Distribution Of Casualties Research Articles

Exploring variations in flood events and casualties over Yamuna River basin, India

ABSTRACT The current study seeks to investigate the temporal and spatial distribution of flood events and casualties in the Yamuna River basin from 1978 to 2014. The data were compiled from the published reports on disastrous weather events and analyzed with simple quantitative methods (sums, averages, and percentages). The analysis revealed the occurrence of a total of 1886 flood events, which resulted in 5481 casualties (148 per year). The years 1995, 2003, 1993, and 1996 were observed as the most devastating years, contributing about 30 percent of the total flood events, while 1978, 1980, 1981, 1995, 2006, and 2013 were the deadliest years in terms of casualties (47 percent). The largest number of flood events and casualties were recorded during June–September months. Considering the event/casualty density and rates, the states of Himachal Pradesh and Uttarakhand experienced the highest event density (0.036 and 0.091) and casualty rates (2.1 and 1.9 persons). These findings will help in identifying and demarcating the worst flood-affected areas over the Yamuna River basin, which can subsequently help in reducing the flood risk and human casualties in these regions after initiating suitable flood mitigation measures.

Integrated optimization of facility location, casualty allocation and medical staff planning for post-disaster emergency response

PurposeDisaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.Design/methodology/approachThis study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.FindingsUsing a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.Originality/valueThis study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

Clustering and pedestrian crashes prediction modelling: Amman case

Pedestrian casualties are a severe domestic as well as international problem. This study analyses the spatial distribution of pedestrian casualties to define contributory factors and delineate the means for their prediction. Three years of crash data were collected along with other factors and analysed using kernel density estimation (KDE), spatial autocorrelation (Moran’s I), cluster K-Means, spatial regression, and general linear regressions (GLM). Kernel density estimate defines a cluster of pedestrian deaths within 1250 meters. According to Moran’s I, 17/22 attributes about casualties, road networks, demographics, and land use have positive values, indicating similar importance clustering. The spatial pattern of pedestrian casualties is random and insignificant and does not change with time. Casualties are negatively related to the surrounding attributes, indicating a tendency towards dispersion. A K-Means analysis of multiple variables revealed that when variables included in the clustering were higher, the variance explanation percentage was lower. In the multi-variable GLM assuming Poisson distribution, the road network length alone or with the house permits combined were the best predictors of casualties. Classic regressions were not significantly enhanced by spatial dimension, and none of the autoregressive coefficients were significant. The predictions from the Poisson-based GLM model are similar to the classic regressions.

Disaster Management Simulation–A Novel Virtual Exercise

Introduction:Disaster management and emergency preparedness relies on the collaboration, communication, and expertise of a multidisciplinary team. Skills in preparation, communication, and management of disasters are core competencies of an emergency physician. To learn the principles of disaster management, simulations are critical as mass casualty/rapid surge events seldom occur. The COVID-19 pandemic resulted in the cancellation of in-person events. In response to these restrictions, the University of Toronto, EM Program developed a successful virtual interprofessional mass casualty simulation.Method:The novel online simulation event was piloted in 2021 and ran for three-hours. The exercise focused on developing soft skills (e.g., communication, team-work, and debriefing) and hard skills (e.g., triage, casualty distribution, and activation of plans). Groups were composed of members of each post-graduate year to facilitate near-peer learning. A total of six groups were formed: Adult, Children, Community Hospitals, EMS, Government, and Media. Each Team used multiple communication tools (i.e., Whatsapp groups, Zoom breakout rooms, Shared Google Documents) to swiftly pivot and manage a mass casualty event. Post-exercise debriefing and anonymous evaluations were gathered.Results:A total of 28-residents (nine PGY1, ten PGY2, and eight PGY3 learners) and 11-staff observers participated (25-respondents). Nineteen participants rated the simulation exercise as excellent and six as “very good”. Twenty participants rated the workshop as “very useful” and five as “useful”. Positive feedback centered around content applicability, exercise creativity, level of engagement, and learning value. Constructive feedback included the need for more pre-exercise orientation time, increasing disaster management time, and inviting allied-health staff.Conclusion:There is a clear need for EM residents to learn and develop skills related to disaster management and emergency preparedness. This exercise showed that disaster management and emergency preparedness competencies can be learned in a virtual format. This virtual format has encouraged its continuation and further inspired the curation of a four-year program.

Fire in the Hole: Modeling the Thermal Effects of a Nuclear Detonation in an Urban Environment

Introduction:In general, models for thermal effects of nuclear weapons are not as well developed as models for blast and radiation effects, yet casualties resulting from fires and burns in a nuclear detonation would significantly impact civil defense and emergency healthcare. Previous studies have conducted in-depth analysis of the various atmospheric conditions that affect the thermal radiation transmissivity. However, such models have yet to consider the role that buildings play in the urban environment to estimate the casualties from the thermal effect more accurately.Method:A three-dimensional model of the area within a three-mile radius of the detonation site in Atlanta, Georgia, USA was created in Blender. To represent the thermal energy resulting from a 15 kiloton, near-surface burst, a point light was created with a power of 96,725 gigawatts and a radius of 81 meters. Using the Cycles render engine, the resulting light/shadow was orthographically captured directly above the scene.Results:The rendered model demonstrated the attenuating effects of the built, urban environment. Nearly half (46.82%) of the pixels in the resulting raster were black, or regions that were not exposed to any thermal energy. Slightly less than a quarter (22.32%) of the pixels were white or light gray, or regions that received mostly direct thermal energy. The remaining regions (30.86% of the pixels) were dark gray, or regions that were initially in shadow from the thermal pulse but received thermal energy via reflection from nearby buildings.Conclusion:As the thermal pulse travels at the speed of light, it arrives at a location before the blast wave. As such, the built urban environment offers protection from the thermal energy released during a nuclear detonation. Future studies that incorporate this thermal model may more accurately determine the quantity and geospatial distribution of burn casualties in the aftermath of a nuclear detonation.

Demand-supply balance of disaster medical care in Osaka City based on damage estimation for a Nankai Trough megathrust earthquake: A geographic information system-based analysis.

Studies have not fully examined whether the medical care system would be able to manage the high number of casualties due to a Nankai Trough earthquake, whose probability of recurrence in the next 30 years is ~70%. This study assessed the demand-supply balance of the disaster medical care system in Osaka city by integrating the data on damage estimation and disaster coping hospitals using a geographic information system. We obtained data on the distribution of casualties in two cases, high and low rates of evacuation from the tsunami, and available beds in Osaka city calculated from operating data of each disaster coping hospital. We expanded these data on a geographic information system and investigated the balance of medical care. The total number of available beds in the disaster medical care facilities was 5,559, and the shortage with evacuation rates being either low or high, would be 47,631 and 1,487, respectively. With a low evacuation rate, bed shortage is a common occurrence in coastal areas. With a high evacuation rate, bed shortage decreases, and problems with medical care arise in the eastern area of Osaka city. In the case of a low evacuation rate, greater bed shortage was found along the coast of Osaka Bay where the probabilities of flooding are high. In the case of a high evacuation rate, however, the number of casualties was much lower. A shortage of medical care did not occur along the coast, but in the eastern part of Osaka city.

Estimation of the influence of protective behaviour on expected injuries in transport accidents with hazardous materials

The release of hazardous materials due to transport accidents can have major health consequences for bystanders. The number of casualties will partly be determined by their protective behaviour.This study describes a three-step approach to predict health consequences of protective behaviour (for example, hiding or escaping) of bystanders in the first minutes of a transport accident with hazardous material. First, a discrete choice experiment (DCE) was used to predict protective behaviour. Second, a gas dispersion model (SeReMo) was used to estimate the distribution of casualties for different protective behaviours. Third, results of the DCE and SeReMo were combined to estimate the distribution of casualties in the population-at-risk. This approach was applied to a hypothetical marine accident with different hazardous material scenarios on a large waterway in a close vicinity of a beach/quay with bystanders.An important finding of our study was that in general a short reaction time and escaping in cross-wind direction, as protective behaviours, are of vital importance to reduce the number of casualties. A scenario with a short reaction time and a visible cloud towards the beach/quay resulted in a protective behaviour with the largest reduction of casualties.A dynamic risk assessment approach considering that people threatened by hazardous material are not ‘stationary observers’, but will exhibit protective behaviour, and a risk assessment that takes into account empirical information on expected protective behaviour will present a more realistic estimate of the number and severity of casualties when a large transport accident with hazardous materials would occur.

The role of the socio-economic context in the spread of the first wave of COVID-19 in the Marche Region (central Italy)

The first wave of COVID-19 arrived in Italy in February 2020 severely hitting the northern regions and delineating sharp differences across the country, from North to South. The Marche Region (central Italy) is a good example of such uneven distribution of contagion and casualties. This paper discusses the spatial diffusion of COVID-19 during the spring of 2020 in the five provinces of Marche and discusses it by means of descriptive and quantitative analysis of local socio-economic variables. Results show that the high impact of COVID-19 in Pesaro and Urbino, the northernmost province of Marche, might be reasonably attributable to higher mobility of local residents, especially northbound. Similarly, the larger contagion among the elderly in the center and norther provinces, is possibly due to a high number of hospices and seniors' residential facilities. Finally, the North-to-South diffusion of the virus can be explained by the Region's transportation infrastructures and urban layout along the coastal area.

A method for detailed determination of hospital surge capacity: a prerequisite for optimal preparedness for mass-casualty incidents

BackgroundDefined goals for hospitals’ ability to handle mass-casualty incidents (MCI) are a prerequisite for optimal planning as well as training, and also as base for quality assurance and improvement. This requires methods to test individual hospitals in sufficient detail to numerically determine surge capacity for different components of the hospitals. Few such methods have so far been available. The aim of the present study was with the use of a simulation model well proven and validated for training to determine capacity-limiting factors in a number of hospitals, identify how these factors were related to each other and also possible measures for improvement of capacity.Materials and methodsAs simulation tool was used the MACSIM® system, since many years used for training in the international MRMI courses and also successfully used in a pilot study of surge capacity in a major hospital. This study included 6 tests in three different hospitals, in some before and after re-organisation, and in some both during office- and non-office hours.ResultsThe primary capacity-limiting factor in all hospitals was the capacity to handle severely injured patients (major trauma) in the emergency department. The load of such patients followed in all the tests a characteristic pattern with “peaks” corresponding to ambulances return after re-loading. Already the first peak exceeded the hospitals capacity for major trauma, and the following peaks caused waiting times for such patients leading to preventable mortality according to the patient—data provided by the system. This emphasises the need of an immediate and efficient coordination of the distribution of casualties between hospitals. The load on surgery came in all tests later, permitting either clearing of occupied theatres (office hours) or mobilising staff (non-office hours) sufficient for all casualties requiring immediate surgery. The final capacity-limiting factors in all tests was the access to intensive care, which also limited the capacity for surgery. On a scale 1–10, participating staff evaluated the accuracy of the methodology for test of surge capacity to MD 8 (IQR 2), for improvement of disaster plans to MD 9 (IQR 2) and for simultaneous training to MD 9 (IQR 3).ConclusionsWith a simulation system including patient data with a sufficient degree of detail, it was possible to identify and also numerically determine the critical capacity-limiting factors in the different phases of the hospital response to MCI, to serve as a base for planning, training, quality control and also necessary improvement to rise surge capacity of the individual hospital.

An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)

Subway transportation is one of the most prevalent urban transportation methods globally. Millions of people around the globe use this medium as their mode of transportation daily. However, subway stations may be highly prone to fire, smoke, or explosion accidents. The safety of people using subway stations demands a robust and practical framework to assess fire hazards and risks. This study provides a methodology to assess fire risk at a subway station. This study integrates fault tree analysis (FTA) and fuzzy analysis to conduct a comprehensive fire risk assessment. An integrated numerical model of fire temperature and fatality rate was developed using probit correlations for various fire exposure scenarios. The fire dynamics simulator (FDS) provides the probability distribution of casualties caused by fire. To demonstrate the operationalization of the model, Line 1 of the Harbin Metro, located in China, is used as a case study. Results show a probability of 42% of having fire risk in the subway station. Results reveal the highest fatality rate is 6.2% when evacuation time exceeds 200 s. The research helps us to understand the spread of smoke and temperature distribution due to a fire in a subway station. This study is helpful for fire protection engineers, safety managers, and local fire departments to develop a contingency plan to deal with fire in a subway station.

Evacuation simulation of multi-story buildings during earthquakes based on improved cellular automata model

s The evacuation process in buildings provides an efficient method for engineers to evaluate the rationality of the architectural design and structural design scheme. The simulation of the authentic evacuation process is conducive to accurately evaluate the casualties of buildings under earthquake. The economic loss estimation in the performance-based seismic design method can then be implemented. This study improves the traditional cellular automata model in order to simulate the crowd evacuation process in buildings under earthquake. The modified model simulates the attraction of exits to crowds, herd behavior of crowds, avoidance behavior for obstacles, decision-making behavior for paths/exits selection, and conflict between pedestrians in the evacuation process. Based on the variation coefficient of evacuation time and video which records authentic evacuation under earthquake, the influence coefficients of each factors are determined. In addition, the modified cellular automata model uses the refined cellular space to describe the geometric dimensions of the evacuation environments and obstacles, and therefore it improves the accuracy of the evacuation model. The explicit finite element method is used to simulate the seismic damage process of structural and non-structural components. The judgment criterion of casualties which combines the finite element model with the evacuation model, is proposed. The number and distribution of casualties are predicted based on the criteria. The prediction method for casualties helps the architects to optimize the size and layout of the building components. In the structural design stage, identifying areas with high population density or high casualties is conducive to optimize the structural design scheme, and provide a basis for the formulation of a post-earthquake rescue plan. Finally, a seven-story official building with reinforced concrete frame structure located in Dujiangyan City, Sichuan Province, China is considered as example to verify the rationality and applicability of the proposed method.

The 1620 and 1644 Earthquakes in Alcoy and the Eastern Region of Spain

Abstract The 2 December 1620 earthquake, which caused considerable damage to the town of Alcoy in eastern Spain, and the seismic sequence of June 1644 in the region from Alcoy to the coast of the Mediterranean Sea are studied using contemporary sources. Focal parameters are determined for the 1620 shock and the three mainshocks of the 1644 sequence on 15, 19, and 26 June. The distribution of damage and casualties from the 1620 earthquake in Alcoy leads to the assignment of maximum intensities of VIII–IX. A solution is presented for problems concerning dates, locations, and sizes of the three largest shocks of the 1644 sequence given in previous catalogs and studies.

Characterization and management of human-wildlife conflicts in mid-hills outside protected areas of Gandaki province, Nepal.

With the intent to better management human wildlife conflict (HWC) and wildlife conservation in mid-hills outside protected areas of Gandaki province, Nepal, we analyzed the patterns and drivers of HWC. Using data collected from literature, government records and questionnaire survey, we investigated temporal, seasonal and spatial distribution of human casualties caused by wildlife attacks. We also appraised the perception of local people towards wildlife conservation. We have recorded 77 cases (69 human injuries and 8 mortalities) during the period of nine year between 2011 and 2019. The number of wildlife attacks increased over this period. Wildlife attacks were more frequent in winter with 50% (42) of attacks occurred between September and December. Common leopard (Panthera pardus) and Himalayan black bear (Ursus thibetanus laniger) were the major species involved in these conflicts. Common leopard was the most feared species that causes highest number of human mortalities (87%, n = 67); the most severe type of HWC outcome. Forty-eight percent (n = 37) attacks were reported at human settlement areas followed by 27% attacks in agriculture land (n = 21) and 24% (n = 19) in forest. Generalized linear model analysis on spatial variables showed that the probability of human attacks increases with decreasing elevation (β = -0.0021, Z = -1.762, p = 0.078) and distance from the forest (β = -0.608, Z = -0.789, p = 0.429). We recommend to decrease habitat degradation / fragmentation, carry out habitat management program within forest to increase prey availability to decrease the wildlife invasion into human settlement area, and decrease dependency of people on forest resources by providing alternative livelihood opportunities. Simplified relief fund distribution mechanism at local level also helps alleviate the impact of HWC. The knowledge obtained by this study and management measures are important for better human-wildlife co-existence.

Assessment and determination of earthquake casualty gathering area based on building damage state and spatial characteristics analysis

Timely determination of the spatial distribution of post-earthquake relief forces and appropriate levels of response is a daunting task. This paper proposes a method based on building damage state and spatial characteristics analysis to assess the hotspot distribution of earthquake casualties and determine the dangerous gathering area. The method comprises three steps: (1) use the basic information of the buildings in the study area to calculate the building damage state and build the relationship with the casualties; (2) mesh the research area and establish the mapping relationship with the casualties caused by the building damage; (3) use grid data for spatial autocorrelation analysis (Moran's I) and hotspot analysis (Getis-Ord Gi*) to comprehensively assess the casualty cluster area. The feasibility of the proposed method was validated using the seismic damages of Longtoushan Town in the 2014 Ludian earthquake of China. The damage state of buildings and the number of casualties evaluated by this method coincide quite well with the actual earthquake results, and the casualty concentration area is determined. This method quantifies the degree of spatial risk aggregation of casualties and provides scientific guidance for disaster prevention planning and rescue.

Blunting Barbarossa’s Spear: Analyzing Army Group Center’s Officer Losses During the Campaign’s First Half

ABSTRACT This study examines officer losses during the first three months of Operation Barbarossa. It uses original, never-published German officer casualty data extracted and statistically analyzed from 13 by-name reports prepared by the Army Group Center Adjutant for Officer Personnel (IIa) during the summer of 1941. The list, comprising 7,644 names, proposes a periodization of the first phase of Operation Barbarossa in the Army Group Center zone of operations and presents an innovative perspective that uses the rise and fall of officer casualties as a one-of-a-kind measure of combat intensity. In other words, periods of differing casualty rates are seen as discrete operational phases when equated to neighboring intervals. To make the losses comparable across time, the article proposes the concept of division-days, which, in a manner similar to man-hours, records effective activity of these units in daily intervals. The casualty rate compared to total number of division-days is a measure of intensity. The analysis indicates that although there are three operational periods, two later phases see higher odds for officer losses, indicating intensified combat. In addition, the article considers several under-studied aspects of operational military history. First, it analyzes the distribution of casualties across divisions as a function of their posture (attack, defense, movement, reserve). The article further reveals that battle posture does not always follow the precept that ‘movement is the best defense’. In fact, overall analysis shows that units maneuvering (attack and move) were more likely to lose officers than those stationary (defend and reserve). Overall, the article is a first attempt to judge the nature and intensity of Barbarossa as a function of complex, over-time data, broken down by types of unit and posture, revealing how dear the officer casualty toll was for the Germans, setting the tone for a long and ultimately unwinnable war.

Response of Fully Prefabricated Subway Stations Subjected to Internal Blast Loading

A new kind of fully prefabricated subway station is developed in Changchun, China. This study investigates the failure mechanisms of these stations subjected to medium internal blast loading. A series of numerical simulations are carried out using the finite element program LS-DYNA. From the results, the damage and failure of the station are progressive and occur when the main event of blast loading is over. The distribution of casualties is presented in the subway station. Results show that the joints of the fully prefabricated stations can help reduce the damage of the underground stations.

전쟁에서 발생하는 전투의 규모와 빈도 관계에 적용되는 멱함수 분포에 대한 연구

In this research, we discuss the relationship between the severity and frequency of battle in order to analyze pattern of battles in modern warfare. Though previous studies found a particular pattern, i.e., a power-law distribution, in the casualty of armed conflict including interstate wars, intrastate wars, and terror attacks, the studies have not sufficiently explored this pattern for battles in war. Therefore, this research studies whether this pattern appears in battles occurred in an individual war, specifically the Korean War and the Vietnam War, based on the casualty data of battle. As a result, it is confirmed that the relationship between the severity and frequency of battle in war follows a power-law distribution. This phenomenon implies that the power-law distribution of battle casualties in war a scale-free pattern, which emerges through interaction among the components of system. Finally, the power-law-based analysis method for battle severity in war presented in this research can be used as a systematic approach to study the scale, frequency and timing of battle in war.

The Impact of Autonomous Ships on Safety at Sea – A Statistical Analysis

• If autonomous ships shall improve safety, focus should be on general cargo ships. • Making very large ships autonomous only has a minor effect on safety at sea. • Removing crew has a much larger effect on safety than autonomous navigation. The advent of autonomous ships that are unmanned or low-manned will reduce the number of people at risk at sea. Even when autonomous navigation does not reduce the number of accidents, this means that safety at sea will increase. In fact, increased safety is one of the primary perceived drivers for autonomous shipping, although this safety increase has not yet been quantified in academic literature. In this article a statistical analysis is performed to determine the distribution of human casualties and lost ships over accident types, ship types and ship sizes. Subsequently, based on several scenarios for the implementation of autonomous ships, a quantification of the estimated reduction in loss of life and loss of ships is provided. It is concluded that the implementation of autonomy on small cargo ships with a length below 120 m will have the largest safety benefit, since these ships account for the majority recorded ship losses and lives lost.

Human Consequences of Multiple Nuclear Detonations in New Delhi (India): Interdisciplinary Requirements in Triage Management.

The human casualties from simulated nuclear detonation scenarios in New Delhi, India are analyzed, with a focus on the distribution of casualties in urban environments and the theoretical application of a nuclear-specific triage system with significant innovation in interdisciplinary disaster management applicable generally to urban nuclear detonation medical response. Model estimates of nuclear war casualties employed ESRI’s ArcGIS 9.3, blast and prompt radiation were calculated using the Defense Nuclear Agency’s WE program, and fallout radiation was calculated using the Defense Threat Reduction Agency’s (DTRA’s) Hazard Prediction and Assessment Capability (HPAC) V404SP4, as well as custom GIS and database software applications. ESRI ArcGISTM programs were used to calculate affected populations from the Oak Ridge National Laboratory’s LandScanTM 2007 Global Population Dataset for areas affected by thermal, blast and radiation data. Trauma, thermal burn, and radiation casualties were thus estimated on a geographic basis for New Delhi, India for single and multiple (six) 25 kt detonations and a single 1 mt (1000 kt) detonation. Major issues related to the emergency management of a nuclear incident are discussed with specific recommendations for improvement. The consequences for health management of thermal burn and radiation patients is the worst, as burn patients require enormous resources to treat, and there will be little to no familiarity with the treatment of radiation victims. Of particular importance is the interdisciplinary cooperation necessary for such a large-scale emergency response event, which would be exemplified by efforts such as the application of a Nuclear Global Health Workforce.

Unifying casualty distributions within and across conflicts

The distribution of whole war sizes and the distribution of event sizes within individual wars, can both be well approximated by power laws where size is measured by the number of fatalities. However the power-law exponent value for whole wars has a substantially smaller magnitude – and hence a flatter distribution – than for individual wars. We provide detailed numerical evidence that confirms that these numerically different power-law exponent values are interrelated in a simple way by the effect of aggregating fatalities from individual events within wars to whole wars. We offer intuition for this finding and hence strengthen the case for a unified description and understanding of human conflict across scales.