Explore the vast range of titles available.

Background The practical application of infectious disease emergency plans in mental health institutions during the ongoing pandemic has revealed significant shortcomings. These manifest as chaotic management of mental health care, a lack of hospital infection prevention and control (IPC) knowledge among medical staff, and unskilled practical operation. These factors result in suboptimal decision-making and emergency response execution. Consequently, we have developed a digital-based emergency prevention and control system to reinforce IPC management in psychiatric hospitals and enhance the hospital IPC capabilities of medical staff. Methods The system incorporates modern technologies such as cloud computing, big data, streaming media, and knowledge graphs. A cloud service platform was established at the PaaS layer using Docker container technology to manage infectious disease emergency-related services. The system provides application services to various users through a Browser/Server Architecture. The system was implemented in a class A tertiary mental health center from March 1st, 2022, to February 28th, 2023. Twelve months of emergency IPC training and education were conducted based on the system. The system’s functions and the users’ IPC capabilities were evaluated. Results A total of 116 employees participated in using the system. The system performance evaluation indicated that functionality (3.78 ± 0.68), practicality (4.02 ± 0.74), reliability (3.45 ± 0.50), efficiency (4.14 ± 0.69), accuracy (3.36 ± 0.58), and assessability (3.05 ± 0.47) met basic levels (> 3), with efficiency improvement and practicality achieving a good level (> 4). After 12 months of training and study based on the system, the participants demonstrated improved emergency knowledge (χ 2  = 37.69, p  < 0.001) and skills ( p  < 0.001). Conclusion The findings of this study indicate that the digital-based emergency IPC system has the potential to enhance the emergency IPC knowledge base and operational skills of medical personnel in psychiatric hospitals. Furthermore, the medical personnel appear to be better adapted to the system. Consequently, the system has the capacity to facilitate the emergency IPC response of psychiatric institutions to infectious diseases, while simultaneously optimising the training and educational methodologies employed in emergency prevention and control. The promotion and application of this system in psychiatric institutions has the potential to accelerate the digitalisation and intelligence construction of psychiatric hospitals. Key points • Digital Emergency-Plan System Improved Responding Efficiency Of Psychiatry Hospital. • Digital System Enhanced Knowledge Level and Emergency Responding Ability of Staff. • Digital Emergency-Plan System Helped Relocation of Emergency Resource.

Water pollution is an important aspect of a national water treatment. Sudden water safety incidents are random and destructive, often bringing about huge losses of life and property. Due to the uncertainty of sudden water pollution, it is difficult to respond in a timely and rapid manner. Emergency personnel must deal with emergencies quickly and effectively to reduce the harm caused by these emergencies. The randomness and uncertainty of sudden water pollution events make emergency work more complicated; it is difficult for current emergency plans to play guiding roles in complex responses. The decision-making and use of traditional water safety procedures largely depend on the experiences of command personnel, as well as on the emergency plan, which often has poor applicability. This can result in ineffective implementation of emergency actions and use of resources stemming from the high subjectivity and low efficiency of emergency plans. In this paper, we summarize previous research on digital planning and platform component technology exploration in order to evaluate the use of sudden water safety emergency procedures. We first analyze the main problems in the construction and use of emergency plans (e.g., the lack of experience and adaptability). Secondly, based on the decision-making support platform, a digital emergency plan database for water pollution emergencies was established by using component technology and knowledge map technology. In doing so, the decision support platform could enable the rapid construction of digital plans that improve application efficiency in an actual response scenario. Finally, through the system example, this system model can be quickly matched from the plan database to the emergency plan that meets the current scenario. It is a recommended model used to provide rapid and effective assistance for emergency management and improve emergency efficiency.

The U.S. government supports programs to combat global HIV/AIDS through an initiative that is known as the President's Emergency Plan for AIDS Relief (PEPFAR). This initiative was originally authorized in the U.S. Leadership Against HIV/AIDS, Tuberculosis, and Malaria Act of 2003 and focused on an emergency response to the HIV/AIDS pandemic to deliver lifesaving care and treatment in low- and middle-income countries (LMICs) with the highest burdens of disease. It was subsequently reauthorized in the Tom Lantos and Henry J. Hyde U.S. Global Leadership Against HIV/AIDS, Tuberculosis, and Malaria Reauthorization Act of 2008 (the Lantos-Hyde Act). Evaluation of PEPFAR makes recommendations for improving the U.S. government's bilateral programs as part of the U.S. response to global HIV/AIDS. The overall aim of this evaluation is a forward-looking approach to track and anticipate the evolution of the U.S. response to global HIV to be positioned to inform the ability of the U.S. government to address key issues under consideration at the time of the report release.

PurposeDecision-making problems in emergency plan selection for epidemic prevention and control (EPAC) are generally characterized by risky and uncertainty due to multiple possible emergency states and vagueness of decision information. In the process of emergency plan selection for EPAC, it is necessary to consider several obvious features, i.e. different states of epidemics, dynamic evolvement process of epidemics and decision-makers' (DMs') psychological factors such as risk preference and loss aversion.Design/methodology/approachIn this paper, a novel decision-making method based on cumulative prospect theory (CPT) is proposed to solve emergency plan selection of an epidemic problem, which is generally regarded as hybrid-information multi-attribute decision-making (HI-MADM) problems in major epidemics. Initially, considering the psychological factors of DMs, the expectations of DMs are chosen as reference points to normalize the expectation vectors and decision information with three different formats. Subsequently, the matrix of gains and losses is established according to the reference points. Furthermore, the prospect value of each alternative is obtained and the comprehensive prospect values of alternatives under different states are calculated. Accordingly, the ranking of alternatives can be obtained.FindingsThe validity and robustness of the proposed method are demonstrated by a case calculation of emergency plan selection. Meanwhile, sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and TODIM (an acronym in Portuguese for interactive and MADM) method illustrate the effectiveness and superiority of the proposed method.Originality/valueAn emergency plan selection method is proposed for EPAC based on CPT, taking into account the psychological factors of DMs.HighlightsThis paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.

Individual household emergency planning is the most fundamental and can be the least expensive way to prepare for natural disasters. However, despite government and nonprofit educational campaigns, many Americans still do not have a household plan. Using a national sample of Americans, this research observes factors that influence people’s likelihood of developing a household emergency plan. Based on the analysis, people’s efficacy in preparedness activities, previous exposure to disasters and preparedness information positively influence the likelihood that someone will have developed a household emergency plan. Alternatively, demographic variables such as being Hispanic/Latino, identifying as Asian, and being a renter decrease the likelihood that someone will have developed a plan in the American context. But, the reason for these negative relationships are unclear. Subsequent to the analysis, recommendations for future research are provided to better understand observed relationships.

Emergency response is an important task in geologic hazard emergency management in China. Rapid emergency response actions can effectively reduce the losses caused by geologic hazards. Emergency plans and emergency command systems play an important role in emergency response. The emergency response still comes with challenges, such as the difficulty of integrating emergency plans with real-time geologic hazard information and the operability of emergency disposal in emergency plans. One possible approach to solving this problem is to model and represent knowledge and to enable the emergency command system to acquire and intelligently provide the required emergency response knowledge. In this paper, we propose a conceptual model of knowledge for geologic hazard emergency response (GHER). The geospatial characteristics of GHER knowledge are represented by the geo-ontology in the modeling process. The ontology enables semantic interoperability of GHER knowledge. A case study is used as an application test to evaluate the framework of GHER knowledge acquisition. In the framework, the GHER knowledge model enables the emergency command system to provide imperative knowledge intelligently for emergency decision-making; knowledge inference enables the emergency command system to provide important implicit knowledge for emergency response; and spatial analysis of geographic information system is applied to visualize and analyze spatial data in the process of emergency response.

The emergency plans for water diversion projects suffer from weak knowledge correlation, inadequate timeliness, and insufficient support for intelligent decision-making. This study incorporates knowledge graph technology to enable intelligent recommendations for emergency plans in water diversion projects. By employing pre-trained language models (PTMs) with entity masking, the model's ability to recognize domain-specific entities is enhanced. By leveraging matrix-based two-dimensional transformations and feature recombination, an interactive convolutional neural network (ICNN) is constructed to enhance the processing capability of complex relationships. By integrating PTM with ICNN, a PTM–ICNN method for joint extraction of emergency entity relationships is constructed. By utilizing the Neo4j graph database to store emergency entity relationships, an emergency knowledge graph is constructed. By employing the mutual information criterion, intelligent retrieval and recommendation of emergency plans are achieved. The results demonstrate that the proposed approach achieves high extraction accuracy (F1 score of 91.33%) and provides reliable recommendations for emergency plans. This study can significantly enhance the level of intelligent emergency management in water diversion projects, thereby mitigating the impact of unforeseen events on engineering safety.

To make the emergency plan system more feasible and make up for the deficiency of current emergency management organization, a super network structure model of the emergency plan system of coastal cities based on risk scenarios, emergency tasks, emergency resources and emergency capabilities is proposed. Firstly, according to the requirements of the super network structure and the key influencing factors of the emergency plan system in coastal cities, four types of core elements, namely risk scenarios, emergency tasks, emergency resources and emergency capabilities, are proposed. Secondly, the paper defined the relationship of similar core elements and heterogeneous core elements and established a super network structure of coastal city emergency plan system, which consists of four types of core elements and multi-nodes participating in super edge. Thirdly, in order to measure the feasibility of the emergency plan system, the comprehensive index evaluation method of feasibility is proposed by integrating three indicators: node correlation degree, emergency plan system coordination ability and emergency plan system similarity. Finally, the case application shows that the super network model provides an effective method for establishing emergency plan system of coastal cities in China.

The Three Gorges reservoir area in the Yangtze River economic belt has frequent geological disasters. To assist decision-makers make effective emergency decisions based on their experience, this paper proposes a dynamic geological disaster emergency plan selection scheme based on case-based reasoning and prospect theory. Geological information and data of disaster sites in the Three Gorges reservoir area are collected from the China Geological Environment Monitoring Institute and China Geological Survey of the Ministry of Natural Resources. First, historical geological disasters are analyzed to extract the gene structure characteristics and develop a gene library, from which geological and economic disaster indicators are selected. The indicator values are then divided into several intervals according to their corresponding distributions, which are then processed with a pruning method. Prospect theory is applied to compensate for the differences in decision-making, for which comprehensive foreground values and rank schemes are calculated. A comparison is made between the proposed method and other methods, besides, the Zigui County landslide in Hubei Province is taken as an example to verify the feasibility and effectiveness of the proposed method.

PurposeWhen a railway emergency occurs, it often leads to unexpected consequences, especially for trains of higher speed and larger passenger flow. Therefore, the railway emergency plan, a pre-established plan to deal with emergencies, plays an important role in reducing injuries and losses. However, the existing railway emergency plans remain as plain-text documents, requiring lots of manual work to capture the important regulations. This paper aims to propose a visualized, formal and digital railway emergency plan modeling method based on hierarchical timed Petri net (HTPN), which is also of better interpretability.Design/methodology/approachFirst, the general railway emergency plan was analyzed. Second, the HTPN-based framework model for the general railway emergency plan was proposed. Then, the instantiated model of electric multiple units rescue emergency plan was built by ExSpect, a Petri net simulation tool.FindingsThe experiments show that the proposed model is more digital and of better readability, visualization and performability, and, meanwhile, can generally conform to the practice well, offering a promising reference for future analysis of the optimization of railway emergency plans.Originality/valueThis study offers a promising reference for future analysis of the optimization of railway emergency plans.