The ethical, legal and social issues of pandemics: An analysis from the EU perspective

This book proposes an ethical and legal framework to improve the responses to social issues related not only to the current SARS-CoV-2 pandemic, but also to future pandemics. Its contents cover the issues that are likely to be most controversial in any public health crisis. It starts by discussing non-pharmacological measures, such as the appropriateness of confinement, how to control compliance with public health measures and the ethical, legal and social acceptability of health certificates. Then it turns to issues related to the production, distribution and administration of vaccines, with a particular focus on the design and implementation of vaccination policies. Finally, it analyses the most appropriate criteria to develop a triage, when the situation brings us to this terrible scenario. The analyses presented in this book are based on the ethical and legal frameworks, as well as the social context, of the European Union, and aims to address the main dilemmas faced by any liberal democracy dealing with a pandemic: how to reconcile the defense against a public health crisis together with a respect for fundamental rights and freedoms. The European legal systems have developed a number of conceptual tools designed to ensure that there is no room for arbitrariness in the restrictions introduced by the political power in emergency situations, and this book builds upon these tools. The Ethical, Legal and Social Issues of Pandemics: An Analysis from the EU Perspective is a predominantly practice-oriented book, which will help policy makers to adopt policies that effectively combine public health needs with individual rights and freedoms. It will also help health care givers to understand better the ethical and legal issues involved in their work and citizens, in general, to participate in public decision making in an informed manner. Finally, it will help to design tools that faithfully comply with existing fundamental rights standards. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Research of mortality risk prediction based on hospital admission data for COVID-19 patients.

As COVID-19 continues to spread across the world and causes hundreds of millions of infections and millions of deaths, medical institutions around the world keep facing a crisis of medical runs and shortages of medical resources. In order to study how to effectively predict whether there are risks of death in patients, a variety of machine learning models have been used to learn and predict the clinical demographics and physiological indicators of COVID-19 patients in the United States of America. The results show that the random forest model has the best performance in predicting the risk of death in hospitalized patients with COVID-19, as the COVID-19 patients' mean arterial pressures, ages, C-reactive protein tests' values, values of blood urea nitrogen and their clinical troponin values are the most important implications for their risk of death. Healthcare organizations can use the random forest model to predict the risks of death based on data from patients admitted to a hospital due to COVID-19, or to stratify patients admitted to a hospital due to COVID-19 based on the five key factors this can optimize the diagnosis and treatment process by appropriately arranging ventilators, the intensive care unit and doctors, thus promoting the efficient use of limited medical resources during the COVID-19 pandemic. Healthcare organizations can also establish databases of patient physiological indicators and use similar strategies to deal with other pandemics that may occur in the future, as well as save more lives threatened by infectious diseases. Governments and people also need to take action to prevent possible future pandemics.

Cognitive appraisals and coping strategies of registered nurses in the emergency department combating COVID-19: A scoping review.

OBJECTIVE: Explore the relevant evidence about stress-related cognitive appraisal and coping strategies among registered nurses in the emergency department (EDRNs) coping with the COVID-19 pandemic. METHODS: This scoping review followed the methodological framework of Arksey and O'Malley to map relevant evidence and synthesize the findings. We searched PubMed, EMBASE, CINAHL, Web of Science, and Scopus electronic databases for related studies from inception through February 2, 2022. This review further conducted study selection based on the PRISMA flow diagram and applied Lazarus and Folkman's Psychological Stress and Coping Theory to systematically organize, summarize, and report the findings. FINDINGS: Sixteen studies were included for synthesis. Most of the studies showed that the majority of EDRNs were overwhelmed by the COVID-19 pandemic. Depression, triaging distress, physical exhaustion, and intention to leave ED nursing were cited as major threats to their wellness. Additionally, comprehensive training, a modified triage system, a safe workplace, psychological support, promotion of resilience, and accepting responsibility may help EDRNs cope with pandemic-related challenges effectively. CONCLUSION: The long-lasting pandemic has affected the physical and mental health of EDRNs because they have increased their effort to respond to the outbreak with dynamically adjusted strategies. Future research should address a modified triage system, prolonged psychological issues, emergency healthcare quality, and solutions facing EDRNs during the COVID-19 or related future pandemics. CLINICAL RELEVANCE: EDRNs have experienced physical and psychological challenges during the pandemic. The ED administrators need to take action to ensure EDRNs' safety in the workplace, an up-to-date triage system, and mental health of frontline nurses to provide high-quality emergency care for combating COVID-19.

Integrated clinical judgement and physician responsibility at the time of Covid-19

The essay deals with ethical and professional issues concerning access to intensive care units during the Covid-19 pandemic, when available health-care resources were very scarce. The article criticises the a priori criterion of the age limit proposed by SIAARTI (Italian Society of Anaesthesia, Analge-sia, Resuscitation and Intensive Care), and the a priori criterion of the algorithm for determining which patients should be admitted to intensive care units. As an alternative to the extra-clinical criteria of the age limit and the algorithm, the essay proposes the integrated clinical criterion, which is more respectful of the physicians' professional responsibility. © 2022, Edizioni ETS. All rights reserved.

EVALUATION OF COVID-19 TRIAGE ASSESSMENT SCALE IN PATIENTS ATTENDING THE EMERGENCY DEPARTMENT

Objective: To predict SARS-CoV-2 Polymerase chain reaction (PCR) positivity on the basis of symptoms and contact history of individuals who attend emergency department (ED). Methods: The data for the study which was of a prospective-methodological type were collected from 503 patients who attended ED of a hospital with suspected Coronavirus Disease 2019 (COVID-19) between 02 January - 15 March 2021 and were given PCR test. COVID-19 Visual Triage Scale (VTS) and questionnaire were used for collecting data. Distribution of socio-demographic data was interpreted in frequency, percentage. Independent samples t-test and chi-square test were used to compare quantitative data. Cut-off value of the scale was determined. In the study, sensitivity and specificity of the scale were tested through scoring adopted based on the real time PCR test result. Results: According to the PCR test, 67% of the patients were tested negative while 33% of them were positive. According to COVID-19 VTS, 55% of the patients were found to be negative while 45% were found positive. Validation of scale resulted in 0.65 AUC with a 45% sensitivity and 82% specificity using a cut-off value >4. In its comparison with PCR test, the scale was found to detect 93 real positive and 204 real negative patients. Self-reported fever, cough, sore throat, loss of taste and smell and history of contact with a confirmed COVID-19 case were found to be strong predictors for detecting COVID-19 (p<.05). Conclusions: In the study, sensitivity and specificity of COVID-19 VTS were found to be low. However, for COVID-19 and future pandemics, it is supposed to be useful in sorting patients during the early stages of the pandemic where testing facilities are limited and during the times of fluctuation.