1000 days of COVID-19: A gender-based long-term investigation into attitudes with regards to vaccination

The coronavirus pandemic has undoubtedly been one of the major recent events that have affected our society at the global level. During this period, unprecedented measures have been imposed worldwide by authorities in an effort to contain the spread of the disease. These measures have led to a worldwide debate among the public, occurring not least within the forum of social media, tapping into pre-existing trends of skepticism, such as vaccine hesitancy. At the same time, it has become apparent that the pandemic affected women and men differently. With these two themes in view, the paper aims to analyze using a data-driven approach the evolution of opinions with regards to vaccination against COVID-19 throughout the entire duration of the pandemic from the point of view of gender. For this analysis, approximately 1,500,000 short user-contributed texts have been retrieved from the popular microblogging platform Twitter, posted between 30 January 2020 and 30 November 2022. Using a machine learning approach, several classifiers have been trained to identify the likely gender (female or male) of the author, as well as the stance of the specific post towards the COVID-19 vaccines (neutral, in favor, or against), achieving 85.69% and 93.64% weighted accuracy measures for each problem, respectively. Based on this analysis, it can be observed that most tweets exhibit a neutral stance, while the number of tweets in favor of vaccination is greater than the number of tweets opposing vaccination, with the distribution varying across time in response to specific events. The subject matter of the tweets varied more between stances than between genders, suggesting that there is no significant difference between the contents of tweets posted by females and males. We also find that while the overall engagement on Twitter with the topic of vaccination against COVID-19 is on the wane, there has been a rise in the number of against tweets continuing into the present. Author

Grey Clustering of the Variations in Reverse Pyramid Boarding Method Considering Pandemic Restrictions

The COVID-19 pandemic has significantly hit the airline industry mostly due to the reduced number of flights between regions, the implementation of different protocols, restrictions, and the reluctance of the passengers to travel by airplane. In this context, the airlines have tried to offer an appropriate environment for their customers by ensuring a safe boarding process while considering the imposed restrictions related to social distancing. According to the literature, the Reverse Pyramid boarding method offers superior results in terms of boarding time and health risks in times of pandemics when compared to other classical airplane boarding methods. As the variations in Reverse Pyramid implementation are numerous, the present paper aims to determine which of these variations can be used when the airplane boarding process is made through the front door of the airplane. For this purpose, an agent-based model is created and used for simulating the variations in the Reverse Pyramid boarding method, while grey clustering is applied for dividing the variations into categories based on their performance. Three performance indicators, as reported in the scientific literature related to airplane boarding in times of COVID-19, are used, namely the boarding time, aisle seat risk, and window seat risk. Different scenarios are presented and analyzed in depth.

COVID-19 Vaccination Opinions in Education-Related Tweets

The coronavirus pandemic has forced authorities to take unprecedented measures, including the temporary closure of business and the instauration of national and regional lockdowns. The educational system, one of the key components of the society, has also been disrupted, as many schools and universities have moved their courses online for prolonged periods. With the introduction of the first vaccine on December 8, 2020, social media users have reacted by posting messages supporting or rejecting the vaccination process. In this context, the present paper aims to analyze the opinions regarding COVID-19 vaccination in education-related tweets. A dataset containing 102,805 English tweets published in the month following the beginning of the vaccination process has been collected. Several classical machine learning and deep learning algorithms have been compared and the best-performing classifier, RoBERTa, has been selected and applied for determining the stance of the collected tweets, as in favor, against or neutral. The evolution of the opinions has been put in correspondence with the main events that have occurred during the analyzed period, while the main discussion topics have been outlined using the Latent Dirichlet Allocation and n-gram analysis. The obtained results can be useful for authorities looking to better understand the opinions of the parents, students, teachers, and general public. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Distribution of Depression among Different Groups and Sub-Groups of Women during the Covid Pandemic an Analysis from an Interdisciplinary Perspective

Objective. In this article, we analyze depression in the female population using interference and descriptive statistics applied to multiple groups and subgroups to better understand depression in the population (pregnant, not pregnant, and newly mothers-6 to 8 weeks) and also analyzing the perspective of suicide during the COVID-19 pandemic. Thus, depending on the analyzed perspective, we have from 2 to 6 study groups. Methods. The analysis was done by applying the Edinburgh Postnatal Depression Scale (EPDS) questionnaire in groups of pregnant women during pregnancy and new mothers (six to eight weeks after birth) and Beck Depression Inventory BDI in all the groups. Results. According to forecasts, all hypothesis where validated . Conclusion(s): An immediate priority of the scientific community should be collecting high-quality data on the mental health effects of the COVID-19 pandemic across the whole population and especially vulnerable groups such as that of pregnant women who were presented in this study. Copyright © 2022 Romanian Society of Legal Medicine.

FORENSIC PERSPECTIVE OF THE COVID PANDEMIC IMPACT ON THE NUMBER OF VICTIMS OF VIOLENCE

Objectives. The present research is a longitudinal study with the aim of highlighting the effect of the pandemic on the frequency of aggressions from a forensic perspective. The hypothesis started from the premise that the aggressions showed an increasing trend during the pandemic, indicating a significant difference between the number of aggressions in the previous period and the number of aggressions in the pandemic and post-pandemic period. Population. The sample of the study consisted of 420 people who were identified by forensic findings at the Institute of Forensic Medicine of Cluj Napoca, as victims of aggression between 2019-2022. The results showed significant differences in the number of aggressions during the pandemic period resulting in an upward trend. Conclusions. The pandemic period had a significant impact on aggressive behaviors, with a tendency of an increased number of aggressions.

BURNOUT EFFECT IMPACT OVER MEDICAL STAFF DURING ACTUAL COVID-19 PANDEMIC CONTEXT

Stress and burnout are considered modern epidemics and their importance for physical health and work capacity was recognized worldwide. Working environment has a very well-known impact, either positive, or negative, over employees’ health. Adverse working conditions may lead to professional burnout, a syndrome generated from chronical stress at the working place, which is characterized by overwhelming exhaustion, negative attitude or lack of commitment. This process can lead to undesirable consequences for the employees, their families, but also in the working environment and organizations. © 2021 Romanian Society of Legal Medicine.

Social distancing in airplane seat assignments for passenger groups

We provide a mixed-integer programming model (MIP) to assign airplane passengers to seats while preserving two types of social distancing: the distance from the passengers' seats to the aisle and the distance among groups of passengers who are not travelling together. The method assigns passengers travelling within a family group to seats near others of the same group. We present a heuristic algorithm to solve the proposed MIP. This algorithm is warm started with an initial seat assignment. Stochastic simulation experiments using the new method confirm that more passengers can be assigned safely to the seats when family groups are considered. For a certain load of passengers, as the percentage of family groups compared to singleton passengers increases, the model can practice social distancing among more passengers from different groups. The proposed model provides a superior seating assignment compared to an airline policy of blocking all middle-seats.

THE EMOTIONAL IMPACT OF COVID-19 ON FORENSIC STAFF

Objective. The present research addresses the respondents' emotional state regarding the fear of SarsCoV-2 contamination and the rational-emotional attitude. Specifically, we are interested in whether catastrophic perceptual-emotional evaluations can intensify maladaptive emotions and behaviors in the case of forensic staff. Methods. The study included 91 participants from the Romanian Forensic Medicine Network, randomized, using DA-COVID Scale19, Delcea C and Siserman C, 2020, in electronic / online version in order to assess the subjective dimension of maladaptive emotions and adaptive emotions. The research period was from October 10, 2020 to December 20, 2020. Results. The scores show the following: forensic pathologists have an adaptive-moderate result;in biologists, general practitioners, pharmacists, nurses, coroners, orderlies and other professional categories we have an adaptive-low result. In the Pearson statistical method, we obtained a significant correlation p <0.01. Conclusions. The results show that respondents did not catastrophically evaluate the Pandemic phenomenon. Moreover, they did not develop any maladaptive emotional and behavioral consequences.

EMOTIONAL DISTRESS AND COPING STRATEGIES OF HEALTH CARE WORKERS DURING COVID-19 PANDEMIC

Stress is perceived as a common, almost inevitable problem that most people face on a daily basis on all levels. In this field, a special sector, due to the multiple implications, is the occupational stress. Despite the theoretical or practical applicative development approached by specialists from various fields over time, the issue of stress still offers, perhaps today more than ever, the possibility and need of new analytical and investigative openings leading to more effective control of it. Mental health puts its mark on the medical act and implicitly on the patients, on their personality. Research demonstrates the many implications of emotional stress in the etiology of various mental and emotional disorders and imbalances that affect the professional performance of health care workers. The new coronavirus known as SARS-CoV-2 is an extremely contagious infectious disease which was declared pandemic by the World Health Organization on the 11th of March, this year. Ever since, during outbursts, health care workers are submitted to an enormous emotional load as they must balance the fundamental principles of their duty to treat patients with their duties to family and loved ones. The aims of our study were to evaluate the levels of stress, emotional distress, and the coping strategies among medical sta., during this public health emergency times.

MARKS OF THE COVID-19 PANDEMIC ON FORENSIC MEDICINE: A SYSTEMATIC REVIEW

Since the end of 2019, humanity has been facing a pandemic generated by the SARS-COV-2 virus, which is felt in most functioning domains. Thus, the goal is to see how much forensic medicine has been affected by this virus and how it has reacted to this pandemic, given the fact that this domain can be of key importance in the fight against COVID-19. A number of 7 articles that met the inclusion and exclusion criteria were thus analysed, initially starting from a number of 414 articles of so, searched in the PubMed database. The analysis of the specialized literature shows us that the number of autopsies performed, as well as of the publications in this sense is a low one.

Grey clustering of the variations in the back-to-front airplane boarding method considering COVID-19 flying restrictions

Purpose The airline industry has been significantly hit by the occurrence of the new coronavirus SARS-CoV-2, facing one of its worst crises in history. In this context, the present paper analyses one of the well-known boarding methods used in practice by the airlines before and during the coronavirus outbreak, namely back-to-front and suggests which variations of this method to use when three passenger boarding groups are considered and a jet bridge connects the airport terminal with the airplane. Design/methodology/approach Based on the importance accorded by the airlines to operational performance, health risks, and passengers' comfort, the variations in three passenger groups back-to-front boarding are divided into three clusters using the grey clustering approach offered by the grey systems theory. Findings Having the clusters based on the selected metrics and considering the social distance among the passengers, airlines can better understand how the variations in back-to-front perform in the new conditions imposed by the novel coronavirus and choose the boarding approach that better fits its policy and goals. Originality/value The paper combines the advantages offered by grey clustering and agent-based modelling for offering to determine which are the best configurations that offer a reduced boarding time, while accounting for reduced passengers' health risk, measured through three indicators: aisle risk, seat risk and type-3 seat interferences and for an increased comfort for the passengers manifested through a continuous walking flow while boarding.