Emergency plan selection for epidemic prevention and control based on cumulative prospect theory and hybrid-information MADM

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.

Challenges faced by nurse managers during the COVID-19 pandemic: an integrative review.

Background: Nurses have crucial roles in caring for patients and preventing the spread of COVID-19. Therefore, nurse managers have a prominent role during the pandemic, being responsible for the support and training of the nursing team to ensure quality care. While performing their duties in this time of fear and uncertainty, nurse managers face several challenges. Aim: To identify the challenges faced by nurse managers during the COVID-19 pandemic. Methods: It is an integrative literature review whose search for articles was carried out in Medline, PubMed and Scopus. Qualitative content analysis was used. Results: Twelve primary research studies were included. Four themes emerged: (1) Workplace demands, (2) Impacts on physical and psychological health, (3) Coping measures and resilience and (4) Recommendations to better support nurse managers in times of crisis. Nurse managers had their roles expanded or completely changed, and they experienced many pressures and stressors in the workplace. Nurse managers also faced physical and psychological health problems. Nurse managers drew on experience; management skills; social media applications; support from family, colleagues and hospital administrators; training, and continuing education to solve the problems that emerged due to the COVID-19 pandemic. Organisations should use collaborative, inclusive and participatory practices for better crisis management. Conclusions: Knowing the experiences of nurse managers during the pandemic period may help health institutions and policymakers better prepare for emergencies.

Policy implementation challenges and the ritualization of public health emergency plans: An investigation of urban communities in Jiangsu Province, China.

Introduction: The COVID-19 pandemic has been a global public health emergency, and countries worldwide have responded to it through a vast array of pre-planned, adaptively devised and ad-hoc measures. In China, public health emergency plans - the plans expected to drive the response to epidemics or pandemics - demonstrated a concerning tendency towards "ritualization." "Ritualization" denotes the practice of public health emergency plans to be reliably developed so that a formal requirement is met, while being implemented selectively or not at all in the emergency response. Methods: This study explored the phenomenon of ritualization by analyzing data from 1485 questionnaires, 60 in-depth interviews and 85 actual public health emergency plans. It used the Smith Policy-Implementation-Processing pattern as its conceptual framework. Results: The study found that the infeasibility of plans, their ineffective implementation by emergency management agencies, the obstructive behaviors of community residents, and the lack of an appropriate policy environment all contributed to the practice of ritualization. Discussion: As China seeks to better respond to COVID-19 and accelerate the recovery of its health system, it is essential to ensure that its public health emergency plans are effectively developed and implemented.

An Epidemic Spreading Simulation and Emergency Management Based on System Dynamics: A Case Study of China’s University Community

The spread of epidemics, especially COVID-19, is having a significant impact on the world. If an epidemic is not properly controlled at the beginning, it is likely to spread rapidly and widely through the coexistence relationship between natural and social systems. A university community is a special, micro-self-organized social system that is densely populated. However, university authorities in such an environment seem to be less cautious in the defence of an epidemic. Currently, there is almost no quantitative research on epidemic spreading and response strategies in universities. In this paper, a case study of a university community is considered for a simulation of an infection evolving after an epidemic outbreak based on the method of system dynamics of the three stages. The results show the following: (1) By improving the speed of the initial emergency response, the total number of patients can be effectively controlled. (2) A quarantine policy helps to slow down the evolution of infection. The higher the isolation ratio, the higher the cost;therefore, the isolation ratio should be optimized. (3) It is important to make emergency plans for controlling epidemic spreading and carry out emergency drills and assessments regularly. According to the results of this study, we suggest an emergency management framework for public health events in university communities.

Supporting Outpatient Care in a Pandemic: Recommendations from the Evaluation of the Bavarian Approach Regional Medical Coordination in the First Phase of the COVID-19 Pandemic.

Background: In the early phase of the COVID-19 pandemic in spring 2020, so-called regional medical coordinators (RMCs) were deployed in Bavaria as part of the declared state of emergency in districts and independent cities to coordinate ambulatory care. The experiences were examined in an evaluation project. One aim of the project was to use the data collected to develop recommendations for supporting ambulatory care in future pandemics. Methods: First, cross-sectional surveys of RMCs and general practitioners (GPs) were conducted in parallel, as well as an interview-based qualitative survey of RMCs, GPs and representatives of authorities and the Bavarian Association of Statutory Health Insurance Physicians (BASHIP). Afterwards, based on the empirical data collected and taking into account available publications and reports, recommendations for decision-makers were developed in a sequential process. Results: The main recommendations are a greater consideration of ambulatory care in catastrophic and emergency situations as well as in the updating of existing emergency and pandemic plans;establishment of systematic advisory and feedback structures for policy-makers and authorities with the involvement of experienced, ambulatory physicians to avoid frictional losses;more efficient use of the existing strength in ambulatory care;pre-definition of persons, responsibilities and tasks on state, district and county level;ensuring adequate supporting infrastructure so that advisory physicians can act efficiently. Conclusions: Although the recommendations were developed in the context of an evaluation project of the Bavarian RMC concept, they could be helpful for future pandemic and emergency situations, also nationwide and outside official disaster situations, if adapted to local conditions. (English) [ FROM AUTHOR] Hintergrund: In der ersten Phase der COVID-19-Pandemie im Frühjahr 2020 wurden in Bayern im Rahmen des ausgerufenen Katastrophenfalls in Landkreisen und kreisfreien Städten sogenannte Versorgungsärzt* innen (VÄ) eingesetzt, um die ambulante Versorgung zu koordinieren. Die Erfahrungen mit diesem Ansatz wurden in einem Evaluationsprojekt untersucht. Ein Ziel des Projektes war es, auf Basis der erhobenen Daten über den Versorgungsarztansatz hinausgehende Empfehlungen zur Unterstützung der ambulanten Versorgung in zukünftigen Pandemien zu erarbeiten. Methoden: Zunächst erfolgten Querschnittsbefragungen von Versorgungsund Hausärzt*innen sowie eine interviewbasierte qualitative Befragung von Versorgungs-, Hausärzt*innen und Vertreter*innen von Behörden und der Kassenärztlichen Vereinigung Bayerns. Auf Basis der erhobenen Daten wurden in einem sequenziellen Prozess Empfehlungen für Entscheidungsträger*innen erarbeitet. Ergebnisse: Hauptempfehlungen sind eine stärkere Berücksichtigung der ambulanten Versorgung in Katastrophen- und Notfallsituationen sowie bei der Aktualisierung vorhandener Katastrophenund Pandemiepläne;der Aufbau systematischer Beratungsund Feedbackstrukturen für Politik und Behörden unter Einbindung erfahrener niedergelassener Ärzt*innen zur Vermeidung von Reibungsverlusten;eine effizientere Nutzung der vorhandenen Stärke des ambulanten Bereichs;Personen, Zuständigkeiten und Aufgaben für die Ebenen Land, Bezirk, Kreis vorab festlegen;angemessene, unterstützende Infrastruktur sicherstellen, damit beratende Ärzt*innen effizient agieren können. Schlussfolgerungen Obwohl die Empfehlungen im Rahmen einer Evaluation des bayerischen Versorgungsarztansatzes entstanden sind, könnten sie, an die lokalen Gegebenheiten angepasst, auch bundesweit und außerhalb des offiziellen Katastrophenfalles für zukünftige Pandemie- und Notfallpläne hilfreich sein. (German) [ FROM AUTHOR] Copyright of ZFA: Zeitschrift für Allgemeinmedizin is the property of Deutscher Aerzte-Verlag GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

UN World Food Programme: Toward Zero Hunger with Analytics

Each year, the United Nations World Food Programme (WFP) provides food assistance to around 100 million people in more than 80 countries. Significant investments over the last decade have put planning and optimization at the forefront of tackling emergencies at WFP. A data-driven approach to managing operations has gradually become the norm and has culminated in the creation of a supply chain planning unit and savings of more than USD 150 million-enough to support two million food-insecure people for an entire year. In this paper, we describe three analytical solutions in detail: the Supply Chain Management Dashboard, which uses descriptive and predictive analytics to bring end-to-end visibility and anticipate operational issues;Optimus, which uses a mixed-integer programming model to simultaneously optimize food basket composition and supply chain planning;and DOTS, which is a data integration platform that helps WFP automate and synchronize complex data flows. Three impact studies for Iraq, South Sudan, and COVID-19 show how these tools have changed the way WFP manages its most complex operations. Through analytics, decision makers are now equipped with the insights they need to manage their operations in the best way, thereby saving and changing the lives of millions and bringing the world one step closer to zero hunger.

The economic impact of COVID-19 based on dazta mining

Our economy, social life and spiritual life have been greatly impacted by a sudden COVID-19. Economies are affected as epidemics spread. In a closely connected and integrated world, the impact of the disease far exceeds mortality. Therefore, governments around the world have been developing emergency plans and aid packages to maintain their economies. In China, we have seen severe lockdowns. This has led to a reduction in consumption and interruption of production. In general, the function of the global supply chain has been disrupted, affecting companies around the world. In this paper, we used machine learning algorithms to build a model to predict the trend and impact of COVID-19. We also conducted a visual analysis of data correlation in order to identify a variety of data hiding characteristics. These characteristics provided us with useful guidance to evaluate the impact of COVID-19 on the economy of various countries. We used data from Kaggle, which included information on the economic impact of COVID-19 from 170 countries. We used a variety of algorithms to determine the trend and impact of the epidemic, including XGBOOST, KNN, SVR, Decision Tree, etc. In terms of MSE index, we found that the value of XGBoost is 2.525 less than KNN, 0.098 less than SVR, and 2.477 less than Decision Tree. Experiments have revealed that XGBOOST results were the best. © 2021 ACM.

A prediction method for population density in key areas

Predicting the population density in certain key areas of the city is of great importance. It helps us rationally deploy urban resources, initiate regional emergency plans, reduce the spread risk of infectious diseases such as Covid-19, predict travel needs of individuals, and build intelligent cities. Although current researches focus on using the data of point-of-interest (POI) and clustering belonged to unsupervised learning to predict the population density of certain neighboring cities to define metropolitan areas, there is almost no discussion about using spatial-temporal models to predict the population density in certain key areas of a city without using actual regional images. We 997 key areas in Beijing and their regional connections into a graph structure and propose a model called Word Embedded Spatial-temporal Graph Convolutional Network (WE-STGCN). WE-STGCN is mainly composed of three parts, which are the Spatial Convolution Layer, the Temporal Convolution Layer, and the Feature Component. Based on the data set provided by the Data Fountain platform, we evaluate the model and compare it with some typical models. Experimental results show that the Spatial Convolution Layer can merge features of the nodes and edges to reflect the spatial correlation, the Temporal Convolution Layer can extract the temporal dependence, and the Feature Component can enhance the importance of other attributes that affect the population density of the area. In general, the WE-STGCN is better than baselines and can complete the work of predicting population density in key areas. © 2021 SPIE.