Emergency Response Capability Research Articles

Spatial Accessibility Assessment of Emergency Response of Urban Public Services in the Context of Pluvial Flooding Scenarios: The Case of Jiaozuo Urban Area, China

Urban pluvial flooding has become an important factor in urban casualties and economic losses, thus, there is an urgent need to strengthen urban emergency management research and improve emergency response capabilities to flooding. The SCS–CN hydrological model combined with GIS spatial analysis were used to assess the spatial accessibility of the emergency response to key urban public services (medical and fire) for different pluvial flooding scenarios of the Jiaozuo urban area. The results show that the coverage area of the public service department (medical and fire) emergency response decreases as the period of pluvial flooding recurrence increases. The accessibility of the public service department (medical and fire services) emergency response shows a gradual decline from the center of the Jiaozuo urban area to the periphery. The depth and area of water accumulation in the northern part of the Zhongzhan District, the northeastern part of the Macun District, and the southwestern part of the Shanyang District gradually increased as the heavy rainfall recurrence period increased. Emergency response from public services (medical and fire services) could not arrive within 15 min.

Augmentation of a Hospital Incident Command System to Support Continued Waves of the COVID-19 Pandemic.

Stamford Hospital (SH) is a 305 bed Level II Trauma center located in Fairfield County, the epicenter of the coronavirus disease 2019 (COVID-19) pandemic in Connecticut. The COVID-19 pandemic was a fast paced, rapidly evolving crisis, presenting our leadership team with unique challenges related to resource availability, patient care, and staff safety. The existing Hospital Incident Command System (HICS) was activated in March 2020 to coordinate our operational emergency management planning, response, and recovery capability for this unplanned event. Although HICS lays the groundwork for hospital preparations and protocol implementation, it is not designed to withstand prolonged crisis circumstances. Given the conditions that the COVID-19 pandemic presented, the possibility for future waves became an impending reality, prompting the need for a long-term solution. To establish guidelines that promoted balance between necessary preparations in the case of additional surges of the pandemic and concurrent resumption then maintenance of routine hospital operations, the SH COVID-19 Playbook was created. The Playbook, presented here, is arranged in accordance with the evidence-based 4 S's (Space, Staff, Systems, and Stuff) strategic critical care planning framework, to address surge capacity management within our hospital's four main patient care areas and additional supportive services. Through feedback from frontline caregivers and leaders within SH, the Playbook captures our experience, best practices, and insight acquired during the first wave of the pandemic. Established with the intentions of equipping leadership and staff globally, guidelines are presented to aid in the navigation of future pandemic surges and successfully care for COVID-19 patients, ensure staff safety, allow for normal services to operate, and provide optimal communication and support for the community, patients, and staff.

Flood risk assessment of urban cultural heritage based on PSR conceptual model with game theory and cloud model – A case study of Nanjing

Urban cultural heritage has rich historical, artistic, and scientific value. However, due to the increasing occurrence of extreme rainfall events globally, urban cultural heritage sites face increasing flood disaster risks. A flood risk assessment tool offers a scientific foundation for decision-making and is critical for understanding and managing flood risk for these heritage sites. There are several shortcomings in the previous literature, such as its failure to consider the emergency response capability of cultural heritage sites; nor does it reveal the uncertainty and nonlinear relations between assessment indexes and risk levels. To address these limitations of the previous research, this study builds a novel and easy-to-implement index-based flood risk assessment method based on the pressure-state-response conceptual model with game theory and cloud model (PSR-GT-CM). This study shows that the PSR-GT-CM is a feasible and effective method for flood risk assessment of urban cultural heritage sites. This method can be used to provide an accurate and efficient preliminary assessment of flood risk for urban cultural heritage sites with limited data and can be a useful reference for making decisions about the protection of cultural heritage sites and identifying cultural heritage sites that need a more detailed analysis. This method is illustrated through an application to 93 national-level protected cultural heritage sites in Nanjing, China.

DEVELOPMENT AND APPLICATION OF A SMART EMERGENCY RESPONSE PLATFROM FOR EARTHQUAKE DISASTERS BASED ON MULTI-SOURCE MONITORING DATA

Abstract. Because of the characteristics of the strong suddenness of disasters, many secondary disasters, and high requirements for response timeliness, the development of integrated disaster monitoring with space-air-ground (SAG) multi-source data is a key scientific issue to deal with natural disasters and ensure the safety of people's lives and properties. However, the existing technical methods of emergency response information extraction and collaborative monitoring and evaluation are slightly weak, and the application service capability needs to be improved. Based on the formation mechanism and evolution law of earthquake disasters, this paper studies the SAG multi-source collaborative monitoring method. Using multi-source data, we not constructed the algorithm model of disaster evolution process simulation and risk dynamic assessment, but realized rapid disaster emergency assessment and intelligent emergency decision-making. At the same time, it has developed an integrated platform for earthquake disaster monitoring and smart spatial information services, which realizes the integrated expression of elements such as rapid access to multi-source spatiotemporal information, smart service models, and disaster monitoring information. We provide a task-driven software-hardware cooperative service application. In this way, the emergency response capability of regional earthquake disasters can be improved, the development of disaster prevention, mitigation, and relief emergency industries can be accelerated, and scientific and technological support can be provided, which ensures national development.

Compact Vehicle Driver Fatigue Recognition Technology Based on EEG Signal

The driver’s fatigue directly affects the safety factor of the compact vehicle driving in actual road. Mastering the driver’s fatigue state plays an important role in the driver’s safety driving and timely adjustment of mental state. In view of the particularity of the driving safety of the compact vehicle, this paper takes the driver’s brain electricity (EEG) signal as the research object, and starts from the formulation of the experimental scheme, and based on the special training system in the simulation driving software. Two types of driving quality evaluation indicators: the fine operation ability and emergency response capability is formulated; after preprocessing and eigenvalue selection of EEG signals, DPCA clustering algorithm combined with driving quality is used to complete the classification of driver fatigue and the marking of EEG signal feature data set. Finally, the driver fatigue recognition model is initially constructed by using the labeled data set combined with the convolutional neural network (CNN).

Application of an Ordinal Probit Regression Model in predicting emergency response rates in the Fire Department of New York City.

This article introduces the use of an Ordinal Probit Regression Model to predict emergency response rates in the Fire Department of New York City (FDNY) when data are of the count-type variety and ordinal. The main objective of this article is to model the effects of boroughs, emergency incident types, and the volume of emergency incidents (counts) on response rates for the years 2010-2016. The model framework discusses the model selection criteria when the proportional odds assumptions for ordinal models are no longer valid, and a model in which scale effects are allowed to vary among emergency incident types is preferred. This statistical insight can be used by elected officials and city agencies to evaluate FDNY's emergency response availability, capability, and operational performance in order to improve emergency services in the five boroughs.

Evaluation and Obstacle Analysis of Emergency Response Capability in China.

Emergency response capability evaluation is an essential means to strengthen emergency response capacity-building and improve the level of government administration. Based on the whole life cycle of emergency management, the emergency capability evaluation index system is constructed from four aspects: prevention and emergency preparedness, monitoring and early warning, emergency response and rescue, and recovery and reconstruction. Firstly, the entropy method is applied to measure the emergency response capability level of 31 Chinese provinces from 2011 to 2020. Second, the Theil index and ESDA (Exploratory Spatial Data Analysis) are applied in exploring the regional differences and spatial-temporal distribution characteristics of China’s emergency response capacity. Finally, the obstacle degree model is used to explore the obstacle factors and obstacle degrees that affect the emergency response capability. The results show that: (1) The average value of China’s emergency response capacity is 0.277, with a steady growth trend and a gradient distribution of “high in the east, low in the west, and average in center and northeast” in the four major regions. (2) From the perspective of spatial distribution characteristics, the unbalanced regional development leads to the obvious aggregation effect of “high-efficiency aggregation and low-efficiency aggregation”, and the interaction of the “centripetal effect” and “centrifugal effect” finally forms the spatial clustering result of emergency response capability level in China. (3) Examining the source of regional differences, inter-regional differences are the decisive factor affecting the overall differences in emergency response capability, and the inter-regional differences show a reciprocating fluctuation of narrowing–widening–narrowing from 2011 to 2020. (4) Main obstacles restricting the improvement of China’s emergency response capabilities are “the business volume of postal and telecommunication services per capita”, “the daily disposal capacity of city sewage” and “the general public budget revenue by region”. The extent of the obstacles’ impacts in 2020 are 12.19%, 7.48%, and 7.08%, respectively. Based on the evaluation results, the following countermeasures are proposed: to realize the balance of each stage of emergency management during the holistic process; to strengthen emergency coordination and balanced regional development; and to implement precise measures to make up for the shortcomings of emergency response capabilities.

Grassroots Mirroring under COVID-19: Does Community Resilience Affect Residents’ Responses? The Case of Shenzhen, China

In the face of the sudden outbreak of COVID-19, the community has played a large role in stemming the impact of COVID-19, and community resilience has become a key part of community governance. Community resilience is the ability of a community to respond effectively to risk and keep the community functioning by strengthening governance and leveraging community relationships in the face of external-disaster disruptions; this gives community participants a real sense that the community is equipped to face adversity and challenges. However, the evasive response of some residents is an important factor that hinders the community’s emergency response capabilities. Therefore, this study selected different types of communities in Shenzhen, China, from 9–23 July 2021, conducted a field survey, and obtained 2256 questionnaires using multi-segment random sampling. Based on the questionnaire data, this study uses factor analysis, correlation analysis, multiple linear regression analysis, and cluster analysis to explore the mechanisms of community resilience on residents’ risk coping styles, and the differences between community resilience and residents’ risk coping styles in different types of communities. The study found that, first, community resilience has a significant positive impact on proactive risk response, among which governance performance has a more significant impact; second, community resilience has a negative correlation with evasive coping styles, in which governance performance has a more significant impact; third, there are obvious differences in the level of resilience between different types of communities, with urban communities being the best, mixed communities being second, and transition communities being last. The government’s role in guiding and organizing the population was extremely significant during the COVID-19 pandemic, highlighting the superiority of the socialist system. The role of the community in social management has become increasingly prominent, and community resilience has become a key factor in controlling COVID-19.

Study on emergency escape route planning under fire accidents in the Burtai coal mine

Developing an effective safety emergency plan for coal mines is crucial to prevent and reduce accidents, as well as improve the emergency response capability. This paper identifies and analyzes potential accident hazards in the Burtai coal mine through a comprehensive and practical investigation of risk factors. Based on a mathematical model of a mine fire disaster relief algorithm, the MATLAB software is used to conduct numerical simulations of the dynamic spreading process of the fire smoke. Several escape routes are determined based on the simulation results, including the main escape route at the working face of coal mining, the main escape route at the working face of tunneling, and the main escape route against the reverse wind in the main inclined shaft, the auxiliary adit, and the main air intake roadway. The results presented in this study can provide guidance for improving fire emergency escape and rescue plans of the Burtai coal mine.

Establishment and assessment of urban meteorological disaster emergency response capability based on modeling methods

Emergency response capability assessments can be performed to determine the state of emergency management and identify weaknesses, thus increasing preparedness and strengthening emergency rescue capabilities. Multiple linear regressions (MLRs), support vector machines (SVMs), and artificial neural networks (ANNs) are widely used for assessment and prediction. However, few studies have used them to evaluate urban meteorological disaster emergency response capabilities. This study used these mathematical models to evaluate urban meteorological disaster emergency response capabilities, and the model verification parameters and deviations were compared. The analytic hierarchy process formulated a comprehensive weighting system and a quantitative assessment standard. The meteorological disaster cases from 2010 to 2020 were used as the data source, and then 50 sets of sample data were obtained to enhance the operability and scientificity. MLR, SVM, and ANN were used to establish an urban meteorological disaster emergency response capability assessment and prediction model. The results indicate that all three models are effective. SVMs (mean squared error = 0.1074) provide excellent prediction, MLRs (mean squared error = 0.1184) provides satisfactory prediction, and ANNs (mean squared error = 0.3211) provides poor prediction. The proposed estimation methods provide an effective predictive evaluation model that reflects the actual conditions and can enable the government and other groups to perform inspections conveniently. It can not only check one by one according to the quantitative evaluation standards but also continuously improve the emergency management ability according to the forecast results and then enhance the ability to resist meteorological disasters in time.

Comprehensive Risk Assessment of Urban Waterlogging Disaster Based on MCDA-GIS Integration: The Case Study of Changchun, China

Urban waterlogging will harm economic development and people’s life safety; however, the waterlogging risk zoning map provides the necessary decision support for the management of urban waterlogging, urban development and urban planning. This paper proposes an urban waterlogging risk assessment method that combines multi-criteria decision analysis (MCDA) with a geographic information system (GIS). The framework of urban waterlogging risk assessment includes four main elements: hazard, exposure, vulnerability, and emergency response and recovery capability. Therefore, we selected the urban area of Changchun City, Jilin Province as the study area. The Analytic Hierarchy Process (AHP) is a generally accepted MCDA method, it is used to calculate the weight and generate a result map of hazards, exposure, vulnerability, and emergency responses and recovery capability. Based to the principle of natural disaster risk formation, a total of 18 parameters, including spatial data and attribute data, were collected in this study. The model results are compared with the recorded waterlogging points, and the results show that the model is more reliable.

Causal Analysis and Prevention Measures for Extreme Heavy Rainstorms in Zhengzhou to Protect Human Health.

This study focused on the extreme heavy rainstorm that occurred in Zhengzhou in July 2021; approximately 380 people were killed or missing as a result of this storm. To investigate the evolution behaviors of this rainstorm and take corresponding prevention measures, several methods and models were adopted, including cloud modeling, preliminary hazard analysis (PHA), fault tree analysis (FTA), bow-tie modeling, and chaos theory. The main reasons for this rainstorm can be divided into the following three aspects: force majeure, such as terrain and extreme weather conditions, issues with city construction, and insufficient emergency rescue. The secondary disasters caused by this rainstorm mainly include urban water logging, river flooding, and mountain torrents and landslides. The main causes of the subway line-5 accident that occurred can be described as follows: the location of the stabling yard was low, the relevant rules and regulations of the subway were not ideal, insufficient attention was given to the early warning information, and the emergency response mechanism was not ideal. Rainstorms result from the cross-coupling of faults in humans, objects, the environment, and management subsystems, and the evolution process shows an obvious butterfly effect. To prevent disasters caused by rainstorms, the following suggestions should be adopted: vigorously improve the risk awareness and emergency response capabilities of leading cadres, improve the overall level of urban disaster prevention and mitigation, reinforce the existing reservoirs in the city, strengthen the construction of sponge cities, and improve the capacity of urban disaster emergency rescue.

TECHNOLOGY ON HIGH-ACCURACY DEM EXTRACTION FROM AIRBORNE INTERFEROMETRIC SAR

Abstract. Remote sensing image mapping (aviation, aerospace, UAV) is the main form of current mapping. Optical image mapping has been a certain research foundation and played an important role in the mapping task. However, cloud, ice, snow, rain, and haze conditions seriously affect the interpretation and processing of optical images, making it difficult to meet the needs of rapid emergency response. Synthetic Aperture Radar (SAR) is currently the only method that can achieve all-day, all-weather rapid imaging under various weather conditions such as day, night, cloud, snow, rain, etc. With unique advantages unmatched by traditional optical remote sensing technology, it is an important technical guarantee for improving emergency response capabilities and promoting remote sensing and geographic information industries, and an earth observation technology that has been invested and vigorously developed internationally. Digital Elevation Model (DEM) plays an increasingly important role in the application of terrain information acquisition such as rapid acquisition of sudden disasters and surface deformation information acquisition. Rapid acquisition of large area high-accuracy DEM is one of the important research contents of SAR mapping. Based on interferometric SAR data combined with sensor orbit data, external DEM and other auxiliary data, DEM is finally generated through complex image registration, interference image generation, removal of flat ground effects, interference phase filtering, phase unwrapping, interference calibration and geocoding. The registration accuracy of multiple images greatly affects the accuracy of DEM. This paper proposes an improved registration method based on the conventional rough registration, pixel-level registration and sub-pixel registration. When the motion compensation of the sensor platform is unknown during imaging, it can meet the requirements of high-accuracy and large-scale rapid registration of dual-antenna polarization interferometric SAR. The experimental data is X-band airborne SAR data in Weinan region of Shaanxi Province, and DEM products with the elevation accuracy better than 0.5m is generated, which verifies the effectiveness, accuracy and fast processing ability of the method.

The Nigerian Military Public Health Response to COVID-19: A 14-Month Appraisal.

The COVID-19 pandemic has caused significant morbidity and mortality since its emergence in December 2019. In Nigeria, the government inaugurated the Presidential Task Force on COVID-19 to coordinate resources while the Nigeria Centre for Disease Control led the public health response. The Nigeria Ministry of Defence Health Implementation Programme (MODHIP), in partnership with the US Army Medical Research Directorate - Africa/Nigeria, responded immediately to the pandemic by establishing a public health emergency operations center to coordinate the military response in support of national efforts. MODHIP has 5 functional units and 6 pillars that coordinate testing, surveillance, case management, risk communication, logistics, research, and infection prevention and control. It developed an incident action plan and each pillar had its own terms of reference to guide specific response activities while preventing duplication of efforts within the military and the Nigeria Centre for Disease Control. In addition, awareness and sensitization sessions were conducted on preventive practices for COVID-19 and infrastructure was provided for hand hygiene and screening at all military facilities. Military laboratories were configured for SARS-CoV-2 testing while selected military health facilities were equipped and designated as COVID-19 treatment centers. Research proposals aimed at better understanding the disease and controlling it were also developed. The traditional combat role of the military was redirected to complement this public health emergency response. In this article, we highlight gaps, opportunities, and lessons to improve military participation in public health emergency response in the future. More funding and multisectoral collaboration with civilian institutions are key to strengthening military public health emergency preparedness and response capabilities.

Assessment of Maize Drought Risk in Midwestern Jilin Province: A Comparative Analysis of TOPSIS and VIKOR Models

Drought is a major natural disaster that causes a reduction in rain-fed maize yield. Agricultural drought risk assessment is conducive to improving regional disaster management ability, thereby reducing food security risks and economic losses. Considering the complexity of risk assessment research, an increasing number of researchers are focusing on the multiple-criteria decision-making (MCDM) method. However, the applicability of the MCDM method to agro-meteorological disaster risk assessments is not clear. Therefore, this study comprehensively evaluated hazard, exposure, vulnerability, and emergency response and recovery capability using the TOPSIS and VIKOR models to generate a maize drought risk map in mid-western Jilin Province and ranked the drought risk of each county. The results showed that: (1) maize drought risk in the middle and west of Jilin province showed an increasing trend. Spatially, the risk diminished from west to east. The drought risks faced by Tongyu, Changchun, and Dehui were more severe; (2) the evaluation results of the two models were verified using the yield reduction rate. The VIKOR model was found to be more suitable for agrometeorological drought risk assessments; (3) according to the damage degree of drought disaster to maize, the cluster analysis method was used to divide the study area into three sub-regions: safe, moderate drought, and severe drought. Combined with the characteristics of different regions, suggestions on disaster prevention and mitigation are proposed. The results of this study can provide a basis for formulating strategies to alleviate drought, reduce losses, and ensure the sustainable development of agriculture.

Flexible emergency management: Operational area adaptation during a pandemic.

The pandemic environment shaped the field of emergency management in 2020, creating a new operational paradigm for Contra Costa County's coordinated emergency response capability. This discussion represents initial steps in the improvement planning process for the County Emergency Operations Center (EOC). It offers one tool supporting organizational growth through a critical discussion of adaptation and flexibility in the EOC. Drawing from local, state, and national data, the discussion frames the local EOC experience in the context of how the pandemic intersected with long-established response frameworks. The discussion considers implications for future response to complex expanding incidents. The County operational area applied the emergency management frameworks of the Incident Command System (ICS) and California's Standardized Emergency Management System (SEMS) in novel ways, developed innovative solutions to meet critical resource needs, and leveraged new partnerships to enhance capabilities in 2020. Through this experience, the County emergency management organization was both singularly challenged and informed by the pandemic, even as it responded to simultaneously occurring incidents. There are takeaways in each of these areas that bear on improvement planning. In particular the review highlights the need to expand beyond traditional ICS roles and frameworks to facilitate a more flexible response. More broadly, this suggests that the field of emergency management grows more dynamic as it responds to more complex concurrent incidents with an ever-widening spectrum of -stakeholders.

Melding Fog Computing and IoT for Deploying Secure, Response-Capable Healthcare Services in 5G and Beyond

The fifth generation (5G) of mobile networks is designed to mark the beginning of the hyper-connected society through a broad set of novel features and disruptive characteristics, delivering massive connectivity, coverage and availability paired with unprecedented speed, throughput and capacity. Such a highly capable networking paradigm, facilitated by its integrated segments and available subsystems, will propel numerous cutting-edge, innovative and versatile services, spanning every possible business vertical. Augmented, response-capable healthcare services have already been identified as one of the prime objectives of both vendors and customers; therefore, addressing controversies and shortcomings related to the specific field is considered a priority for all stakeholders. The scope of this paper is to present the architectural elements of 5G which enable efficient, remote healthcare services along with emergency health monitoring and response capability. In addition, we propose a holistic scheme based on technical enablers such as Internet-of-Things (IoT) and Fog Computing, for mitigating common issues and current limitations which may compromise the proclaimed service delivery.

Modeling and probabilistic analysis of civil aircraft operational risk for suborbital disintegration accidents.

To reduce the collision risk to civil airliners caused by suborbital vehicle disintegration events, this paper uses a covariance propagation algorithm to model the debris landing point of suborbital disintegration accidents and gives a collision probability analysis method for civil airliners encountering debris during the cruise. Collision warning is performed for airborne risk targets to improve the emergency response capability of the ATC surveillance system to hazardous situations. The algorithm models the three-dimensional spatial motion target localization problem as a Gauss-Markov process, quantifying the location of debris landing points in the vicinity of nominal trajectories. By predicting the aircraft trajectory, the calculation of the inter-target collision probability is converted into an integration problem of a two-dimensional normally distributed probability density function in a circular domain. Compared with the traditional Monte Carlo method, the calculation speed of debris drop points is improved, which can meet the requirements of civil aviation for real-time response to unexpected situations.

Key emergency response technologies for abrupt air pollution accidents in China

Abrupt air pollution accidents can endanger people's health and destroy the local ecological environment. The appropriate emergency response can minimize the harmful effects of accidents and protect people's lives and property. This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years. With decades of effort, China has made significant progress in emergency monitoring technologies and equipment, source estimation technologies, pollutant dispersion simulation technologies and others. Many effective domestic emergency monitoring instruments (e.g., portable DOAS/FT-IR systems, portable FID/PID systems, portable GC-MS systems, scanning imaging remote sensing systems, and emergency monitoring vehicles) had been developed which can meet the demands for routine emergency response activities. A monitoring layout technique combining air dispersion simulation, fuzzy comprehensive evaluation, and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources. Multiple source estimation technologies, including the forward method and the inversion method, have been established and evaluated under various scenarios. Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed. A comprehensive emergency response platform integrating database support, source estimation, monitoring schemes, fast monitoring of pollutants, pollution predictions and risk assessment was developed based on the technical idea of "source identification - model simulation - environmental monitoring" dynamic interactive feedback. It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China.

Review on visualization technology in simulation training system for major natural disasters.

Major natural disasters have occurred frequently in the last few years, resulting in increased loss of life and economic damage. Most emergency responders do not have first-hand experience with major natural disasters, and thus, there is an urgent need for pre-disaster training. Due to the scenes unreality of traditional emergency drills, the failure to appeal to the target audience and the novel coronavirus pandemic, people are forced to maintain safe social distancing. Therefore, it is difficult to carry out transregional or transnational emergency drills in many countries under the lockdown. There is an increasing demand for simulation training systems that use virtual reality, augmented reality, and mixed reality visualization technologies to simulate major natural disasters. The simulation training system related to natural disasters provides a new way for popular emergency avoidance science education and emergency rescue personnel to master work responsibilities and improve emergency response capabilities. However, to our knowledge, there is no overview of the simulation training system for major natural disasters. Hence, this paper uncovers the visualization techniques commonly used in simulation training systems, and compares, analyses and summarizes the architecture and functions of the existing simulation training systems for different emergency phases of common natural disasters. In addition, the limitations of the existing simulation training system in practical applications and future development directions are discussed to provide reference for relevant researchers to better understand the modern simulation training system.