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Since the beginning of the COVID-19 pandemic, many works have been published proposing solutions to the problems that arose in this scenario. In this vein, one of the topics that attracted the most attention is the development of computer-based strategies to detect COVID-19 from thoracic medical imaging, such as chest X-ray (CXR) and computerized tomography scan (CT scan). By searching for works already published on this theme, we can easily find thousands of them. This is partly explained by the fact that the most severe worldwide pandemic emerged amid the technological advances recently achieved, and also considering the technical facilities to deal with the large amount of data produced in this context. Even though several of these works describe important advances, we cannot overlook the fact that others only use well-known methods and techniques without a more relevant and critical contribution. Hence, differentiating the works with the most relevant contributions is not a trivial task. The number of citations obtained by a paper is probably the most straightforward and intuitive way to verify its impact on the research community. Aiming to help researchers in this scenario, we present a review of the top-100 most cited papers in this field of investigation according to the Google Scholar search engine. We evaluate the distribution of the top-100 papers taking into account some important aspects, such as the type of medical imaging explored, learning settings, segmentation strategy, explainable artificial intelligence (XAI), and finally, the dataset and code availability. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive summary of evidence to explore and position the role of serology testing in the context of coronavirus disease 19 (COVID-19) immunization and policy response in the Asia-Pacific (APAC) region. The document builds on a review of academic literature and existing policies followed by a process of discussion, validation, and feedback by a group of six experts. Six countries and territories—Australia, Hong Kong, India, Indonesia, Thailand, and Taiwan—were sampled to highlight the differing contexts and scenarios in the region. The review includes an overview of (1) the impact of the COVID-19 pandemic, including the emergence of Variants of Concern (VOCs), especially Omicron, (2) the introduction of immunization, (3) the available testing options and potential use of serology testing, (4) the landscape of guidelines and recommendations for their use, and (5) the barriers and challenges to implementing serology testing as a tool to support COVID-19 immunization. Based on the findings, the co-authors propose a set of recommendations to resolve knowledge gaps, to include the use of serology testing as part of the policy response, and to ensure adequate means of implementation. This paper's target audience includes members of the academic community, medical societies, health providers and practitioners, and decision-makers. [ABSTRACT FROM AUTHOR]

Although South Africa was the first country to register and roll out oral pre-exposure prophylaxis (PrEP) biomedical human immunodeficiency virus (HIV) prevention intervention in sub-Saharan Africa (SSA), its uptake remains low, particularly among adolescent girls and young women (AGYW). The uptake of PrEP may have worsened during the Coronavirus disease 2019 (COVID-19) pandemic. Some innovative interventions to improve PrEP uptake among AGYW have been implemented. This study aims to evaluate the effectiveness of PrEP innovative interventions implemented during COVID-19 towards reducing the risk of HIV infection among AGYW in South Africa. An exploratory, descriptive design will be conducted to carry out four study objectives. Firstly, to carry out a systematic review of innovative PrEP interventions implemented during COVID-19 in SSA countries. Secondly, to conduct a stakeholder analysis to identify PrEP stakeholders and interview them on their views on the implemented interventions. Thirdly, to assess the implementation outcomes of the innovative interventions using document reviews and Consolidated Framework for Implementation Research. Fourthly, to develop a framework for an improved PrEP service delivery among AGYW. Qualitative data will be captured in ATLAS.ti software (Technical University, Berlin, Germany) version 23 and analysed via thematic analysis. A statistical software package (STATA) version 18 (College Station, TX, USA) will be used to capture quantitative data and analyse them via descriptive analysis. The generated evidence will be used towards the development of framework, guidelines, and policies to strengthen the uptake of, scale-up, and adherence to PrEP among AGYW. [ABSTRACT FROM AUTHOR]

Patients with cancer can be immunocompromised because of their disease and/or due to anticancer therapy. In this population, severe influenza virus infections are associated with an elevated risk of morbidity and mortality. Influenza vaccination is therefore highly recommended in cancer patients, including those receiving anticancer therapy. However, vaccination coverage remains far below the recommended target for vulnerable subjects. Six specialists in oncology, hematology, immunology, and public health/vaccinology convened with the objective of developing strategies, based on evidence and clinical experience, for improving influenza vaccination coverage in cancer patients. This viewpoint provides an overview of current influenza vaccination recommendations in cancer patients, discusses barriers to vaccination coverage, and presents strategies for overcoming said barriers. New immunization issues raised by the COVID-19 pandemic are also addressed. Future directions include improving public education on influenza vaccination, providing the media with accurate information, improving knowledge among healthcare professionals, improving access to vaccines for cancer patients, co-administration of the influenza and COVID-19 vaccines, increased collaboration between oncologists and other health professionals, increased accessibility of digital vaccination registries to specialists, shared information platforms, and promoting immunization campaigns by healthcare systems with the support of scientific societies. [ABSTRACT FROM AUTHOR]

Since the beginning of the COVID-19 pandemic almost two years ago, there have been more than 700,000 scientific papers published on the subject. An individual researcher cannot possibly get acquainted with such a huge text corpus and, therefore, some help from artificial intelligence (AI) is highly needed. We propose the AI-based tool to help researchers navigate the medical papers collections in a meaningful way and extract some knowledge from scientific COVID-19 papers. The main idea of our approach is to get as much semi-structured information from text corpus as possible, using named entity recognition (NER) with a model called PubMedBERT and Text Analytics for Health service, then store the data into NoSQL database for further fast processing and insights generation. Additionally, the contexts in which the entities were used (neutral or negative) are determined. Application of NLP and text-based emotion detection (TBED) methods to COVID-19 text corpus allows us to gain insights on important issues of diagnosis and treatment (such as changes in medical treatment over time, joint treatment strategies using several medications, and the connection between signs and symptoms of coronavirus, etc.). [ABSTRACT FROM AUTHOR]

This paper explores the research trends in the literature about supply chain disruptions published over the last 20 years through a comprehensive review and keyword-based analysis. A sample of 4239 papers retrieved from Scopus was analyzed to identify the key themes covered and the shifts in time of those themes. The results highlight a significant rise in the number of publications on supply chain disruptions since 2021, reflecting the dynamic nature of supply chains and the need to adapt them to increasingly complex scenarios. The findings point out the importance of resilience and risk management but also the progressive shift toward technological innovations and digital tools, as a means to enhance supply chain robustness and sustainability in response to recent global disruptions (e.g., the COVID-19 pandemic, the Russia–Ukraine conflict, and the climate change). From the analyses carried out, interesting opportunities for future research directions are delineated. This study represents a unicum in the scientific literature in terms of the number of articles analyzed, the timespan, as well as the scientometric approach adopted. Finally, the paper highlights the main trends in the field of supply chain disruptions, providing valuable insights for future research activities. [ABSTRACT FROM AUTHOR]

The interest of the research community in happiness and its associated issues has been steadily growing over the years, including during the period marked by the COVID-19 pandemic. The pandemic has brought about significant changes in various aspects of people's lives. In this study, the objective is to analyze the themes and the most significant trends in papers dedicated to happiness in the context of COVID-19 during the period following the onset of the pandemic. To achieve this, the authors have compiled a dataset of papers sourced from Clarivate Analytics' Web of Science Core Collection database, which were extracted using keywords related to both happiness and COVID-19. This database comprises 1932 articles. The researchers have conducted a comprehensive bibliometric analysis of this dataset, providing insights into the most prolific authors in this field, the most frequently cited documents, and the preferred journals for publishing this research. The authors also explore details related to collaboration networks and author clusters. An n-gram analysis is performed on titles, abstracts, keywords, and keywords plus, offering a deeper understanding of the primary research themes. Furthermore, the contributors present a review of the top 10 most cited papers, which completes the analysis and underscores the research trends related to happiness in the context of COVID-19. [ABSTRACT FROM AUTHOR]

Subclinical Myocardial Dysfunction in Patients with Persistent Dyspnea One Year after COVID-19 - Why Should Screening for Cardiovascular Diseases Be Performed? The presence of persistent dyspnea was observed in one-third of the recovered COVID-19 patients, in line with the current data on the long-term evolution of COVID-19 [[3]]. A total of 66 COVID-19 patients without a previous history of cardiorespiratory diseases were evaluated at 12 months for potential subclinical cardiac dysfunction following the acute infection [[2]]. [Extracted from the article]

The article titled "COVID-19 Prevention and Treatment—2nd Edition" is a collection of research and review articles related to various aspects of COVID-19. The articles are divided into four themes: treatment, prevention, mechanism of action, and general and specific conditions of pathology. The treatment section focuses on drug treatment, convalescent plasma use, extracorporeal membrane oxygenation (ECMO), endotracheal intubation (ETI), and the global effectiveness of COVID-19 treatment. The prevention section discusses vaccination efficacy and the identification of antibodies associated with decreased clinical immunity. The mechanism of action section explores biomarkers associated with the loss of taste or olfactory ability. The general and specific conditions of pathology section examines ageusia and swallowing in COVID-19 patients. The collection emphasizes the need for a comprehensive approach to COVID-19 prevention and treatment. [Extracted from the article]

The global impact of the COVID-19 pandemic has been profound, placing significant challenges upon healthcare systems and the world economy. The pervasive presence of illness, uncertainty, and fear has markedly diminished overall life satisfaction. Consequently, sentiment analysis has gained substantial traction among scholars seeking to unravel the emotional and attitudinal dimensions of this crisis. This research endeavors to provide a bibliometric perspective, shedding light on the principal contributors to this emerging field. It seeks to spotlight the academic institutions associated with this research domain, along with identifying the most influential publications in terms of both paper volume and h-index metrics. To this end, we have meticulously curated a dataset comprising 646 papers sourced from the ISI Web of Science database, all centering on the theme of sentiment analysis during the COVID-19 pandemic. Our findings underscore a burgeoning interest exhibited by the academic community in this particular domain, evident in an astonishing annual growth rate of 153.49%. Furthermore, our analysis elucidates key keywords and collaborative networks within the authorship, offering valuable insights into the global proliferation of this thematic pursuit. In addition to this, our analysis encompasses an n-gram investigation across keywords, abstracts, titles, and keyword plus, complemented by an examination of the most frequently cited works. The results gleaned from these endeavors offer crucial perspectives, contribute to the identification of pertinent issues, and provide guidance for informed decision-making. [ABSTRACT FROM AUTHOR]

The spread and resurgence of the SARS-CoV-2 virus (COVID-19 disease) threatens human health and social relations. Prevention of COVID-19 disease partly relies on fabricating low-cost, point-of-care (POC) sensing technology that can rapidly and selectively detect the SARS-CoV-2 virus. We report a colorimetric, paper-based polydiacetylene (PDA) biosensor, designed to detect SARS-CoV-2 spike protein in artificial saliva. Analytical characterizations of the PDA sensor using NMR and FT-IR spectroscopy showed the correct structural elucidation of PCDA-NHS conjugation. The PDA sensor platform containing the N-Hydroxysuccinimide ester of 10, 12-pentacosadiynoic acid (PCDA-NHS) was divided into three experimental PCDA-NHS concentration groups of 10%, 20%, and 30% to optimize the performance of the sensor. The optimal PCDA-NHS molar concentration was determined to be 10%. The PDA sensor works by a color change from blue to red as its colorimetric output when the immobilized antibody binds to the SARS-CoV-2 spike protein in saliva samples. Our results showed that the PDA sensing platform was able to rapidly and qualitatively detect the SARS-CoV-2 spike protein within the concentration range of 1 to 100 ng/mL after four hours of incubation. Further investigation of pH and temperature showed minimal influence on the PDA sensor for the detection of COVID-19 disease. After exposure to the SARS-CoV-2 spike protein, smartphone images of the PDA sensor were used to assess the sensor output by using the red chromatic shift (RCS) of the signal response. These results indicate the potential and practical use of this PDA sensor design for the rapid, colorimetric detection of COVID-19 disease in developing countries with limited access to medical testing. [ABSTRACT FROM AUTHOR]

An early detection tool for latent COVID-19 infections in oncology staff and patients is essential to prevent outbreaks in a cancer center. (1) Background: In this study, we developed and implemented two early detection tools for the radiotherapy area to identify COVID-19 cases opportunely. (2) Methods: Staff and patients answered a questionnaire (electronic and paper surveys, respectively) with clinical and epidemiological information. The data were collected through two online survey tools: Real-Time Tracking (R-Track) and Summary of Factors (S-Facts). Cut-off values were established according to the algorithm models. SARS-CoV-2 qRT-PCR tests confirmed the positive algorithms individuals. (3) Results: Oncology staff members (n = 142) were tested, and 14% (n = 20) were positives for the R-Track algorithm; 75% (n = 15) were qRT-PCR positive. The S-Facts Algorithm identified 7.75% (n = 11) positive oncology staff members, and 81.82% (n = 9) were qRT-PCR positive. Oncology patients (n = 369) were evaluated, and 1.36% (n = 5) were positive for the Algorithm used. The five patients (100%) were confirmed by qRT-PCR. (4) Conclusions: The proposed early detection tools have proved to be a low-cost and efficient tool in a country where qRT-PCR tests and vaccines are insufficient for the population. [ABSTRACT FROM AUTHOR]

In the continuously evolving field of E-government, understanding the breadth and depth of academic research is crucial for advancing governmental digital transformation and policy development. This study employs visual bibliometric analysis, using the Web of Science database to map the evolution trajectory of E-government research from 2000 to 2023. By utilizing CiteSpace for a comprehensive examination of 4536 academic articles, this paper outlines the growth patterns and thematic evolution within the field. The development of the E-government field is delineated into four distinct phases: the budding period (2000–2003), the bottleneck period (2004–2014), the development period (2015–2018), and the growth period (2019–2023), which are each marked by unique thematic shifts and technological advancements. The research results reveal the transformation of research focus in different periods, from the initial focus on the technological means and the electronic transformation of government services, moving on to more complex issues such as E-government acceptance and government transparency and corruption, and ultimately to the current focus on innovation and smart cities. In addition, the paper also clarifies that the research boom that began in 2019 is driven by technological innovation opportunities, the improvement in infrastructure, and multidisciplinary research. By depicting these developmental stages and emerging trends, this study not only unveils past academic efforts but also forecasts future research directions, thereby providing valuable insights for researchers and policymakers aiming to understand and implement effective E-government strategies. [ABSTRACT FROM AUTHOR]

This article investigates the impact of the COVID-19 pandemic on logistics and supply chain processes through a two-phase analysis. First, a literature review maps the existing studies, published from 2021 to 2023 (101 papers), offering a view of the multiple challenges faced by supply chains during the pandemic emergency. The literature analysis makes use of descriptive statistics, thematic classifications and cross-analyses to provide a detailed overview of the issues raised by the COVID-19 pandemic and of the related implications. Second, a case study targeting a logistics operator was conducted, to derive practical insights into the real-world implications of pandemic disruptions. The study highlights the importance of proactive risk management strategies and the role of Industry 4.0 technologies to improve supply chain resilience and sustainability. Hence, this research contributes to a deeper understanding of the impact of the COVID-19 pandemic on logistics and supply chain processes and offers valuable guidance for companies, especially those working in the transport and logistics field. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome (SARS-CoV-2), the causative agent of the global pandemic, which has resulted in more than one million deaths with tens of millions reported cases, requires a fast, accurate, and portable testing mechanism operable in the field environment. Electrochemical sensors, based on paper substrates with portable electrochemical devices, can prove an excellent alternative in mitigating the economic and public health effects of the disease. Herein, we present an impedance biosensor for the detection of the SARS-CoV-2 spike protein utilizing the IgG anti-SARS-CoV-2 spike antibody. This label-free platform utilizing screen-printed electrodes works on the principle of redox reaction impedance of a probe and can detect antigen spikes directly in nasopharyngeal fluid as well as virus samples collected in the universal transport medium (UTM). High conductivity graphene/carbon ink is used for this purpose so as to have a small background impedance that leads to a wider dynamic range of detection. Antibody immobilization onto the electrode surface was conducted through a chemical entity or a biological entity to see their effect; where a biological immobilization can enhance the antibody loading and thereby the sensitivity. In both cases, we were able to have a very low limit of quantification (i.e., 0.25 fg/mL), however, the linear range was 3 orders of magnitude wider for the biological entity-based immobilization. The specificity of the sensor was also tested against high concentrations of H1N1 flu antigens with no appreciable response. The most optimized sensors are used to identify negative and positive COVID-19 samples with great accuracy and precision. [ABSTRACT FROM AUTHOR]

A review of the top 10 cited papers in the journal in 2018-2020 covering such topics as bank profitability, cryptocurrency market trading, and corporate social responsibility is presented.

However, the GCW and GWI values of the two groups, both with and without dyspnea, do not deviate from the normal reference values, which are based on the NORRE study [[2]] and that were underpinned by the authors. The study reports the following echocardiographic differences: Compared to asymptomatic patients, patients with dyspnea presented lower LV constructive work (GCW): 2183.7 ± 487.9 vs. 2483.1 ± 422.4, I p i = 0.024; and a lower global work index (GWI): 1960.0 ± 396.2 vs. 2221.1 ± 407.9, I p i = 0.030. This study compares 23 patients with self-reported dyspnea and 43 without 1 year after hospital admission for COVID-19. [Extracted from the article]

The pandemic of COVID-19 and its widespread transmission have made us realize the importance of early, quick diagnostic tests for facilitating effective cure and management. The primary obstacles encountered were accurately distinguishing COVID-19 from other illnesses including the flu, common cold, etc. While the polymerase chain reaction technique is a robust technique for the determination of SARS-CoV-2 in patients of COVID-19, there arises a high demand for affordable, quick, user-friendly, and precise point-of-care (POC) diagnostic in therapeutic settings. The necessity for available tests with rapid outcomes spurred the advancement of POC tests that are characterized by speed, automation, and high precision and accuracy. Paper-based POC devices have gained increasing interest in recent years because of rapid, low-cost detection without requiring external instruments. At present, microfluidic paper-based analysis devices have garnered public attention and accelerated the development of such POCT for efficient multistep assays. In the current review, our focus will be on the fabrication of detection modules for SARS-CoV-2. Here, we have included a discussion on various strategies for the detection of viral moieties. The compilation of these strategies would offer comprehensive insight into the detection of the causative agent preparedness for future pandemics. We also provide a descriptive outline for paper-based diagnostic platforms, involving the determination mechanisms, as well as a commercial kit for COVID-19 as well as their outlook. [ABSTRACT FROM AUTHOR]

Background and Objectives: Accelerated orthodontics represents a significant shift in dental practice aimed at reducing treatment times while maintaining optimal patient outcomes. This bibliometric analysis evaluated the research landscape of accelerated orthodontics from 2012 to 2023, focusing on publication trends, citation patterns, influential journals, leading institutions, and key contributors. Materials and Methods: A comprehensive search in Scopus identified 600 relevant articles, with the top 50 most-cited papers encompassing systematic reviews, randomized controlled trials, and experimental studies. Key techniques, such as corticotomy and piezocision, have been frequently highlighted for their effectiveness in expediting tooth movement. Results: The analysis revealed fluctuating annual scientific outputs, with notable peaks driven by technological advancements and increased patient demand for quicker orthodontic solutions. However, the production of high-impact papers was hindered by delays in citation accumulation and disruptions caused by the COVID-19 pandemic. Keyword analysis identified critical themes, such as orthodontic tooth movement, malocclusion, and demographic factors, while a global collaboration map underscored extensive international research partnerships. Leading journals included the American Journal of Orthodontics and Dentofacial Orthopedics, and prominent institutions such as the University of California at Los Angeles played significant roles in advancing the field. Conclusions: This study provides a comprehensive overview of the current state of accelerated orthodontics, emphasizing the need for continued research, particularly RCTs, to further refine and validate accelerated orthodontic techniques and improve clinical outcomes. [ABSTRACT FROM AUTHOR]

Measuring the colorimetric signals produced by the biospecific accumulation of colorimetric probes and recording the results is a key feature for next-generation paper-based rapid tests. Manual processing of these tests is time-consuming and prone to a loss of accuracy when interpreting faint and patchy signals. Proprietary, closed-source readers and software companies offering automated smartphone-based assay readings have both been criticized for interoperability issues. Here, we introduce a minimal reader prototype composed of open-source hardware and open-source software that has the benefits of automatic assay quantification while avoiding the interoperability issues associated with closed-source readers. An image-processing algorithm was developed to automate the selection of an optimal region of interest and measure the average pixel intensity. When used to quantify signals produced by lateral flow immunoassays for detecting antibodies against SARS-CoV-2, results obtained with the proposed algorithm were comparable to those obtained with a manual method but with the advantage of improving the precision and accuracy when quantifying small spots or faint and patchy signals. [ABSTRACT FROM AUTHOR]

During the 2022 summer, Europe experienced heatwaves with record temperatures, and a study has argued that they caused about 62,000 deaths between 30 May and 4 September. The total number of excess deaths during the same period was about 137,000, indicating that the heatwaves were a substantial contributor. Not ruling out that explanation entirely, this paper argues that it was unlikely a strong cause. First, if the heatwaves were a strong cause of numerous deaths, one would assume that the older and deprived were relatively likely to die. However, during the 2022 summer heatwaves in England, which were claimed to have caused about 2900 deaths, the oldest age cohort did not have a higher excess death rate than the middle age cohort, and the excess death rate actually decreased with deprivation status. Moreover, Iceland had among Europe's highest excess death rates during the summer, which cannot be attributed to heatwaves. During June, July, and August 2022, comparable southern hemisphere countries furthermore had high excess death rates, which cannot be attributed to heatwaves either, as it was during their winter. Also, Europe's excess death rate was higher during the 2022–2023 winter than during the 2022 summer, and intuitively not attributed to heatwaves, but neither to cold weather, as that winter was abnormally mild. Finally, the paper discusses the puzzling issue that about 56% more women than men, relative to the population, presumably died from the heatwaves. [ABSTRACT FROM AUTHOR]

Purpose: Given the growth in the use of wearable measuring technology, this study aimed to investigate the frequency of writing about wearable monitoring devices in the field of sports sciences and sports-related health professions during the years affected by the COVID-19 pandemic (2020 to 2022). The goal was to observe the number of studies right before the quarantine and during the first years of pandemic. Methodology: A systematic literature analysis was performed in the Web of Science Core Collection (WoS CC) and Scopus databases in March 2023. The filters used in the search were the following: original scientific papers in the English language and open access. The research field was sports sciences in the past three years (2020–2022) in the Wos CC, and health professions and medicine in Scopus. Results: The initial search resulted in 54 studies in the WoS, 16 of which were included in a detailed qualitative analysis, and 297 studies in Scopus with 19 of them analyzed (35 altogether). The keywords used were "fitness watch" (sport watch, smartwatch), "smart shoes", "smart clothing", "smart ring", "smart belt", and "smart glasses". In the past three years, there has been a steady increase in the number of studies using smart monitoring devices to measure their data (nine in 2020, nine in 2021, and seventeen in 2022). Results showed that the most used device is a smartwatch, while the most carried out studies were about physical activity and daily activities of living. Furthermore, there are more studies about measuring devices being used as testing equipment than about device performance in general. Conclusions: This study summarizes various research conducted in the field of sports with the use of wearable measuring devices to determine the frequency of use of such devices in sport studies. [ABSTRACT FROM AUTHOR]

The real estate market constitutes one of the major sectors that was influenced by the COVID-19 pandemic. It is therefore useful to understand the ways in which COVID-19 has changed the dynamics of the real estate market, establishing new trends in different market segments. The health crisis has upset the consolidated "human normality" by spreading new behaviors and involving almost all sectors. Among economic fields, the identification of temporary and permanent impacts on the real estate market is fundamental to assess the consequences worldwide and to evaluate countries' resilience ability. The aim of the research is to provide a systematic literature review on the existent academic insights in order to identify the aspects that have been mainly addressed regarding the real estate market's impacts from COVID-19 and to grasp how the real estate market dynamics have changed. Thus, through five structured steps—from the formulation of research questions formulation to an analysis and discussion of the selected papers for drafting overall conclusions—102 research papers published in the period between the second half of 2020 and the first half of 2023 collected from Scopus and Google Scholar were reviewed and examined. The findings reveal that (i) the housing market has been the most analyzed, (ii) the period between 2021 and 2022 has been the most scientifically prolific, (iii) the US real estate market has been the most studied, (iv) American authors have been the most active on the subject, (v) and the "article" type of research paper has been the most published. These results provide the basis for future research developments on COVID-19 and real estate market dynamics, supporting the implementation of recovery plan strategies and decision-making processes of the market operators for improving the sector. [ABSTRACT FROM AUTHOR]

This paper addresses the significant problem of identifying the relevant background and contextual literature related to deep learning (DL) as an evolving technology in order to provide a comprehensive analysis of the application of DL to the specific problem of pneumonia detection via chest X-ray (CXR) imaging, which is the most common and cost-effective imaging technique available worldwide for pneumonia diagnosis. This paper in particular addresses the key period associated with COVID-19, 2020–2023, to explain, analyze, and systematically evaluate the limitations of approaches and determine their relative levels of effectiveness. The context in which DL is applied as both an aid to and an automated substitute for existing expert radiography professionals, who often have limited availability, is elaborated in detail. The rationale for the undertaken research is provided, along with a justification of the resources adopted and their relevance. This explanatory text and the subsequent analyses are intended to provide sufficient detail of the problem being addressed, existing solutions, and the limitations of these, ranging in detail from the specific to the more general. Indeed, our analysis and evaluation agree with the generally held view that the use of transformers, specifically, vision transformers (ViTs), is the most promising technique for obtaining further effective results in the area of pneumonia detection using CXR images. However, ViTs require extensive further research to address several limitations, specifically the following: biased CXR datasets, data and code availability, the ease with which a model can be explained, systematic methods of accurate model comparison, the notion of class imbalance in CXR datasets, and the possibility of adversarial attacks, the latter of which remains an area of fundamental research. [ABSTRACT FROM AUTHOR]

This document is a comment on a review paper titled "Could Selenium Supplementation Prevent COVID-19? A Comprehensive Review of Available Studies." The authors of the comment are experienced selenium researchers who take issue with the assessments made in the review. They argue that the review is not comprehensive and fails to include important studies that support the association between selenium and COVID-19 outcomes. The authors also address specific criticisms made by the reviewers regarding their own work and highlight the importance of further research into the role of selenium in COVID-19. [Extracted from the article]

This document is an editorial from the journal Biomedicines, discussing a special issue on the latest research in post-COVID conditions. The COVID-19 pandemic has led to a significant increase in research, with a focus on managing acute cases and preventing the spread of the virus. However, there is now a growing concern about the development of long-lasting symptoms after the acute infection, known as long-COVID or post-COVID-19 condition. This special issue includes fourteen papers covering topics such as the treatment of post-COVID-19 condition, the impact of SARS-CoV-2 infection on neonates, risk factors for severe COVID-19, and the phenotyping of post-COVID pain. The papers discuss various treatment strategies, the potential transmission of the virus during pregnancy, risk factors for severe disease, and different types of post-COVID pain. Overall, this special issue provides valuable insights into the understanding and management of post-COVID conditions. [Extracted from the article]

The present paper investigates the relationship between stock prices, credit ratings, and ESG scores for banks internationally. First, it describes stock prices and ESG scores at an annual frequency, as well as stock price and credit risk at a daily frequency. The relationships between (a) stock price and credit rating returns with ESG score returns and (b) among ESG scores are examined by pairwise annual correlation, and daily correlations are examined between price and credit rating returns. Furthermore, Granger causality is used to examine the relationships between the following: (a) price and ESG score annual returns; (b) price and credit rating daily returns; and (c) total and pillar annual ESG scores. This study makes a significant contribution to the literature by providing a detailed temporal analysis using both annual and daily data frequencies, which is relatively rare in the field. There is evidence of statistically and empirically important relations in the form of pairwise correlations. The regressions reveal a low significance of few ESG score changes in explaining credit rating changes. A unique aspect of this paper is the comprehensive analysis of 16 granular ESG scores, including overall scores, pillar scores, and sub-scores, allowing for a multi-faceted understanding of how specific ESG factors impact financial metrics. We found evidence of the significance of COVID-19 in all research questions. Additionally, this paper highlights the impact of the COVID-19 pandemic on the relationships between ESG scores, credit ratings, and stock prices, offering timely insights into the heightened importance and volatility of ESG factors during crisis periods. Future research needs to shed more light on this relationship, however. [ABSTRACT FROM AUTHOR]

Introduction: Dermatologists had to face several challenges during the COVID-19 pandemic. In this scenario, a large amount of data has been produced and published. Objectives: We present a literature analysis of publications on COVID-19 in the dermatology field in the first year of the pandemic. Methods: The research was carried out by searching the PubMed database using keywords related to "COVID-19" combined with the keyword "Dermatology" in the "affiliation" search field and collecting articles published from February 2020 to December 2020. Results: A total of 816 publications from 57 countries were retrieved. Overall, publications increased notably along the timespan considered in this study and appeared to be closely linked to pandemic progression in different countries. In addition, article types (i.e., commentaries, case reports, original research) appeared to be strictly influenced by the pandemic's progression. However, the number and category of these publications may raise questions regarding the scientific relevance of the messages reported. Conclusions: Our analysis provides a descriptive quantitative analysis and suggests that publications do not always respond to real scientific needs but are sometimes linked to a need/opportunity for publication. [ABSTRACT FROM AUTHOR]

The aim of this concept paper is the description of a new tool to support institutions in the implementation of targeted countermeasures, based on quantitative and multi-scale elements, for the fight and prevention of emergencies, such as the current COVID-19 pandemic. The tool is a cloud-based centralized system; a multi-user platform that relies on artificial intelligence (AI) algorithms for the processing of heterogeneous data, which can produce as an output the level of risk. The model includes a specific neural network which is first trained to learn the correlations between selected inputs, related to the case of interest: environmental variables (chemical–physical, such as meteorological), human activity (such as traffic and crowding), level of pollution (in particular the concentration of particulate matter) and epidemiological variables related to the evolution of the contagion. The tool realized in the first phase of the project will serve later both as a decision support system (DSS) with predictive capacity, when fed by the actual measured data, and as a simulation bench performing the tuning of certain input values, to identify which of them led to a decrease in the degree of risk. In this way, we aimed to design different scenarios to compare different restrictive strategies and the actual expected benefits, to adopt measures sized to the actual needs, adapted to the specific areas of analysis and useful for safeguarding human health; and we compared the economic and social impacts of the choices. Although ours is a concept paper, some preliminary analyses have been shown, and two different case studies are presented, whose results have highlighted a correlation between NO 2 , mobility and COVID-19 data. However, given the complexity of the virus diffusion mechanism, linked to air pollutants but also to many other factors, these preliminary studies confirmed the need, on the one hand, to carry out more in-depth analyses, and on the other, to use AI algorithms to capture the hidden relationships among the huge amounts of data to process. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, scientific collaboration has profoundly influenced the sustainability of human science. The pandemic has exposed the fragility of the global health system, forcing various research institutions to cooperate more actively and giving rise to a pressing inquiry regarding its implications on the patterns of scientific institution collaboration. With this in mind, we investigate 2,252,016 scientific papers between 2019 and 2020 to study this issue from an institution cooperation view. Specifically, by proposing a novel weighted cooperation network and utilizing institution cooperation freshness, we investigate different collaboration patterns and strategies when institutions respond to the pandemic. The results show that the crisis generally promotes both fresh and stable cooperation relationships among institutions, and different fields (e.g., STEM and Humanities) demonstrate different collaboration patterns. During the pandemic, institutions with a strong influence have a variety of cooperation strategies, while institutions with a low influence prefer a conservative strategy. Moreover, institutions participating in COVID-19 research are very cautious in choosing partners, which may originate from the risk of cooperation, e.g., the fluctuation of influence, and the causal inference results also verify this conclusion. Overall, our study reveals the impact of the COVID-19 pandemic on scientific research work, which may pave the way for designing policy when other global crises occur again. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic affected nearly all strata of life, including scientific activities. Implementation of nationwide lockdowns, closures of universities, and other measures significantly limiting social mobility precluded field and laboratory research from being pursued at a pre-pandemic pace. On the other hand, working from home could translate into higher productivity of researchers in terms of publication output, ultimately affecting the journals' metrics. This effect has been well evidenced in the biomedical field, but whether it also occurred in aquatic sciences has not been explored. Therefore, this study aimed to analyze and compare various metrics of journals classified in the Scopus evaluations in 2019 (encompassing 2016–2019, the pre-pandemic period) and 2022 (covering 2019–2022, the pandemic period) within three subjects: aquatic science, oceanography, and water science and technology. In general, the number of journals classified into the considered categories increased in 2022 by 12%, and the majority (78%) experienced an increase in the CiteScore metric. The total published articles and received citations also significantly increased in 2022 by 17.5% and 63.5%, respectively, and were even higher in the case of open access journals—69% and 145%, respectively. The overall share of cited articles in the considered period was higher by 5% than in the 2019 Scopus evaluation and by 7% in the case of open access periodicals. However, source normalized impact per paper (SNIP) and the SCImago journal rank (SJR) values decreased by 7% and 8%, respectively. The highest share of citations was generated by Water Research, Water, and the Journal of Hydrology, and the highest number of articles was published by Water, Frontiers in Marine Science, and Desalination and Water Treatment. Only five of the COVID-19-related papers published in journals with the highest CiteScore and total number of citations received more than 200 citations, but their contribution to citations received by the journals was not high. In summary, the present study's findings indicate the high potential of the field dedicated to water sciences to adapt in a period challenged by an infectious disease pandemic. However, they do not exclude the adverse effect that this period could have on the activities of individual scientists and research teams. [ABSTRACT FROM AUTHOR]

COVID-19 is an enveloped virus with a single-stranded R N A genome. The surface of the virus contains spike proteins, which enable the virus to attach to host cells and enter the interior of the cells. After entering the cell, the virus exploits the host cell's mechanisms for replication and dissemination. Since the end of 2019, COVID-19 has spread rapidly around the world, leading to a large-scale epidemic. In response to the COVID-19 pandemic, the global scientific community quickly launched vaccine research and development. Vaccination is regarded as a crucial strategy for controlling viral transmission and mitigating severe cases. In this paper, we propose a novel mathematical model for COVID-19 infection incorporating vaccine-induced immunization failure. As a cornerstone of infectious disease prevention measures, vaccination stands as the most effective and efficient strategy for curtailing disease transmission. Nevertheless, even with vaccination, the occurrence of vaccine immunization failure is not uncommon. This necessitates a comprehensive understanding and consideration of vaccine effectiveness in epidemiological models and public health strategies. In this paper, the basic regeneration number is calculated by the next generation matrix method, and the local and global asymptotic stability of disease-free equilibrium point and endemic equilibrium point are proven by methods such as the Routh–Hurwitz criterion and Lyapunov functions. Additionally, we conduct fractional-order numerical simulations to verify that order 0.86 provides the best fit with COVID-19 data. This study sheds light on the roles of immunization failure and fractional-order control. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic was a health, economic, and financial crisis. The aviation sector was one of the most severely hit. Despite the extensive literature on this, COVID-Finance has been focused on stock returns, neglecting what could be learnt from the spreads of airlines' credit default swaps (CDSs). This would seem of the utmost importance, given the epicenter of the crisis within the credit market. In this paper, an in-depth analysis of airlines' CDS spreads is conducted. It is found that they were severely hit, for all airlines studied. However, the results of the PSY test showed that speculative trading led the surge, as explosive roots were found in the spreads of all these aviation firms. The dramatic increase in CDS spreads has contributed to already high borrowing costs for airlines. Our results suggest that aviation bail outs have helped to mitigate spreads' explosiveness. Monetary policy measures have also limited, albeit indirectly, the funding risk posed by the government bail outs. By the end of March 2021, spreads were no longer explosive, and were approaching, at highly heterogeneous paces, their pre-pandemic values. Notwithstanding, airlines' stock prices have been notably resistant to recovery. [ABSTRACT FROM AUTHOR]

The paper is set within the methodological framework of the Territorial Impact Assessment (TIA) process, which is an instrument designed to facilitate sustainable and cohesive policy-making choices at the European level. The article is developed within the context of a European H2020-RICE cooperative project, which utilises the STeMA (Sustainable Territorial Economic/Environmental Management Approach) TIA methodology to investigate the potential relationship between statistical economic indicators, specifically Gross Domestic Product, and related parameters (metadata), and Earth Observation (EO) data. The objective is to provide evidence of socioeconomic trends during the Coronavirus 2019 pandemic in the Lazio Region (Italy), with a particular focus on the metropolitan area of the Rome capital city Rome. In line with the pertinent European context and the scientific literature on the subject, the paper examines the potential for combining classical and Earth observation indicators to assess macroeconomic dimensions of development, specifically in terms of gross domestic product (GDP). The results of the analysis indicate the presence of certain correlations between grey data and EO information. The STeMA-TIA approach allows for the measurement and correlation of both qualitative and quantitative statistical indicators with typological functional areas (in accordance with European Commission-EC and Committee of Ministers responsible for Spatial/Regional Planning—CEMAT guidance) at the NUTS (Nomenclature des unités territoriales statistiques) 2 and 3 levels. This facilitates the territorialisation of information, enabling the indirect comparison of data with satellite data and economic trends. A time series of data was gathered and organised for the purpose of facilitating comparison between different periods, beginning with 2019 and extending to the present day. In order to measure and monitor the evolution of the selected territorial economies (the Lazio Region), a synthetic index (or composite indicator) was developed in the economic and epidemic dimensions. This index combines single values of indicators according to a specific STeMA methodology. It is important to note that there are some critical observations to be made about the impact on GDP, due to the discrepancy between the indicators in the two fields of observation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to apply Bronfenbrenner's ecological systems theory to explore the literature on how Conditional Cash Transfer (CCT) and Unconditional Cash Transfer (UCT) programs might support positive mental health outcomes. The paper begins with transnational considerations of stress, such as poverty and COVID-19, and their impact on mental health. Bronfenbrenner's theory is applied to better understand the mechanisms by which CCT and UCT programs can potentially lead to positive outcomes for children and families who face such stressors. The implications of cash transfer programs are subsequently discussed in terms of how they might promote positive mental health outcomes among families globally. This theoretical application paper concludes with a call for transnational research to explore connections between cash transfer programs and mental health outcomes for children/adolescents and their parents/caregivers. [ABSTRACT FROM AUTHOR]

Systematic inflammatory response syndrome (SIRS) and the accompanying sepsis pose a huge threat to human health worldwide. Heparin is a part of the standard supportive care for the disease. However, the molecular mechanism is not fully understood yet, and the potential signaling pathways that play key roles have not yet been elucidated. In this paper, the main findings regarding the molecular mechanisms associated with the beneficial effects of heparin, including inhibiting HMGB-1-driven inflammation reactions, histone-induced toxicity, thrombo-inflammatory response control and the new emerging mechanisms are concluded. To set up the link between the preclinical research and the clinical effects, the outcomes of the clinical trials are summarized. Then, the structure and function relationship of heparin is discussed. By providing an updated analysis of the above results, the paper highlights the feasibility of heparin as a possible alternative for sepsis prophylaxis and therapy. [ABSTRACT FROM AUTHOR]

Comparing hospitals using multicriteria methods facilitates a thorough assessment of performance across multiple dimensions, supports informed decision-making, promotes accountability, and drives continuous improvement in healthcare delivery. This paper aims to apply multicriteria methods to assess hospitals in Slovakia in the pre-crisis (2019), crisis (2021), and post-crisis (2023) periods of the COVID-19 pandemic. The assessment is conducted using four multicriteria methods, i.e., a ranking method, scoring method, normed variable method, and TOPSIS method, and nonmetric multidimensional scaling (NMDS). The research sample comprises a group of hospitals classified under the sector (SK) NACE 86.1—Hospital activities. Seven indicators (financial and non-financial) were entered into the analysis. The results show that the agreement among the employed multicriteria evaluation methods was statistically significant. Moreover, the findings demonstrate that Slovak hospital rankings based on the selected criteria vary over time. The perfect quality of the NMDS models, as indicated by stress values below 0.025, shows that NMDS analysis provides a highly accurate and reliable representation of hospital comparisons. By combining multicriteria methods with NMDS, we harness the strengths of each approach to improve decision-making and achieve greater insights into intricate datasets. A comprehensive assessment of hospitals allows for the identification of the system's strengths and weaknesses, which can be utilized to formulate new improvement strategies. As an additional benefit, this paper includes a bibliometric analysis, offering a systematic evaluation and synthesis of existing research on multicriteria evaluation methods. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic brought into prominence several emergent medical and surgical entities, but, also, it served as trigger and contributor for numerous apparently unrelated ailments such as arterial and venous thromboembolic complications. Additional risk factors for these thrombotic traits may be concurrent (known or unknown) malignancies, including at hepatic level. Among these, cholangiocarcinoma (CCA), a rare cancer of intra- and extra-hepatic biliary ducts, represents a very aggressive condition that typically associates local and distant advanced stages on first presentation requiring a prompt diagnosis and a stratified management. This neoplasia has been reported to present a large spectrum of paraneoplastic syndromes in terms of dermatologic, renal, systemic, neurologic, endocrine, and cardiovascular settings, that, overall, are exceptional in their epidemiologic impact when compared to other cancers. Our aim was to introduce a most unusual case of CCA-associated distant thrombosis in a male adult who initially was considered to experience COVID-19-related thrombotic features while having a history of obesity and bariatric surgery. This is a hybrid type of paper: this clinical vignette is accompanied by two distinct sample-focused analyses as a basis for discussion; they each had different methods depending on their current level of statistical evidence. We only included English-published articles in PubMed, as follows: Firstly, we conducted a search of reports similar to the present case, regarding distant vein thrombosis in CCA, from inception until the present time. We performed a literature search using the keywords "cholangiocarcinoma", "thrombosis", and "Trousseau's syndrome" and identified 20 cases across 19 original papers; hence, the current level of evidence remains very low Secondly, we searched for the highest level of statistical evidence concerning the diagnosis of venous thrombosis/thromboembolism in patients who underwent COVID-19 infection (key search terms were "COVID-19", alternatively, "coronavirus", and "SARS-CoV-2", and "thrombosis", alternatively, "thromboembolism") and included the most recent systematic reviews and meta-analyses that were published in 2024 (from 1 January 2024 until 8 July 2024). After excluding data on vaccination against coronavirus or long COVID-19 syndrome, we identified six such articles. To conclude, we presented a probably unique case of malignancy with an initial manifestation consisting of recurrent superficial vein thrombosis under anticoagulation therapy, with no gastrointestinal manifestations, in a patient with a notable history for multiple episodes of SARS-CoV-2 infection and a prior endocrine (gastric) surgery. To our knowledge, this is the first identification of a CCA under these specific circumstances. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has affected all Sustainable Development Goals (SDGs), leading to setbacks in various Latin American countries. In Brazil, progress in technological development and the adoption of sustainable practices by organizations has been significantly hindered. Yet, there remains a limited understanding of the long-term impacts on the country's development, and a structured national plan for recovery and resuming progress toward the SDGs is lacking. This paper aims to investigate the repercussions of COVID-19 on SDGs 9 (industry, innovation, and infrastructure) and 12 (sustainable consumption and production) in the context of a latecomer country such as Brazil. This study adopted the Delphi-based scenario and Fuzzy Delphi approach and involved the participation of 15 sustainability experts with extensive experience in the Brazilian industrial sector. The findings elucidate the long-term impacts of the pandemic on these SDGs, focusing on Brazil's socioeconomic landscape and developmental challenges. The pandemic worsened pre-existing issues, hindering infrastructure modernization, technological investment, and sustainable practices. Insufficient research funding, industry modernization, and small business integration further impede progress. Additionally, the paper identifies implications for research, companies, and public policies, aiming to provide actionable insights for fostering sustainable development in the post-pandemic era. [ABSTRACT FROM AUTHOR]

We examine the financial performance of the forest products industry in the initial phase of the COVID-19 pandemic, employing data for publicly trading companies in the industry globally. We first examine the market investor reaction to the declaration of a pandemic by the World Health Organization (WHO) in March 2020 by conducting an event-study analysis. Then, we analyze medium-term changes in stock returns and their systematic risk by an econometric estimation of the capital asset pricing model. Our event-study analysis of the forest products industry shows that the forestry subsector was impacted more than the paper subsector when the WHO declared the pandemic. The effect was most prominent in North America. We find that the systematic risk for the forestry subsector tended to increase during 2020, until October. Again, this effect was most clear in North America. Conversely, the impact on the paper subsector was more stable. [ABSTRACT FROM AUTHOR]

The author believes that the principles of statistical methods for vaccine safety can be divided into three categories: comparison of adverse event incidence rates between vaccinated and unvaccinated groups, analysis of incidentality in the vaccinated group, and a combination of both. The first category includes the cohort study; the second, the self-controlled risk interval design (SCRI); and the third, the self-controlled case series method. A single p-value alone should not determine a scientific conclusion, and analysis should be performed using multiple statistical methods with different principles. The author believes that using both the cohort study and the SCRI for analysis is the best method to assess vaccine safety. When the cohort study may not detect a significant difference owing to a low incidence rate of an adverse event in the vaccinated group or a high one in the unvaccinated group, the SCRI may detect it. Because vaccines must have a higher level of safety than the pharmaceuticals used for treatment, vaccine safety is advisable to be assessed using methods that can detect a significant difference even for any value of the incidence rate of an adverse event. The author believes that the analyses of COVID-19 vaccine safety have areas for improvement because the proportion of papers that used the cohort study and the SCRI was negligible. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic disrupted global food waste patterns through unanticipated shifts in composition and quantities. This review explores the impacts of COVID-19 on food waste generation and management approaches in the Near East and North Africa (NENA) region during the recovery phase. This paper comprehensively explores food loss and waste in the NENA region. It presents a detailed analysis of pandemic-induced changes in household food waste behaviors, analyses the integration of circular economy principles in recovery strategies and policy implications, and outlines potential avenues for future research in this critical area. The key findings are threefold: First, this study reaffirms that food waste is a critical challenge in NENA, contributing to food insecurity, water scarcity, and environmental issues. Second, the pandemic catalyzed a dichotomy in consumer behaviors—panic buying initially increased waste, while hardship measures later encouraged sustainable waste reduction practices like meal planning and leftover use. Third, adopting a circular economy approach holds potential, yet its implementation remains limited in terms of curbing food waste and promoting sustainability in NENA. Overall, while the pandemic accentuated the urgency of tackling food waste, it also stimulated innovative policy thinking and strategic planning for building more resilient food systems. This paper concludes that leveraging pandemic-driven sustainability mindsets while addressing systemic drivers of waste will be key to mitigating food waste and its impacts moving forward. This paper offers timely insights into the evolving food waste management landscape in NENA, underscoring the need for integrated policies to navigate post-pandemic recovery effectively. [ABSTRACT FROM AUTHOR]

The essay outlines a four-phase triage process made by a fictive Talmudic rabbi working on an equally fictive hospital COVID-19 ward. The rabbi bases his decision on four different Talmudic texts, proceeding one by one, with each text building on the preceding one, until he is ready to allocate his scarce medical resources to one of the patients, thus being forced to deny them to others. Along the way, the paper will examine how this Talmudic reasoning can also be applied to the patient, or even a potential patient, clarifying the demands of the individual's ethical responsibility to avoid triage situations in the first place through social distancing and even more so through getting vaccinated. The paper argues that the rabbi has a number of Talmudic tools at hand that make his decision easier, not because he strictly follows Jewish law, but because of the rich experience standing behind Jewish legal traditions, making a universally valid ethical justification of difficult decisions possible. The essay proposes that including such theological material in triage guidelines would help make those decisions more acceptable in the long run, especially for societies in which religious traditions still play a certain role in the cultural consciousness. [ABSTRACT FROM AUTHOR]

Increasing local fiscal pressure and insufficient enterprise environmental protection investment are considerable problems in China. Based on the data of A-share-listed companies in heavily polluting industries in China from 2015 to 2021, this paper uses COVID-19 as an exogenous shock of local fiscal pressure and investigates the impact of local fiscal pressure on enterprise environmental protection investment by the continuous DID method. The study found that local fiscal pressure significantly reduces enterprise environmental protection investment and has a greater impact on non-state-owned enterprises, large enterprises, enterprises located in the "two-control-zone" cities and enterprises located in cities with low fiscal self-sufficiency rates. The mechanism of analysis shows that local governments ease fiscal pressure by "increasing revenue" and "cutting expenditure". The former increases the non-tax burden of enterprises, while the latter reduces enterprise environmental protection subsidies, which leads to a decrease in environmental protection investment. The findings of this paper indicate that it is necessary to focus on solving the local fiscal pressure dilemma to increase green investment and achieve green development. [ABSTRACT FROM AUTHOR]

Polypharmacy, the use of multiple and potentially inappropriate medications, is an increasing problem among older adults. The global polypharmacy prevalence is 34.6% in patients with COVID-19, and polypharmacy in COVID-19 increases with age. The present paper proposes that polypharmacy in older adults with COVID-19 and other comorbid conditions is linked to the medication outcome reporting bias of randomized controlled trials. Outcome reporting bias can occur when treatment efficacy is reported as relative risk reductions, which overestimates medication benefits and exaggerates disease/illness risk reductions compared to unreported absolute risk reductions. The comorbidities common in patients with COVID-19 include high blood pressure, cardiovascular disease, dementia or cerebrovascular disease, and diabetes. Accordingly, the present paper reassesses the relative and absolute risk reductions in clinical trials from a small convenience sample of antihypertension, statin, anticoagulant, and antihyperglycemic medications. Examples demonstrate a wide gap between reported relative risk reductions and unreported absolute risk reductions in medication clinical trials. This paper concludes that medication clinical trial outcome reporting bias is an important upstream factor that contributes to biased medication benefits and poor clinical decision making, leading to polypharmacy in older adults with COVID-19 and other comorbid conditions. Public health campaigns are urgently needed to educate the public about the link between polypharmacy and medication outcome reporting bias. [ABSTRACT FROM AUTHOR]

Students' anxiety and behavioural changes while using different examination methods (paper, PC, and mobile exam platforms (MEPs)) were estimated. The influence of academic majors and gender was also determined by answering the following questions: How do anxiety and behavioural changes vary among students using different exam methods? How do students' anxiety levels vary according to academic majors and gender while using different exam methods? A survey was conducted with 826 students enrolled in eight colleges at King Faisal University in Saudi Arabia. The results revealed less anxiety and fewer harmful behavioural changes among students using MEPs compared with other methods. Furthermore, less anxiety and fewer behavioural changes were observed among health and science majors than humanities and social science majors and among female students than male students while using MEPS. Therefore, MEPs should be gradually adopted by higher education institutions in Saudi Arabia, especially for humanities and social science majors and for male students. Furthermore, researchers and decision-makers should find unique solutions to reduce the positive correlation between anxiety and behavioural changes among health and science majors and female students toward MEPs. This can be achieved by identifying obstacles and introducing modern solutions, such as AI-generated exams, among others. [ABSTRACT FROM AUTHOR]

During the last three years, numerous research papers have been reported which use social media data to explore several issues related to the COVID-19 pandemic. Bibliometric methods in this work are used to analyze 1427 peer-reviewed documents from the last three years extracted from the Web of Science database. The results of this study show that there was high growth in publications in open access journals with an annual rate reaching 19.3% and they also identify the top cited journals and research papers. The thematic analysis of papers shows that research topics related to social media for surveillance and monitoring of public attitudes and perceptions, mental health, misinformation, and fake news are important and well-developed, whereas topics related to distance-learning education with social media are emerging. The results also show that the USA, China, and the UK have published many papers and received a high number of citations because of their strong international collaboration. [ABSTRACT FROM AUTHOR]

Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals' evolution of the disease. [ABSTRACT FROM AUTHOR]

This paper studies the performance of machine learning predictions for the counterfactual analysis of air transport. It is motivated by the dynamic and universally regulated international air transport market, where ex post policy evaluations usually lack counterfactual control scenarios. As an empirical example, this paper studies the impact of the COVID-19 pandemic on airfares in 2020 as the difference between predicted and actual airfares. Airfares are important from a policy makers' perspective, as air transport is crucial for mobility. From a methodological point of view, airfares are also of particular interest given their dynamic character, which makes them challenging for prediction. This paper adopts a novel multi-step prediction technique with walk-forward validation to increase the transparency of the model's predictive quality. For the analysis, the universe of worldwide airline bookings is combined with detailed airline information. The results show that machine learning with walk-forward validation is powerful for the counterfactual analysis of airfares. [ABSTRACT FROM AUTHOR]