Emergency Management System Research Articles

Research on the evaluation of emergency management capability for urban public health emergencies under the perspective of resilience—a case study of Henan Province, China

With the rapid development of the economy and society, the likelihood of sudden public health emergencies in urban areas continues to rise. In particular, major infectious diseases that have gained global attention, such as the SARS virus, H1N1 influenza, Ebola outbreak, and COVID-19 pandemic, have presented significant challenges to urban emergency management systems. Evaluating emergency management capability is a fundamental requirement for developing emergency response capacity. To this end, this study combines the theory of resilience with the theory of full-process equilibrium emergency management, selects 31 evaluation indicators from six key aspects: preparedness, forewarning, mitigation, disposal, recovery, and learning. The indicator weights are determined using the AHP-Entropy Weight Method, and a TOPSIS model is constructed to assess the emergency management capability of urban public health emergencies. The model’s applicability is validated by examining 18 cities in Henan Province. The findings suggest that Jiaozuo, Hebi, Zhengzhou, and Luohe possess relatively robust emergency management capabilities for sudden public health incidents, whereas Kaifeng, Pingdingshan, and Shangqiu exhibit weaker capabilities.

Construction of a new emergency management system for potentially viral/viral municipal solid waste in China: Based on the "Beam-Column Structure" framework model

Emergency management of municipal solid waste during public health emergencies is crucial for curbing the spread of viruses and controlling environmental pollution. Most existing solid waste management systems, are designed with a top-down approach, covering multiple industries and sectors. However, these systems often fail to effectively manage potentially viral solid waste in household waste, which impedes effective solid waste management during public health emergencies and increases the risk of viral outbreaks. For example, during the COVID-19 outbreak, negligent management of potentially viral solid waste may result in the formation of a potential transmission chain of COVID-19 virus. Improper waste management may contaminate natural vectors such as water, soil and air, thereby increasing the pathways of human contact with infected vectors and promoting the risk of transmission of viral diseases such as dengue, Zika and hepatitis A. In this study, the applicability and limitations of the Chinese public emergency management system in the disposal of Potentially Viral/Viral Municipal Solid Waste (PVMSW) were analyzed in the breakout of public health crises. To address the need for precise risk control, efficient collaboration among key stakeholders, functional integration crossing multiple management organizations and flexible responses to complex situations, we proposed a PVMSW emergency management system based on a “Beam-Column Structure” model. This system consists of four modules: main traction, organizational leadership, functional articulation and demand matching. Each module is supported by the corresponding safeguards, including multi-level subject responsibilities, multi-scenario organization and implementation, multi-chain process connection and multi-demand control methods. The PVMSW emergency management system proposed in this study contributes to extending the framework of existing waste management protocols and enhancing the timely collection, transportation and disposal of PVMSW in public health crises. It offers valuable insights and guidance on the practices for improving risk awareness and management capacity in China's solid waste emergency response.

Robust Estimation of Crowd Density Using Vision Transformers

Estimating and predicting crowd density at large events or during disasters is of paramount importance for enhancing emergency management systems. This includes planning effective evacuation routes, optimizing rescue operations, and ensuring efficient deployment of emergency services. Traditionally, surveillance systems that rely on cameras have been employed to monitor crowd movements. However, accurately estimating crowd density using such systems presents several challenges. These challenges stem primarily from the interaction between large crowds and the limitations of two-dimensional cameras in capturing the full scope of three-dimensional spaces. Optical distortions, environmental factors, and variations in camera angles further complicate the task, making accurate estimations difficult to achieve. To address these challenges, this paper introduces a robust method for calculating crowd density that leverages advanced vision transformers. By combining the output of these transformers with a two-stage neural network, the method effectively mitigates the limitations of traditional approaches. One of the key advantages of the proposed system is its robustness, which allows it to perform well across different camera specifications, installation locations, and image aspect ratios. The method applies and evaluates various deep learning techniques, introducing improvements to existing network structures that are better suited for the problem at hand. Extensive experimental verification demonstrates that the proposed method consistently produces accurate crowd density estimates, even in diverse and complex crowd environments. This robust performance underscores its potential for improving emergency management and crowd control in real-world situations.

Reshaping disaster management: An integrated community‐led approach

AbstractThe management of disasters has traditionally involved public, private, and nongovernmental organisations working together. While scholars have examined the value of collaborations among these entities, less is known about how to successfully engage and empower communities in disaster management. Based on network governance theory, this article contributes to the growing body of public management literature on community engagement by presenting findings from an Australian research initiative conducted after the 2019/20 Black Summer bushfires in New South Wales. Through workshops and semi‐structured interviews with a total of 58 members from local communities and emergency agencies, this paper identifies differing perspectives on power distribution among stakeholders, indicating complexities in achieving an integrated and community‐led disaster management approach. The findings underscore the need to shift from exclusively centralised to more inclusive systems, recognising the unique contributions of nonofficial community‐based groups. To address this, the study suggests: a funded community consultation committee, ensuring government and local community representation; collaborative debriefing sessions, leveraging technology for knowledge capture; and the adoption of different leadership styles able to identify, include, and integrate communities as both steerers and rowers within established hierarchical arrangements.Points for practitioners The current centralised emergency management system, which relies on recognised experts and state‐controlled facilities, limits the integration of nonofficial resources and community‐based knowledge. A shift towards a more community‐centric and integrated approach (collaborative polycentric governance) is needed to enhance disaster resilience and response in Australia. Different stages of disaster reduction could and should have different leadership styles: a transformational, collaborative community‐based style should be implemented before and after the disaster, while a transactional leadership style, more focused on restructuring the system or how it is applied, should be adopted during the disaster.

Urban Emergency Evacuation Path Optimization Based on Uncertain Environments to Enhance Response for Symmetric and Asymmetric Evacuation Problems

Background: Serious secondary disasters caused by extreme natural weather conditions occur frequently, making it essential to establish a scientific and efficient modern emergency management system to maximize life-saving efforts. Methods: This study focuses on the uncertain environment of urban road networks and employs fuzzy theory to construct a 0–1 integer programming model for emergency evacuation paths that minimizes the average expected travel time. Results: We enhanced the neighborhood search strategy of the traditional ACO_time by incorporating the 2-opt and 3-opt perturbation mechanisms from the SA algorithm. Additionally, we utilized improved ant-volume and ant-perimeter models, along with their combinations, in the pheromone-updating mechanism of the basic ACO. The heuristic principles of the A* algorithm were integrated, introducing the joint influence of path and time into the heuristic function of the ACO algorithm. Conclusions: The IACO3 algorithm was tested on the Sioux Falls network and the Berlin Heisenheimer Center network. The computation time of the improved IACO3 algorithm was reduced by up to 20% compared to the original IACO3 algorithm in relation to the SA algorithm, with only a 4–5% increase in computation time compared to the ACO_time algorithm, which translates to an increase of merely 4–5 s. This demonstrates the superior solution efficiency of the IACO3 algorithm.

International comparison of pandemic policies in the United States and Japan: Combination of all-hazards and single-hazard approaches as a realistic option to policymaking for public health emergency management system

The all-hazards approach (AHA) is a ground concept of crisis management to build common capabilities to deal with diverse hazards and adopted as the standard approach by many countries. The single-hazard approach (SHA), on the other hand, is a concept in which measures are taken specifically for a particular disaster. The recent COVID-19 pandemic has raised a policy debate on the effectiveness of pandemic preparedness in both AHA and SHA regimes, which has yet to be settled. This is because not sufficient studies have been conducted to compare policies under both concepts systematically. In this study, a new analytical framework was developed to compare pandemic policies under AHA and SHA concepts. The framework was designed to analyze coverage of hazards and actions for pandemic preparedness and response in the policy documents. The United States (the U. S.) and Japan were selected as the representative countries adopting AHA and SHA respectively. As a result, we empirically demonstrated for the first time that both countries combined multi-hazards and single-hazard countermeasures. This will provide new alternative solutions for the binary argument between two approaches. We also analyzed the coverage of actions for pandemic preparedness and response and found that while both countries comprehensively scoped overall actions, there were significant differences in coverage of individual actions. These findings may be useful to identify agenda to improve pandemic policies after the COVID-19 in each country and the framework developed in this study provides a new tool contributing to policymaking for crisis management.

An explorative Bayesian analysis of functional dependencies in emergency management systems

AbstractThe study of emergency or crisis management practices acquires strategical relevance for resilient decision‐making under uncertainty. The assessment of system resilience is an asset to identify potential design or operational improvements of a complex socio‐technical system, such as an Emergency Management (EM) system. This research aims at analyzing the functional properties of an EM system recurring to a novel integration of the Functional Resonance Analysis Method (FRAM) and Bayesian Belief Networks (BBN). The FRAM is used to model and display the actors and the interactions in the system, while the BBN, dynamically updated when new data becomes available, supports a complementary quantitative assessment. The methodology is iterated in the analysis of an EM procedure, issued by a second‐line Emergency Response organization for Oil and Gas (O&G) operators in Norwegian continental shelf. The results of the study show that the proposed stochastic methodology compensates the drawbacks of traditional FRAM modeling, via the outcomes of BBN quantitative analyses. The findings, contextualized in EM, can be transferred to different socio‐technical contexts, both military and civil ones.

A Literature Study of Emergency Material Dispatch Models and Optimisation in the Context of Natural Disasters

The recurrent occurrence of natural disasters has brought into sharp focus the urgent need for the expedient distribution of emergency materials. In the aftermath of a disaster, the swift and precise distribution of essential emergency supplies is of the utmost importance in ensuring the basic survival needs of the affected population are met, minimising the impact of the disaster and maintaining social stability. In order to provide a comprehensive overview of the research progress in the field of emergency supplies dispatching after natural disasters, we employ the knowledge graph analysis software VOSviewer to investigate the optimisation issues pertaining to the emergency supplies dispatching model, taking into account the inherent uncertainty, from a multi-objective standpoint and across a range of algorithms. A total of 375 literature sources were included in the China Knowledge Network database for review. The research objectives, methods and conclusions of the representative literature on hot spots at home and abroad were subjected to analysis. The review examines the research objectives, methodologies and conclusions of the most prominent literature on the subject, both domestic and international, and analyses the current status of research on the scheduling of emergency materials in the context of natural disasters. By synthesising these findings, we aim to identify gaps in existing research and suggest directions for future endeavours to promote a more resilient and effective emergency management system that can respond rapidly to the ever-changing needs of disaster-affected communities.

Advanced fire emergency management based on potential fire risk assessment with informative digital twins

Modern large complex buildings, with their vast expanses and multipurpose usability, present diverse fire-spread scenarios, necessitating precise awareness of fire situations. Despite numerous studies integrating building information models with IoT and AI technologies to provide contextual information, there may be limitations in recognizing potential risks under dynamic fire behaviors during urgent situations. This paper presents a fire emergency management system based on an informative digital twin (IDT) to provide instantaneous fire situational information. Utilizing IDT, the system gathers building-specific fire scenario knowledge for immediate fire recognition. Leveraging this knowledge, the IDT assesses building fire risks and shares safety information on egress routes and zones with fire-related applications. A simulation case study revealed a fire recognition processing time of 0.88 s, acceptable for fire emergencies. Additionally, the IDT’s risk assessment reduced the total evacuation time by 65 s and potential injuries by 406, demonstrating the system’s effectiveness in fire emergency management.

The role of large reservoirs in drought and flood disaster risk mitigation: A case of the Yellow River Basin

The acceleration of water cycle processes in the context of global warming will exacerbate the frequency and intensity of extreme events and predispose to drought and flood disasters (DFD). The Yellow River Basin (YRB) is one of the basins with significant and sensitive impacts of climate change, comprehensive assessment and prediction of its DFD risk are of great significance for ecological protection and high-quality development. This study first constructed an evaluation index system for drought disaster risk and flood disaster risk based on hazard, vulnerability, exposure and the role of large reservoirs. Secondly, the weights of each evaluation index are established by the analytic hierarchy process. Finally, based on the four-factor theory of disasters, an evaluation model of DFD risk indicators is established. The impact of large reservoirs on DFD risk in the YRB is analyzed with emphasis. The results show that from 1990 to 2020, the drought disaster risk in the YRB is mainly distributed in the source area of the Yellow River and the northwest region (11.26–15.79 %), and the flood disaster risk is mainly distributed in the middle and lower reaches (30.04–31.29 %). Compared to scenarios without considering large reservoirs, the area at risk of high drought and high flood is reduced by 45.45 %, 44.22 % and 31.29 % in 2000, 2010 and 2020, respectively. Large reservoirs in the YRB play an important role in mitigating DFD risk, but their role is weakened with the enhancement of the emission scenario. Under the influence of different scenario models, the DFD risk in the YRB in 2030 and 2060 will increase, and the area of high drought and high flood risk in the middle and upper reaches of the basin will increase by 0.26–25.15 %. Therefore, the YRB should play the role of large reservoirs in DFD risk defense in its actions to cope with future climate change, while improving non-engineering measures such as early warning and emergency management systems to mitigate the impacts of disasters.

Emergency preparedness in the central sterile supply department: a multicenter cross-sectional survey

ObjectiveTo investigate the current situation of emergency preparation and emergency drill in the CSSD, and analyze its influence on the nurses’ emergency attitude and ability.MethodsThis study employed a multicenter stratified sampling method, conducted from January to June 2023 using the online survey, participants completed the general data, emergency preparedness and drill questionnaire, public health emergency response questionnaire and emergency capacity scale. An independent samples t test or Kruskal-Wallis test was used to analyse differences in nurses’ emergency capacity and attitudes.ResultsThe data from 15 provinces 55 hospitals in China. Overall, 77.58% of participants’ institutions set up emergency management teams, 85.45% have an emergency plan and revise it regularly. 92.12% store emergency supplies. All survey staff participated in the emergency drill, which predominantly consisted of individual drills (51.52%), with 90.30% being real combat drills, 49.09% of participants engaging in drills every quarter, and 91.52% of the drill’s participants exceeding 50%. The respondents’ emergency attitude score was (29.346 ± 6.029), their emergency ability score was (63.594 ± 10.413), and those with rescue experience showed a more positive attitude (Z = -2.316, P = 0.021). Different titles, education levels, rescue experience and the frequency of emergency drill affected the emergency rescue ability of the respondents (P < 0.05).ConclusionsMost medical institutions establish emergency management systems and plans, yet the content lacks geographical specificity.The duration and participation of emergency drills are high, but the effectiveness of the drills needs to be further improved, and the response capacity and attitudes of CSSD nurses are low. It is recommended that agencies develop comprehensive and targeted contingency plans to strengthen the inspection and evaluation of team strength, equipment and safeguards against the contingency plans, so as to ensure that the measures mandated by the contingency plans can be implemented promptly after the emergency response is initiated.

Game Model of Stable Cooperation During Resource Distribution in Self-Organized Emergency Management System

Game Model of Stable Cooperation During Resource Distribution in Self-Organized Emergency Management System

Dempster–Shafer theory-based information fusion for natural disaster emergency management: A systematic literature review

The frequency and unpredictability of natural disasters pose serious challenges to emergency management in modern society. Effective emergency management requires not only rapid response, but also accurate assessment of the situation, rational allocation of resources and scientific decision-making. Dempster–Shafer theory (DST), as a powerful information fusion tool, has been widely used in natural disaster emergency management in recent years. This study sorted out the core related articles of DST in various directions in the field of natural disaster emergency management, and formed a systematic literature review. In order to support and guide the completion of this work, keywords were selected according to the rules of Systematic literature review (SLR) and the requirements of article content research to screen and determine the literatures. On this basis, relevant information of the selected literatures was analyzed, including authors, institutions, countries, keywords, etc. Then, according to the theoretical framework of integrated emergency management, fifteen structured research questions are put forward, involving various aspects of integrated emergency management system, and these questions are answered in detail. After that, it discussed the literature, and summarized the contribution and future development direction of DST based on information fusion in natural disaster emergency management. The final results show that in the field of natural disaster emergency management, DST plays various and important roles, among which one of the most important roles is the integration of decision-making evidence at various stages of disasters, so as to make better decisions. By combining with other methods, DST improves its limitations. And in the process to expand their scope of use. Then, it focuses on how to solve the extended theory, practical application dimension and related defects of DST in the field of natural disaster emergency management.

National Database for Emergency Management (GIS based)

This study looks at the advantages of using geographic information systems for emergency management from two angles: the data management mode and the pre-warning signal emergency management requirements. This study discusses the need for geographic information systems in disaster management. This study explores the manifestation of the function graphics with one mining map, which comprises of the graphics data and characteristics data, the layer stack, and theme maps presenting, through the analysis of geographic information systems functions appropriate for pre-warning signals. It communicates with the conventional pre-warning signal system in order to present the pre-warning signal's outcome based on geographic information systems in the interim. Based on previous research, this study proposes a standard approach for pre- warning using geographic information systems. The project aims to create dynamic, multidimensional technical instruments for emergency management system implementation, as well as useful concepts for the development of pre-warning systems that are intimately related to actual places. Keywords: pre-warning, geographic information system, emergency management, and theme map

Enhancing hospital emergency response based on the experience of COVID-19

ABSTRACT Introduction The COVID-19 pandemic required a significant response from global healthcare systems. In Belgium, the crisis began in March 2020, prompting quick action in hospitals. This study assesses the effectiveness of Belgium’s hospital emergency plans and compares them with global standards for potential enhancements. Methodology An online survey targeting CEOs of 60 Flemish general hospitals evaluated the deployment of hospital emergency coordination cells during the pandemic’s first and fourth waves, utilizing various statistical analyses. Results Findings indicate a high establishment rate of COVID-19 coordination cells before the government’s deadline. Despite this readiness, differences in leadership, involvement, and communication strategies were noted among hospitals. There was a notable shift towards hybrid meetings and an evolving role for coordination cells, highlighting the need for a more structured crisis management approach. Conclusion The study concludes that while Flemish hospitals were quick to respond, the lack of a standardized framework suggests the potential for adopting models like the Hospital Incident Command System (HICS) for improved crisis management. Future research should examine the long-term effects of these strategies and the integration of comprehensive emergency management systems in Belgium’s healthcare.

Evolution of natural disaster terminologies, with a case study of the covid-19 pandemic

Disaster, catastrophe, and cataclysm are some English terminologies that describe the severity of adverse events. Civilians, reporters, and professionals often use these terminologies to communicate and report any event’s severity. This linguistic method is the most practical way to rapidly reach all levels of local/regional/national, and international stakeholders during disasters. Therefore, disaster terminologies play a significant role in disaster management. However, attaining the actual magnitude of a disaster’s severity cannot be comprehended simply by using these terminologies because they are used interchangeably. Unfortunately, there is no consistent method to differentiate disaster terminologies from one another. Additionally, no globally accepted standard technique exists to communicate the severity level when disasters strike; one observer’s ‘disaster’ can be another’s ‘catastrophe’. Hence, a nation’s ability to manage extreme events is difficult when there are no agreed terminologies among emergency management systems. A standard severity classification system is required to understand, communicate, report, and educate stakeholders. This paper presents perceptions of people about disaster terminologies in different geographical regions, rankings and differences in disaster lexical and lexicon. It explores how people perceive major events (e.g., the Covid-19 pandemic), and proposes a ranking of disaster terminologies to create a severity classification system suitable for global use.

SCOPE AND NATURE OF CHANGES IN THE CRISIS MANAGEMENT SYSTEM IN THE CIRCUMSTANCES OF CLIMATE CHANGE ON THE EXAMPLE OF THE POMERANIAN VOIVODESHIP

With the increasing impacts of climate change, especially in the context of rising temperatures,frequency and severity of extreme events, research into the preparedness of emergencymanagement systems is becoming a priority for governments and the international community.The purpose of the research was to identify the current state of the emergency managementsystem in the context of climate change and to assess its preparedness to operate under threatsgenerated by those changes, and to formulate proposals for improvement. The conducted researchwas based on an analysis of strategic documents, legal acts and an assessment of climate changeadaptation plans. An analysis of the preparedness of civil protection system structures for actionunder conditions of climate change at the local, regional and national levels was also carried out.The results of the research showed that the emergency management system of the PomeranianVoivodeship is insufficiently prepared for effective action under existing climate change risks.The discussion of the research results clearly indicates the need for systemic measures, coveringlegislative, organizational, educational and economic areas. Further research should focus ondeveloping tools for assessing the preparedness of civil protection system structures for actionunder conditions of climate change, and on developing more comprehensive adaptation plansat a local level. In addition, it is important to continue research on improving the warning andalert system, as well as increasing public awareness of climate risks. This research is a step towardeffectively preparing the emergency management system for operations under a changing climate,thus providing a more secure environment for local communities.

IMPLEMENTASI TERKAIT KESIAPAN PETUGAS PANTI TERHADAP SISTEM PENANGGULANGAN GAWAT DARURAT TERPADU (SPGDT) DI PANTI SOSIAL LANJUT USIA HARAPAN KITA PALEMBANG

Background: The Integrated Emergency Management System (SPGDT) is one of the health service innovations to handle emergency cases at the Harapan Kita Social Institution for the Elderly, Palembang. Residents of the orphanage still have complaints about the implementation of the SPGDT program, complaints are slow to handle, call center access is not easy to contact, the role of case management by the orphanage staff team is still slow. Purpose: to analyze the implementation related to the readiness of the nursing home staff regarding the integrated emergency response system (SPGDT). Methods: qualitative research with in-depth interviews and observation. There were 3 informants in the study consisting of the head of the orphanage, staff and employees at the Harapan Kita Palembang Social Home for the Elderly. The variables used to see the implementation of the readiness of the orphanage officers are communication, resources and infrastructure. The research was carried out for 3 months February-April 2023. Data analysis was processed according to the characteristics of content analysis, namely: data collection, data reduction, verification, data presentation and drawing conclusions. Research results: shows that the implementation related to the readiness of the orphanage staff has not gone as expected, efforts to increase knowledge and access have not been achieved, communication and coordination between teams have not been effective. Conclusion: the integrated emergency management system at Harapan Kita Social Institution Palembang is still not optimal and has not been supported by medical personnel and adequate infrastructure

Knowledge Management Model for Urban Flood Emergency Response Based on Multimodal Knowledge Graphs

Recently, frequent flood disasters in China have seriously threatened economic development and public safety. This paper addresses the need for a dynamic urban flood emergency knowledge management system in emergency management departments and the lack of systematic knowledge among emergency managers regarding urban flood control. A multimodal knowledge graph-based urban flood emergency knowledge management model was constructed to enhance the decision-making capabilities of emergency management departments, improve the efficiency of public emergency evacuation, and reduce losses from urban flood disasters by analyzing the shortcomings of the existing emergency management system. An intelligent and dynamic flood emergency knowledge management model was built. This paper integrates multimodal knowledge graph technology to establish a multimodal emergency knowledge management framework for urban flood control. It develops and simulates the proposed model’s application scenarios for urban flood emergency evacuation using the Flocking algorithm on the NetLogo platform. Through simulation experiments, the practicality and effectiveness of the model in real flood disaster situations were examined, particularly in simulating crowd evacuation behavior. The study found that the model significantly improves the accuracy of information and decision-making speed during emergency responses and supports emergency management departments in conducting targeted and personalized emergency decisions. This research provides a scientific basis for emergency management departments to optimize their emergency response strategies to flood disasters and serves as a reference and example for the application of multimodal knowledge graph technology in emergency management.

Value Realization of Intelligent Emergency Management: Research Framework from Technology Enabling to Value Creation

This paper studies the application and the application value of intelligent emergency for emergency management in the big data environment, to fill the research gap that neglected the application value (performance) measurement of intelligent emergency, further improving the effectiveness of intelligent emergency management. Firstly, bibliometric analyses of approximately 3900 documents in intelligent emergency field are imported, and the future research trend of intelligent emergency management is cleared. Theory of STT (Socio-Technical Theory), concerning technical system and social system, is introduced. The concept of emergency management system ‘technology enabling’ and ‘enabling value creation’ are defined in accordance with the bibliometric analyses and STT. Secondly, a research framework including ‘technology enabling’ and ‘enabling value creation’ for decision-making paradigm in emergency management according to the big data environment is constructed. Furthermore, detail analyses approach from intelligent emergency ‘technology enabling’ to ‘enabling value creation’ in emergency management are proposed. Finally, earthquake disasters are taken as an example and specific analyses of the intelligent emergency enabling and enabling value creation are explored, specifically, the enabling value creation are discussed from the view of measurable indicators. The clear concept of emergency management system ‘technology enabling’ and ‘enabling value creation’ as well as the detail analyses approach from intelligent emergency ‘technology enabling’ to ‘enabling value creation’ provide theoretical basis for scholars and practitioners to evaluating the value (performance) of intelligent emergency for the first time.