulator, the tool employs an optimized Dijkstra-based algorithm to calculate optimal routes, travel times, and fares. A case study is conducted for the East Bay, using the simulator to gauge the impact of a compromised Bay Area Rapid Transit (BART) system. The results suggested that original BART passengers could face either longer commute times or higher costs during the recovery phase of a major earthquake without appropriate policies. Such outcomes could disproportionately burden low-income riders, affecting their mobility and overall travel time.

In the event of a wildfire, government agencies need to make quick, well-informed decisions to safely evacuate people. Small communities, such as in Marin County, with a mix of residences and flammable vegetation in Wildland-Urban Interface zones tend to lack resources to conduct evacuation studies. Consequently, this study uses a framework of wildfire and traffic simulations to test the performance of potential evacuation strategies, including reducing the volume of evacuating vehicles through car-pooling, phasing evacuations by staggering evacuation times by zone, and prohibiting street parking in four representative areas of Marin County. Results show that reducing vehicle numbers lowers the average travel time by 20%-70% and average exposure time to wildfire by 27%-60% from the baseline. Phased evacuations with suitable time intervals lower the average travel time by 13.5%-70%, but may expose more vehicles to fire in some situations. Prohibiting street parking yields varying results due to different numbers of exits and evacuees. In some cases, prohibiting street parking reduces the average travel time by over 50%, while in other cases it only reduces the average travel time by 9%, contributing little to evacuation efficiency. Altogether, Marin County may want to consider developing a communication and parking plan to reduce the number of evacuating vehicles in wildfire situations. Phased evacuation is also highly recommended, but the suitable phasing interval depends on the speed of fire spread and number of evacuees. Further, whether to establish street parking prohibition policies for a certain area depends on the number of exits and the number of vehicles on the streets.

This paper introduces iTEVAC, an advanced model of the Trusted Evacuation System (TEVAC), designed to optimize emergency evacuation procedures within commercial centers. Building upon the principles of TEVAC, iTEVAC incorporates additional features such as isolation, firefighting, and rescue intervention strategies to enhance the system's performance and efficiency. iTEVAC leverages the power of Fog computing and Internet of Things (IoT) devices to provide real-time guidance for individuals during emergencies. The system operates by executing alerts for isolated nodes and those unable to find an exit route, providing detailed guidance for nodes that need to move within the commercial center's network. A key advantage of iTEVAC is its decision-making speed, which is less than 1 second, crucial in high-stakes, time-sensitive situations. The iTEVAC model also addresses the limitations of older buildings, traditional markets, and crowded areas that often lack efficient and integrated evacuation systems. It allows users to rely not only on smart navigation guide panel but also on their smartphones to find the safest direction using local Wi-Fi and broadband cellular networks, supported by Fog computing. The iTEVAC model represents a significant advancement in emergency response strategies, contributing to the development of more effective and intelligent evacuation strategies. [ABSTRACT FROM AUTHOR]

How to effectively guide occupants to use different evacuation routes under fire situations is the key to improving fire safety and ensuring successful evacuation. Evacuation analysis for fire safety in surveillance videos plays a crucial role in understanding and mitigating risks. The fundamental diagram of pedestrian flow, which illustrates the relationship between pedestrian velocity and crowd density, is a valuable tool for analyzing evacuation dynamics and enhancing fire safety measures. Traditional methods rely on trajectory files obtained from manually tracking each pedestrian in video recordings to construct fundamental diagrams. However, these methods have limitations in accurately representing crowd density and cannot provide real-time analysis, making them unsuitable for surveillance camera analysis in fire safety scenarios. To address this challenge, we propose a novel convolutional neural network-based framework called the deep fundamental diagram network, which is specifically designed for fire safety applications. This framework consists of two modules: the multi-level dilated convolutional neural network (MLD-Net) and the optical flow module. The MLD-Net learns the mapping relationship between input images and density maps, enabling accurate estimation of pedestrian density. Simultaneously, the optical flow module calculates pedestrian movement speed, providing crucial information for evacuation planning. By aligning the density map with the speed map, the fundamental diagram is derived, which aids in understanding evacuation dynamics. The experimental results demonstrate that our method achieves good consistency with traditional approaches while significantly reducing the computational time. Additionally, our framework enables anomaly detection and pedestrian line counting, further enhancing fire safety measures. This work is expected to have good prospects in the fields of fire safety, evacuation dynamics analysis, and real-time crowd analysis systems for fire situations. [ABSTRACT FROM AUTHOR]

Background: Several organizations have proposed guidelines or clinical decision tools for the management of patients with disorders of gut‐brain interactions (DGBI) affecting the lower digestive tract including irritable bowel syndrome and chronic idiopathic constipation. Such algorithms are based on sequential therapeutic trials and modifying the treatment strategy based on efficacy and adverse events. Purpose: The aims of this review are to evaluate the evidence for efficacy of second‐ and third‐line pharmacotherapies and to assess the evidence for the alternative option to manage subgroups of patients with symptoms suggestive of lower DGBI based on diagnostic tests or documented dysfunctions. The preeminent tests to identify such subgroups that present with symptoms that overlap with lower DGBI are detailed: digital rectal examination as well as anorectal manometry and balloon expulsion for evacuation disorders, detailed measurements of colonic transit, and diagnosis of bile acid diarrhea or carbohydrate malabsorption based on biochemical measurements. The review also addresses the cost implications of screening to exclude alternative diagnoses and the costs of therapy associated with the therapeutic options following an algorithmic approach to treatment from the perspective of society, insurer, or patient. Finally, the costs of the diagnostic tests to identify actionable biomarkers and the evidence of efficacy of individualized therapy based on formal diagnosis or documentation of abnormal functions are detailed in the review. [ABSTRACT FROM AUTHOR]

The article presents the results of experimental studies of evacuation of 50 people from a road tunnel in various smoke conditions. Calculations of total evacuation times, pre-movement times and movement speeds were carried out and the impact of smoke on the speed of movement was analyzed. The pre-movement times, the alarm realization and response times for the subsequent experiments (1, 2 and 3) were 36, 7 and 5 s, respectively. The total evacuation times for 3 experiments were 340, 301 and 215 s. It has been shown that the speed of movement in smoke depends not only on the density of smoke, but also on the very attitude of the experiment participants and knowledge of the tunnel. It has also been shown that the adverse impact of low visibility on the evacuation time and movement speed is as important as the motivation of the evacuees and the effect of learning. In order to collect the observations of the participants, as well as assess potential aspects which might have influenced the process of evacuation, a survey was conducted after both experiments. The answers show that the two main reasons that prompted the evacuation were smoke in the tunnel and the fire drill. [ABSTRACT FROM AUTHOR]

Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment. [ABSTRACT FROM AUTHOR]

This paper delves into the pivotal role of machine learning in responding to natural disasters and understanding human behavior during crises. Natural disasters, from earthquakes to floods, have profound consequences for both the environment and society, impacting health, the economy, and mental well-being. Prevention and preparedness are key components of disaster management, yet the psychological challenges faced by affected individuals are equally significant. Psychosocial support and educational programs play a vital role in aiding individuals in their recovery. Machine learning, in this context, offers the ability to predict the evolution of natural disasters, providing early warnings that can save lives and reduce losses. It further extends to analyzing data related to human behavior during disasters, enhancing readiness for future calamities. This study specifically addresses the challenge of understanding human behavior during a snowstorm that struck Greece in 2023, employing artificial intelligence techniques to develop classification models categorizing individuals into three distinct groups based on socio-economic characteristics and is one of the few machine learning approaches that have been performed to date on data derived from corresponding questionnaire surveys. Artificial intelligence methodologies were harnessed to construct these classification models, with a focus on categorizing individuals into three specific classes: "Did not travel at all", "Traveled only as necessary", or "Did not limit travel". The dataset employed in this study was collected through a survey conducted within the framework of the AEGIS+ research project, concentrating on assessing the mental health of individuals impacted by natural disasters. The goal was to generalize the optimal classification model and extract knowledge applicable in natural disaster scenarios. Three methodological frameworks for data analysis were proposed, incorporating combinations of Simple Logistic Regression and Inductive Decision Trees with the SMOTE data balancing method and a new data balancing method called LCC (Leveling of Cases per Class), within the context of validation procedures like "Use Train Set," "10-fold Cross Validation," and "Hold Out." This paper's contribution lies in the development of hybrid classification models, highlighting the significance of data balancing with LCC method throughout the modeling process. The results were deemed satisfactory, with the inductive decision tree method demonstrating superior performance (Classification accuracy near to 90%). This approach, offering strong classification rules, holds potential for knowledge application in natural disaster risk management. Knowledge Mining and Metadata Analysis further revealed the socio-economic characteristics influencing the decision to move during a natural disaster, including age, education, work-status, and workstyle. Crucially, this work, in addition to providing knowledge through the data mining process that can be used to estimate evacuation probability, develop targeted emergency information messages, and improve evacuation planning, is also used as a catalyst for future research efforts. It encourages the collection of relevant data, the exploration of new challenges in data analysis related to natural disasters and mental health, and the development of new data balancing methods and hybrid data analysis methodological frameworks. [ABSTRACT FROM AUTHOR]

This study addresses the challenge of optimizing fire evacuation efficiency in complex buildings by investigating the impact of automating corridor dimension adjustments on reducing evacuation congestion. A Building Information Modeling (BIM)-based approach using Autodesk Revit 2024, Dynamo version 2.17, and Thunderhead Pathfinder 2023 simulations was employed to test this hypothesis. The results show that automated adjustments in hallways have a significant positive impact on evacuation efficiency in the majority of building floor corridor segments. These findings highlight the potential for dynamic design modifications to enhance building safety and sustainability. Future research will focus on refining this approach for diverse building layouts and occupant behaviors. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Disasters often require large-scale evacuations, and damage key infrastructure (e.g., power, transportation). With growing electric vehicle (EV) adoption and electrification of transportation, governments and utilities may face significant power challenges during disasters, especially during the evacuation stage. Low state-of-charge, sporadic charging infrastructure, or power outages could significantly hamper safe and effective evacuations. Yet, EVs also offer possible resilience benefits to emergency response by more easily charging electronics or sending power back to the grid through vehicle-to-grid (V2G) technology. This paper focuses on the opportunities, benefits, and drawbacks of EVs in disasters and evacuations through a systematic review of current literature, reports, and sources. Overall, this review discovered EVs show promise as modes of transportation and mobile energy supply units. However, crucial challenges such as charging infrastructure locations, upfront cost of resilience technologies, and user behavior necessitate more dedicated research to overcome shortcomings and guide more realistic implementation of benefits. [ABSTRACT FROM AUTHOR]

Following an earthquake, abnormal travel demand causes traffic congestion and poses significant problems for relief efforts. Research on post-earthquake travel demand is essential for disaster management. An effective disaster management strategy ensures achieving sustainable development goals. This study focused on this critical period and analyzed post-earthquake trip decisions. The city of Elazığ, a region not at risk of tsunami, was used as a case study. A 6.8 magnitude earthquake hit Elazığ in January 2020. After the earthquake, data from 2739 individuals were collected by a household survey conducted face-to-face. The data were segregated into two categories, depending on the earthquake's intensity. The study used a binary logit model to examine the potential factors of trip decisions after an earthquake. The results showed that 75% of participants made at least one trip within 24 h after the earthquake. It was observed that household, building-and disaster-related attributes influence earthquake survivors' trip decisions. The initial location at the time of the earthquake was the most significant factor affecting trip decisions. It was also found that individuals who experienced the earthquake outside their homes in both datasets were more likely to make a trip. Additionally, the dataset with higher earthquake intensity had more significant variables affecting the trip decision. [ABSTRACT FROM AUTHOR]

The Lumajang Regency is highly vulnerable to various natural disasters, particularly the potential eruption of Mount Semeru. In disaster response efforts, the local government needs to prepare effective and efficient evacuation routes, taking into account the magnitude of the eruption impact in the Semeru disaster-prone area. This research focuses on evacuating vulnerable residents using electric and conventional vehicles. This study is categorized as a vehicle routing problem with energy constraint (VRPEC) because the electric vehicles utilized in this research do not require recharging during their operational process, ensuring rapid evacuation as it is essential. By utilizing Geographic Information Systems (GIS)-based optimization, the best route to evacuate all victims within 12 h is determined. This study involves developing scenarios considering the number of vehicles and their travel distances. There are also evacuation guidelines, including the implementation of priority points and evacuation zone usage. The research results indicate that scenarios EV 5, 8, and 10 are the most optimal for using electric vehicles. Meanwhile, the optimal scenario for conventional vehicles is scenario 5. This analysis shows that implementing electric vehicle scenarios is superior to conventional vehicle scenarios in terms of the total time required to evacuate all victims. [ABSTRACT FROM AUTHOR]

Gestational trophoblastic disease (GTD) refers to a group of pregnancy-related tumors that are recognized as the most curable gynecologic malignancies. Diagnosing GTD can be challenging, particularly after a non-molar pregnancy, due to its various presentations, which may mimic retained products with hypervascularity or arteriovenous malformation. Human chorionic gonadotropin (HCG) serves as an excellent biomarker for monitoring disease progression, response to treatment, and post-treatment surveillance. A plateaued or rising HCG level can facilitate the early detection of progression from complete or partial hydatidiform mole to GTD. Here, we present a case series involving six patients with GTD who initially presented with elevated beta-HCG levels and abnormal bleeding. Of these six patients, five were initially diagnosed with hypervascular retained products following a first-trimester abortion and underwent surgical evacuation. However, due to persistently elevated beta-HCG levels and evidence of myometrial invasion, the diagnosis was later revised to GTD. All patients were successfully managed with chemotherapy. Methotrexate, as a first-line treatment, is effective in achieving complete remission in most non-metastatic and low-risk cases. It has minimal severe toxicity, excellent cure rates, and does not appear to affect fertility. In summary, gestational trophoblastic diseases represent a diagnostic conundrum for clinicians due to their diverse presentations and potential for mimicking other conditions. Nevertheless, when these diseases are identified and managed in a timely manner, the prognosis is highly favorable, underscoring the importance of vigilant monitoring and early intervention. [ABSTRACT FROM AUTHOR]

Accurate assessment of crowd evacuation inside the post-earthquake environment is critical from many perspectives, but this issue receives much less attention compared to the seismic losses of structural and non-structural components. This could be attributed to the fact that post-earthquake evacuation analysis is complex due to the interaction between human behavior and the actual built environment induced by different building contents. This study attempts to tackle this problem by investigating the impacts of different building contents on post-earthquake evacuation time by using an agent-based model that considers turning behavior. To this end, the agent-based model is first described, including: properties of the agent-based model with turning behavior, key aspects in its formulation considering different evacuation stages, and influence of different building contents (namely, debris from partition walls and ceiling systems, and various types of equipment) on the agent's behavior. Subsequently, a school building is used as a benchmark problem to validate the model without earthquake, and the findings indicate that the agent-based model can match the real safety drill results reasonably well. After the validation, the school building is subsequently designed in accordance with modern seismic design codes, and the influence of debris and equipment on post-earthquake evacuation time is quantitatively studied using a suite of pulse-type ground motions as input. Based on this case study, recommendations are made for structural and architectural designers in an effort to reduce the potential evacuation time. Specifically, debris induced by partition walls or ceiling systems should be controlled as it has the greatest impact on the total evacuation time. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of the standards determined within the Turkish "Regulation on Fire Protection of Buildings" scope on evacuation time. The evacuation performance of assembly-purpose structures was measured within the limitations imposed by the regulation. Three classes of assembly-purpose structures were analyzed, including the definition of the highest user load in the regulation. Scenarios A, B, and C, consisting of 230 sub-scenarios with varying user numbers, were created, resulting in a total of 690 different sub-scenarios being analyzed. The scenarios were analyzed using the Pathfinder program. The findings indicate that the user load is a decisive factor in evacuation time. Additionally, the exit width per person specified in the regulation was observed to be larger than necessary to maintain the same conditions. Minimum Required Safe Egress Time (RSET) values were determined for the three different assembly structures with the highest user load definition in the regulation within a fire regulation-compliant building. It was concluded that the exit capacity should exceed the limits set by the regulation to achieve shorter evacuation times. The study's findings demonstrate the need to include performance-based definitions in future amendments to the regulation. This study emphasizes the significance of performance-based analyses to underscore that overreliance on prescriptive definitions can impose limitations during the design process, negatively affecting efficiency. [ABSTRACT FROM AUTHOR]

In 2009, the International Building Code (IBC) introduced a new requirement for an additional exit stair or evacuation elevators in buildings (except residential buildings) over 420 ft. (128 m) tall. This new requirement has emerged as a critical innovation in occupant evacuation in supertall buildings, offering the potential for faster egress during emergencies. In the 2018 edition of the IBC, the analysis of full building evacuation with elevators is further required to demonstrate an evacuation time of less than 1 h. This paper examines the implementation of evacuation elevators in accordance with recent building code developments, such as the International Building Code (IBC), Chinese "General Code for Fire Protection of Buildings and Constructions" (GB 55037-2022), and the Korean Building Code (KBC). This study provides a comparative analysis of these regulations, highlighting the evolving acceptance of elevator-based evacuation methods. Since the requirements on means of egress in the codes in China and Korea follow similar concepts in the IBC, case studies of supertall buildings in China and Korea, where evacuation elevators were integrated into the overall egress strategy, are carried out to demonstrate the capability of evacuation elevators in achieving the IBC's requirement for full evacuation within one hour. Using computer-based egress modeling, the study evaluates practical solutions for reducing evacuation times, exploring factors such as elevator capacity, speed, and coordination with traditional stairwell egress. The results suggest that, while evacuation elevators can significantly improve evacuation efficiency, achieving the one-hour target remains a challenge in complex, high-occupancy environments. The study indicates the importance of optimizing the balance between stair and elevator usage and explores the future role of artificial intelligence (AI) in enhancing evacuation systems. [ABSTRACT FROM AUTHOR]

Estimating potential casualties from a significant earthquake and tsunami event is crucial to enhance disaster preparedness and response. Although various approaches exist to assess potential casualties, few studies have made direct comparisons between them. The present study aimed to clarify the differences in the estimation of casualties between an agent-based model (ABM), which can capture detailed evacuation behavior but demands significant computational resources, and a simplified approach at less computational cost by assuming that evacuees would move along a straight line from their initial location to the closest evacuation destination. These different approaches were applied to three coastal cities in Japan—Mihama, Kushimoto, and Shingu in Wakayama Prefecture—revealing significant differences in the estimated results between the ABM and the simplified approach. Notably, when the effects of building collapse due to an earthquake were considered, the mortality rates estimated by the ABM were higher than those estimated by the simplified approach in the three cities. There were also significant differences in the spatial distribution of the estimated mortality rates between the ABM and the simplified approach. The findings suggest that while the simplified approach can yield results more quickly, casualty estimates derived from such models should be interpreted with caution. [ABSTRACT FROM AUTHOR]

This study presents a proposal for procedures and recommendations for the evacuation of people from cable cars. The proposals and procedures were carried out in a specific facility located in the east of Slovakia. Cable cars represent a certain risk of endangering the lives and health of people. This threat can be caused by technical failures, meteorological conditions, or human factors. Despite the existing safety measures, which are at a high level today, extraordinary events occur on cable cars that require the intervention of the integrated rescue system. The rescue services themselves have their own specific rescue procedures and equipment for rescuing people from heights, and in this paper the most frequently used rescue procedures and methods performed by members of the Fire and Rescue Service will be presented. This paper summarizes individual rescue actions, activities, and technical equipment used in rescuing people from cable cars, as well as an analysis of individual rescue and evacuation techniques from the Skipark Erika cable car. The result of the contribution is a proposal for coordination and an evaluation of the best and most suitable method of rescue in terms of time and safety. [ABSTRACT FROM AUTHOR]

The available theories of evacuation movements are primarily founded on data gathered from adults, making them potentially unsuitable for children, especially in schools. Consequently, it is necessary to undertake further research to collect data on how children move during evacuations to understand their unique characteristics and disparities compared to adults. In this context, this paper aimed to explore the movement of school children and adolescents as they moved over stairs and through exit doorways during evacuations. The evacuation drill involved 295 school children and adolescents, whose behavior was closely monitored using a series of cameras. During the drill, their movement patterns, including flow and speed, were analyzed over stairs and through doorways. The observations revealed that children exhibited frequent interactions and contact with one another, unlike adults, who tend to maintain personal space. The findings of this study indicated that the average traveling speed over stairs was comparable to previous research, although female adolescents had a lower average speed compared to other groups. The speed and flow of participants passing through doorways were found to vary depending on their age and differed from estimates based on adult data. This study highlights that existing evacuation models fall short of adequately accounting for the dynamics of children, indicating the need for further research to improve the generalizability of evacuation models. [ABSTRACT FROM AUTHOR]

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Abstract Estimating potential casualties from a significant earthquake and tsunami event is crucial to enhance disaster preparedness and response. Although various approaches exist to assess potential casualties, few studies have made direct comparisons between them. The present study aimed to clarify the differences in the estimation of casualties between an agent-based model (ABM), which can capture detailed evacuation behavior but demands significant computational resources, and a simplified approach at less computational cost by assuming that evacuees would move along a straight line from their initial location to the closest evacuation destination. These different approaches were applied to three coastal cities in Japan—Mihama, Kushimoto, and Shingu in Wakayama Prefecture—revealing significant differences in the estimated results between the ABM and the simplified approach. Notably, when the effects of building collapse due to an earthquake were considered, the mortality rates estimated by the ABM were higher than those estimated by the simplified approach in the three cities. There were also significant differences in the spatial distribution of the estimated mortality rates between the ABM and the simplified approach. The findings suggest that while the simplified approach can yield results more quickly, casualty estimates derived from such models should be interpreted with caution.

This paper introduces iTEVAC, an advanced model of the Trusted Evacuation System (TEVAC), designed to optimize emergency evacuation procedures within commercial centers. Building upon the principles of TEVAC, iTEVAC incorporates additional features such as isolation, firefighting, and rescue intervention strategies to enhance the system's performance and efficiency. iTEVAC leverages the power of Fog computing and Internet of Things (IoT) devices to provide real-time guidance for individuals during emergencies. The system operates by executing alerts for isolated nodes and those unable to find an exit route, providing detailed guidance for nodes that need to move within the commercial center's network. A key advantage of iTEVAC is its decision-making speed, which is less than 1 second, crucial in high-stakes, time-sensitive situations. The iTEVAC model also addresses the limitations of older buildings, traditional markets, and crowded areas that often lack efficient and integrated evacuation systems. It allows users to rely not only on smart navigation guide panel but also on their smartphones to find the safest direction using local Wi-Fi and broadband cellular networks, supported by Fog computing. The iTEVAC model represents a significant advancement in emergency response strategies, contributing to the development of more effective and intelligent evacuation strategies.

Objective In order to ensure that FAO (fully automatic operation system) can effectively guarantee the safe evacuation of passengers in case of emergency and quickly resume operations after evacuation completion, it is proposed to study the evacuation solution for FAO system based on central remote supervision and command. Method Based on the line conditions (such as evacuation platform, trackbed, etc.) and vehicle conditions (providing side door and end door two evacuation modes) that affect the safety of passenger evacuation, and targeting the safety risks that may be encountered during the passenger evacuation process (such as passengers falling, train collision, transition switch injury, third rail electric shock, etc.), the evacuation activation, evacuation recovery, as well as the FAO multi-system linkage mechanism and protection method for coupling train evacuation are designed in detail from two different application scenarios of platform evacuation and interval evacuation. Result & Conclusion Line and vehicle conditions required for the realization of FAO system evacuation function are proposed. During the evacuation process, the central dispatcher can remotely monitor and direct the evacuation of passengers through CCTV (video surveillance system), PA (broadcast system), emergency intercom and other devices. At the same time, through the ATS (automatic train supervision) system, the central dispatcher can realize the linkage control of multiple systems, such as CC (car controller), ZC (zone controller), and CI (computer interlocking), in order to ensure the safety protection and evacuation recovery of passengers when evacuating through the side/end doors of trains with different marshalling on platforms or intervals. This solution significantly improves the safety level and efficiency of evacuation.

The article considers Kuibyshev city (Samara nowadays) in the wartime (1941–1943), the features of its life activity and development. The solving of the large-scale tasks raised in connection with the unprecedented evacuation of the government departments, diplomatic body, people’s commissariats, factories and population to the city deeply changed the city life. Kuibyshev was the regionally governed city, but it performed many specific functions typical for the soviet capital city of Moscow. The circumstance gave occasion to call the city of Kuibyshev unofficially «alternate capital». The research task is to analyze the various aspects of the Kuibyshev city life in the wartime: to show the different interpretations of its status perception by the historians in 1941–1943; to specify the data concerning the specified All-Union people’s commissariats being on evacuation in the city of Kuibyshev and its quantitative composition; to raise the question of the final date of the acceptance of the «special objects» No. 1 (Stalin’s bunker) and No. 2 (for General Staff of the Red Army) of the Building of Metrostroi (Soviet subway construction company); to qualify the questions about the zoning of the city in the wartime; to cite new data about Bezymyanka district of the prewar time using comparative-historical, analytical and retrospective methods. The article introduces a new document material of the central archives of the Russian Federation into scientific discourse. It is proved that Kuibyshev was neither «alternate» nor «military» capital. It tasted the peak of its «capital city status» during 2–3 months while solving many issues of the All-Union scale and performing capital functions. The conclusion that the acceptance of the city services in the analyzed period was the rating of the city of Kuibyshev to the cities of republican subordination on 21st August 1943 is drawn.

Telemedicine technologies for transmitting digital information about the patient are presented and characterized in the practice of application at the prehospital stage for clarifying the diagnosis, correcting the measures taken, efficient logistics and routing. High diagnostic accuracy and the possibility of round-the-clock diagnostics anywhere significantly improves the quality of medical care provided.

The paper examines the process of evacuation of industrial facilities and civilian population to the territory of the Kemerovo region – Kuzbass during the Great Patriotic War. The author provides information on the number of evacuated enterprises, and also clarifies their locations before and after the relocation. The largest industrial facilities in Kuzbass are highlighted, which were created even before the start of the war and were industrial sites for the commissioning of equipment from arriving factories. The evacuation of the civilian population in most cases occurred in clear dependence on the relocation of industrial facilities. In this regard, the author raises question about the number of evacuated citizens, both in the region as a whole and in individual cities and districts. Based on these statistics, it gives the percentage of the number of evacuees to the total population. In addition, based on archival documents, the author pays attention to aspects related to the evacuation process: reception and accommodation, medical and consumer services, employment. Also, the work highlights the difficulties that evacuated citizens had to face, as well as ways to solve them.

Abstract In an emergency evacuation, the free evacuation of pedestrians can make the entire evacuation process slow and dangerous. To limit the free behavior of pedestrians and reduce the interaction between pedestrians, a reasonable layout of the guider can improve the efficiency and safety of evacuation. How to set the number, location, and exit allocation of guiders requires further investigation. In the current study, we transform the evacuation into a multi-objective optimization problem. A two-layer optimization framework is developed. In the upper level, the improved NSGA-II multi-objective algorithm is introduced to generate the favorable guider layout, and a chromosome fragment deletion operator is added to improve the optimization efficiency. In the lower layer, the agent movement simulation model is used to simulate the evacuation dynamic of crowd under the favorable guider layout. The variables of this multi-objective solution model in the upper layer are the number and location of the guiders. The evacuation time and agent movement cost are calculated by the lower layer simulation as the objective values of the solution sample, and guide the iterative search process to obtain more reasonable optimization results. The developed model is verified and then applied to a fictional scenario. The number, initial position and exit allocation of guiders are obtained by optimizing the iterative process. The results show that the near optimal solution can be applied in various visibility conditions, and the evacuation efficiency is much higher than that of unguided evacuation. This optimization framework can provide theoretical and methodological support for emergency evacuation planning.

International research attention on evacuation issues has increased significantly following the human and natural disasters at the turn of the century, such as 9/11, Hurricane Katrina, Cyclones Idai and Kenneth, the Black Saturday forest fires and tsunamis in Japan. The main problem concerning when a disaster can occur involves studying the risk reduction. Risk, following all the theoretical and experimental studies, is determined by the product of three components: occurrence, vulnerability and exposure. Vulnerability can be improved over time through major infrastructure actions, but absolute security cannot be achieved. When the event will occur with certainty, only exposure remains to reduce the risk to people before the effect hits them. Exposure can be improved, under fixed conditions of occurrence and vulnerability, by improving evacuation. The main problem in terms of evacuating the population from an area is the available transport system, which must be used to its fullest. So, if the system is well managed, the evacuation improves (shorter times), meaning the exposure is reduced, and therefore, the risk is reduced. A key factor in the analysis of transport systems under emergency conditions is the behavior of the user, and therefore, the study of demand. This work identifies the main research lines that are useful for studying demand under exposure-related risk conditions. The classification of demand models that simulate evacuation conditions in relation to the effect on the transportation system is summarized. The contribution proposes a model for updating choice in relation to emergency conditions and utility. The contribution of emerging ICTs to actualization is formally introduced into the models. Intelligent technologies make it possible to improve user decisions, reducing exposure and therefore risk. The proposed model moves within the two approaches of the literature: it is an inter-period dynamic model with the probability expressed within the discrete choice theory; furthermore, it is a sequential dynamic model with the probability dependent on the previous choices. The contribution presents an example of application of the model, developing a transition matrix considering the case of choice updating under two extreme conditions.

Staircase choice is one of the most critical factors leading to the difference in pedestrian flow and evacuation routes in buildings with multiple staircases. Neither the shortest path to the building exit nor the locally quickest path to the nearest staircase can represent the natural mode of evacuation path choices for an authentic evacuation simulation. Thus, a prediction-based approach is established to predict and simulate evacuation choices, which helps to address three key issues: (1) extracting evacuation data through a controlled experiment; (2) establishing a Logit model for staircase choice prediction based on experimental data; (3) developing a prediction-based cellular automaton model. The proposed approach has achieved the coupling between choice prediction and evacuation simulation. A comparison with Pathfinder software is conducted to reveal the superiority of the prediction-based CA model for simulating staircase choice.

The article presents an analysis of fire hazard of high-rise buildings and skyscrapers. The author notes a range of factors significantly impacting on the course of emergency rescue operations, including the difficulty of evacuating people from the burning buildings (e.g., due to the rapid movement of combustion products to the roof of the building, the duration of the descent down the stairs to evacuation exits, etc.), uncertainty of toxicity (the nature of gases formed during combustion, the synergism of their toxic effect, the determination of toxic dose), difficulties in rescuing people from the upper floors of the building and in the process of extinguishing a fire (due to the lack of necessary fire equipment), as well as the behavior of people caught in a fire in the building. The inadmissibility of using «risk-analysis» in the forensic practice is emphasized, since the correct initial data (linear and mass burning rates) for its calculation is unknown. The article is intended for fire experts of the forensic institutions of various departments, investigators of the Ministry of Emergency Situations and employees of engineering organizations.

Despite increasing wildfire severity and range, rapid development in the fire-prone Wildland–Urban Interface (WUI) has continued, and many neighborhoods are at risk of a constrained wildfire evacuation due to a high ratio of houses to community road-network exits. In Texas, Hays County is prone to fire, and rapid population growth has created a substantial WUI. Despite this, there is not sufficient research addressing neighborhood-level evacuation risks. The goal of this research, then, is to search Hays County for neighborhoods that face the highest combined risk of wildfire and potential evacuation difficulty. This research provides a limited use case wherein local decision-makers can quantify the combined risk of wildfire and constrained evacuation at the neighborhood scale by making use of standard spatial analysis techniques and publicly available datasets. The results show an alarming trend of low-egress neighborhoods in fire-prone areas within Hays County which carry the risk of a very difficult evacuation in cases when wildfire warning time is short. By using publicly available datasets and standard techniques, this research provides methods for local decision-makers across the state to identify these at-risk neighborhoods within their own jurisdictions which may aid in emergency planning and mitigation.

Despite increasing wildfire severity and range, rapid development in the fire-prone Wildland–Urban Interface (WUI) has continued, and many neighborhoods are at risk of a constrained wildfire evacuation due to a high ratio of houses to community road-network exits. In Texas, Hays County is prone to fire, and rapid population growth has created a substantial WUI. Despite this, there is not sufficient research addressing neighborhood-level evacuation risks. The goal of this research, then, is to search Hays County for neighborhoods that face the highest combined risk of wildfire and potential evacuation difficulty. This research provides a limited use case wherein local decision-makers can quantify the combined risk of wildfire and constrained evacuation at the neighborhood scale by making use of standard spatial analysis techniques and publicly available datasets. The results show an alarming trend of low-egress neighborhoods in fire-prone areas within Hays County which carry the risk of a very difficult evacuation in cases when wildfire warning time is short. By using publicly available datasets and standard techniques, this research provides methods for local decision-makers across the state to identify these at-risk neighborhoods within their own jurisdictions which may aid in emergency planning and mitigation. [ABSTRACT FROM AUTHOR]

Anthropogenic hazards are unrelenting threat to lives and property, with human irresponsibility emerging as a leading source of urban as well as industrial fires. The complexity of urban structures and crowded layouts make these kinds of fires more lethal. This paper presents an Artificial Intelligence (AI) based framework designed for smart buildings as a solution to the devastating obstacles caused by fire crises. Our system creates a 3D model of the building using floor plans and the A* algorithm for escape route identification. The proposed framework includes a YOLO-based smart monitoring system for the identification and counting of people caught in a fire, with the ability to distinguish between conscious and unconscious persons. The proposed system informs inhabitants in the case of a fire and directs them to the closest exit for a safe evacuation. Moreover, fire and rescue officials receive real-time information on affected persons, such as the number and location of adults and children who are conscious and unconscious. Perhaps most significantly, the suggested framework performs exceptionally well, scoring 96% for precision and 98% for recall in the detection of fire and humans. These findings highlight the effectiveness of the model in locating people within infrastructures affected by fire. The framework considerably outperforms the most advanced algorithms in terms of speed and efficiency for shortest path detection, greatly improving the ability of fire rescue teams to quickly find and aid residents who are trapped in a fire. [ABSTRACT FROM AUTHOR]

Wildfire impacts are increasing due to the multiplicative effect of several factors, including climate change, increased vulnerability in the wildland-urban interface, and impacts of management decisions. This has also led to an increase in evacuations due to the number of wildfires and people affected. This study collected information on behaviour during wildfire evacuation to fill critical research gaps in human behaviour and evacuation knowledge. Seven videos of residents' evacuations from the 2016 Fort McMurray fire were collected from public platforms. Their routes were analyzed, and notable behavioural events were recorded. The evacuees mainly used major roads before getting onto the highway (the only route available for vehicular egress). The notable behaviours observed included using opposite lanes and driving outside of marked roads to avoid congestion. Much of the observed behaviours appeared to be motivated by the surrounding traffic or fire behaviour, further supporting the need for further studies of evacuation. [ABSTRACT FROM AUTHOR]

Effective disaster management can help mitigate both human and financial damage. However, the absence of appropriate disaster preparedness and management efforts can increase the vulnerability of international tourists to natural disasters. International tourists differ from residents and local tourists in various ways, including limited knowledge of disasters and disaster responses, use of different languages, limited access to signs, and shelter locations and evacuation routes. This study developed an agent-based evacuation model to determine the differences in evacuation behaviors among international tourists, residents, and local tourists during a tsunami. Further, it clarified the impact of both soft and hard countermeasures such as information provision and shelter capacity expansion. Our case study was conducted in the Minato Bay area in Osaka, Japan. The simulation results revealed disparities in the evacuation behaviors between international tourists and residents in the arrival times at shelters. The enhanced sign accessibility and provision of signs in multiple languages significantly reduced the arrival time of international tourists at shelters. Consequently, it is necessary to improve disaster management plans that ensure information provision in multiple languages and the establishment of temporary shelters near tourism spots to support international tourists during disaster evacuation. • Disparities exist in the evacuation behaviors of international tourists and residents. • International tourists following other evacuees take more time to reach shelters. • Enhanced sign accessibility reduces international tourists' arrival times. • Information provision in multiple languages reduces international tourists' arrival times. [ABSTRACT FROM AUTHOR]

In January 1945, the Red Army began its Vistula-Oder offensive forcing the German army to abandon many territories that it occupied west of the Vistula River. The offensive also resulted in the westward evacuation of thousands of ethnic Germans, including Mennonites, seeking refuge in the shrinking Third Reich. This paper examines the evacuation strategies and experiences of Mennonites from Deutsch Wymyschle and Gąbin, Poland during this chaotic time. It also investigates the Red Army's brutal treatment of Mennonites following their capture and during the journey back to their villages in Poland. Finally, the paper discusses the way in which Nazi authorities exploited this mass evacuation not only for their own administrative and military purposes, but also to slow down the advancing Red Army. [ABSTRACT FROM AUTHOR]

This article aims to cover a little-known chapter in the history of World War II. In the course of the brutal German occupation rule, not only forced labourers but also scientists were deported from Ukraine to Germany as war booty and forced to work for the Nazi regime. One example of this is mathematicians who arrived in the village of Ummendorf in the Upper Swabia region of southern Germany in the summer of 1943. They were specialists in aerodynamic calculations who had originally come from the Ukrainian Physical-Technical Institute (UPTI) in Kharkiv. In Ummendorf, they came across German colleagues who had been brought there from the city of Aachen, which had been hit by air raids and were deployed there by the Ministry of Aviation for research relevant to the war effort. The researchers from occupied Ukraine also subsequently worked for the Reichsluftwaffe and co-operated with the Göttingen Aerodynamic Research Institute. The research methodology is based on the principle of critical historicisation, which is committed to the principle of the greatest possible objectivity and is based on the analysis of a wide range of sources from German archives and the evaluation of relevant, predominantly Western, research literature. In summary, various conclusions can be drawn from the events described about both the scientific policy of the Nazi state and the social and socio-cultural dynamics of the time. It shows not only the interest of the Nazi regime in the expertise of specialists from occupied Ukraine and the reputation that research work at Ukrainian scientific institutes enjoyed in the racist Nazi state but also the consequences of the everyday coexistence of the scientists with the village population and the difficult situation for the former employees of the Kharkiv’s UPTI after the end of the World War II. [ABSTRACT FROM AUTHOR]

International research attention on evacuation issues has increased significantly following the human and natural disasters at the turn of the century, such as 9/11, Hurricane Katrina, Cyclones Idai and Kenneth, the Black Saturday forest fires and tsunamis in Japan. The main problem concerning when a disaster can occur involves studying the risk reduction. Risk, following all the theoretical and experimental studies, is determined by the product of three components: occurrence, vulnerability and exposure. Vulnerability can be improved over time through major infrastructure actions, but absolute security cannot be achieved. When the event will occur with certainty, only exposure remains to reduce the risk to people before the effect hits them. Exposure can be improved, under fixed conditions of occurrence and vulnerability, by improving evacuation. The main problem in terms of evacuating the population from an area is the available transport system, which must be used to its fullest. So, if the system is well managed, the evacuation improves (shorter times), meaning the exposure is reduced, and therefore, the risk is reduced. A key factor in the analysis of transport systems under emergency conditions is the behavior of the user, and therefore, the study of demand. This work identifies the main research lines that are useful for studying demand under exposure-related risk conditions. The classification of demand models that simulate evacuation conditions in relation to the effect on the transportation system is summarized. The contribution proposes a model for updating choice in relation to emergency conditions and utility. The contribution of emerging ICTs to actualization is formally introduced into the models. Intelligent technologies make it possible to improve user decisions, reducing exposure and therefore risk. The proposed model moves within the two approaches of the literature: it is an inter-period dynamic model with the probability expressed within the discrete choice theory; furthermore, it is a sequential dynamic model with the probability dependent on the previous choices. The contribution presents an example of application of the model, developing a transition matrix considering the case of choice updating under two extreme conditions. [ABSTRACT FROM AUTHOR]

On 1 January 2024, a large earthquake occurred in Japan's Noto region. Many buildings collapsed as a result of violent shaking. Electricity and water supplies were cut off, and communications were disrupted. On 5 January, four days after the earthquake, we visited Noto and conducted disaster-relief activities. This report integrates and discusses the results of the site visits, information broadcasts by public institutions, and previous research. Evacuation centers lacked water and proper sanitation, leading to health issues, including infectious diseases. Disaster Medical Assistance Teams (DMAT) were delayed in implementing infection control measures. Isolated evacuation centers faced communication and supply challenges. Infrastructure restoration, power supply, and toilet facilities at evacuation centers were delayed because of geographical challenges. It is important to have a team that can determine and carry out the necessary activities on site, even without instructions from the DMAT. It is believed to be effective to decide in advance how volunteer teams and the private sector will conduct their activities, assuming that they will be unable to contact public institutions during a disaster. In large-scale disasters, evacuees must operate evacuation centers autonomously. To achieve this, it is necessary for residents to regularly come together as a community. Systematically recording and accumulating these experiences will contribute to improved disaster prevention and mitigation planning. We hope that the experiences we obtained through the abovementioned disaster will be useful for preparing for future disasters. [ABSTRACT FROM AUTHOR]

This paper investigates the possibilities of using an agent-based evacuation model to analyse the formation of queues at the exits of enclosed spaces and the evacuation process of people. The aim is to investigate how the density of people in a crowd affects the safe movement of people and how the width, number, and location of exits affect evacuation time. The analysis was carried out using the Pathfinder evacuation model, which provides two modes to simulate the movement of people: steering and SFPE. An enclosed space of 20 m × 30 m was investigated. First, the differences between the modes of the evacuation model to simulate the movement of people were compared. Then, the steering mode with limited door flow was set and the effect of the width, number, and location of the exits with a total width of 4 m on the evacuation time was investigated. The results of this study highlight differences in the simulation of the movement of people according to the different modes and provide valuable information for the design of safe escape routes. Proper design of escape routes can prevent an adverse situation that could arise when evacuating a large number of people. [ABSTRACT FROM AUTHOR]

Simple Summary: The 2017 Edgecumbe flood in New Zealand triggered the largest companion animal rescue operation in the nation's history, highlighting significant gaps in disaster preparedness for animals. This study aimed to explore the experiences of six first responders from various agencies involved in the rescue efforts. The main challenges identified included the lack of logistical planning during the initial rescue phase, the need for proper animal identification and tracking systems, and the difficulties in decontaminating and providing long-term care for rescued animals. Health and safety issues for responders were also significant, with many facing hazardous conditions and emotional stress. This study concluded that comprehensive collaborative emergency response planning is essential to address the needs of both humans and animals. The findings underscore the importance of including animals in disaster preparedness plans and ensuring that responders are adequately trained and supported. These insights are valuable for improving future emergency responses, promoting community resilience, and ensuring the welfare of animals and humans during disasters. The 2017 Edgecumbe flood in New Zealand necessitated the rescue of over 1000 animals, making it the largest companion animal rescue operation in the nation's history at the time. This qualitative study explores the experiences and perspectives of six first responders from various agencies involved in the animal rescue efforts. Through semi-structured interviews, this study identified several key themes, including challenges during the rescue phase, post-rescue issues, the impact on the human–animal relationship and wellbeing, and the health and safety of responders. The rescue phase was characterised by difficulties in evacuating and rescuing animals, the influence of the socio-zoological scale on rescue prioritisation, issues with feeding animals in place, and the diversity of species requiring rescue. Post-rescue challenges included animal identification and tracking, decontamination, management of deceased animals, and long-term impacts on animals and owners. This study also highlighted the interconnectedness of human and animal welfare during the disaster, as well as the health and safety risks faced by responders. The findings underscore the need for comprehensive collaborative emergency response planning that addresses the needs of both humans and animals, as well as the importance of ongoing efforts to build resilience and preparedness in communities. Lessons learned from the Edgecumbe flood can inform future policy, planning, and practice to enhance the effectiveness and compassion of animal-inclusive emergency management. [ABSTRACT FROM AUTHOR]

Disaster evacuation increases the risk of becoming overweight or obese owing to lifestyle changes and psychosocial factors. This study evaluated the effect of evacuation on becoming overweight during a 7-year follow-up among residents of Fukushima Prefecture during the Great East Japan Earthquake. This was a prospective cohort study. We analysed data collected from 18,977 non-overweight Japanese participants who completed the 'Comprehensive Health Checkup Program' and 'Mental Health and Lifestyle Survey', as part of the Fukushima Health Management Survey, between July 2011 and November 2012. An evacuation was defined as the moving out of residents of municipalities designated as an evacuation zone by the government or having a self-reported experience of moving into shelters or temporary housing. Follow-up examinations were conducted in March 2018 to identify patients who became overweight. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated using a Cox proportional hazards regression model. Among 15,875 participants (6091 men and 9784 women; mean age 63.0 ± 11.1 years) who received follow-up examination (mean follow-up, 4.29 years), 2042 (856 men and 1186 women) became overweight. Age-, baseline body mass index-, lifestyle-, and psychosocial status–adjusted HRs (95% CIs) for becoming overweight after evacuation were 1.44 (1.24–1.66) for men and 1.66 (1.47–1.89) for women. Evacuation was associated with the risk of becoming overweight 7 years after the disaster. Thus, maintaining physical activity, healthy diet, and sleep quality and removing barriers to healthy behaviour caused by disasters, including anxiety concerning radiation, may prevent this health risk among evacuees. [ABSTRACT FROM AUTHOR]

Counter-terrorism measures and preparedness play a critical role in securing mass gatherings, soft targets, and critical infrastructures within urban environments. This paper introduces a comprehensive Decision Support System developed as part of the S4AllCitites project, designed to seamlessly integrate with existing legacy systems in Smart Cities. The system encompasses urban pedestrian and vehicular evacuation, incorporating predictive models to anticipate the progression of incendiary and mass shooting attacks, alongside a probabilistic model for threat assessment in the case of improvised explosive devices. A notable achievement of this research is the successful implementation and deployment of the system in operational environments through pilot studies. It empowers public and private security operators with real time decision support capabilities during both prevention and intervention stages of potential attacks. The decision support information provided encompasses various aspects, including optimal evacuation strategies, estimated egress times, pedestrian movement profiles, probability assessments, and the potential impact of different terrorist threats in terms of casualties. Additionally, the system offers real-time insights into the status of the traffic network under normal and unusual conditions, enabling efficient emergency management throughout its progression. This includes the ability to identify optimal intervention routes and assess the impact of anomalous traffic resulting from evacuations. [ABSTRACT FROM AUTHOR]

Background. The article examines the issue of evacuation of the civilian popula-tion from Moscow and the Moscow region, the region with the largest number of arrivals to the Mari ASSR during the Great Patriotic War. In the course of the study, attention is drawn to the problems of a domestic nature faced by the evacuees, as well as to the organi-zation of reception, accommodation and further assistance from the republican authorities. The purpose of the work is to study the process of evacuation from Moscow and region to the Mari ASSR, the peculiarities of everyday life and social adaptation. Materials and methods. The sources on this topic are mainly documents identified in the State Archive of the Republic of Mari El. The systematic approach reflects the complexity and connection of the evacuation process with other events of the period, their influence on each other. The principles of historicism and objectivity contribute to the correct analysis and understanding of the phenomenon under study. Results. Strengths and weaknesses in working with evacu-ees were identified. The strengths include a good organization for the reception of refugees, a high degree of employment, and constant attention to improving work with the evacuated population. The weak ones include the material supply of both things and products, inter-ruptions in the work of institutions, and often the unpreparedness of local residents to re-ceive evacuees. Conclusions. Evacuation to the Mari ASSR during the Great Patriotic War was important for saving lives and protecting the population. Of course, this was accompa-nied by a significant number of difficulties, largely due to objective factors of wartime. Moreo-ver, the evacuation contributed to the replenishment of the labor reserve, primarily in industry and agriculture, which also had a certain positive impact on the economy of the region.

IntroductionRelocation after a disaster often has negative health effects on vulnerable people, particularly older adults. However, little is known about the number of repeated evacuations and relocations after disasters among those experienced disaster-related deaths. This case series aimed to summarize the secondary problems and mortality risks in patients involved in relocation after disasters.MethodsWe analyzed and summarized the data on 520 disaster-related deaths in Minamisoma City, a municipality near the Fukushima Daiichi Nuclear Power Plant, focusing on the number of relocations. Herein, we describe the cases of three individuals over 80 years old, who died after eight or more relocations, which were certified as disaster-related deaths.ResultsWe discuss following three cases, which are (1) a female patient in her 90s who had a stroke and was completely disabled, (2) a female patient in her 80s whose cancer was detected later due to her failing to see her family doctor, and (3) a male patient in his 80s whose regular postoperative treatment was disrupted following cancer recurrence.DiscussionOur findings indicate that evacuation led to the worsening of chronic diseases and eventually to post-disaster death. Prolonged wide-area evacuation and repeated relocation likely interrupted the continuum of care and led to the failure of adequate care provision. To reduce the loss of human life, it is necessary to review the number of wide-area evacuations and relocations over the medium to long term after large-scale disasters, including nuclear disasters, which may occur in the future. Simultaneously, it is important to establish a medical system at the evacuation site so that disaster victims can continue to receive medical care even after evacuation or relocation.