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Key summary points: Aim: To describe the evidence on the usefulness of a Comprehensive Geriatric Assessment (CGA)-based approach during the COVID-19 pandemic. Findings: The multidimensional, CGA-based approach allows better identification of individual risk profiles and frailty status of infected, recovered but with a post-COVID-19 condition, and non-infected older adults. Message: Capturing older patients' needs through CGA may offer the possibility to guide clinical decision and implement personalized medicine. Purpose: The COVID-19 pandemic has been a dramatic trigger that has challenged the intrinsic capacity of older adults and of society. Due to the consequences for the older population worldwide, the Special Interest Group on Comprehensive Geriatric Assessment (CGA) of the European Geriatric Medicine Society (EuGMS) took the initiative of collecting evidence on the usefulness of the CGA-based multidimensional approach to older people during the COVID-19 pandemic. Methods: A narrative review of the most relevant articles published between January 2020 and November 2022 that focused on the multidimensional assessment of older adults during the COVID-19 pandemic. Results: Current evidence supports the critical role of the multidimensional approach to identify older adults hospitalized with COVID-19 at higher risk of longer hospitalization, functional decline, and short-term mortality. This approach appears to also be pivotal for the adequate stratification and management of the post-COVID condition as well as for the adoption of preventive measures (e.g., vaccinations, healthy lifestyle) among non-infected individuals. Conclusion: Collecting information on multiple health domains (e.g., functional, cognitive, nutritional, social status, mobility, comorbidities, and polypharmacy) provides a better understanding of the intrinsic capacities and resilience of older adults affected by SARS-CoV-2 infection. The EuGMS SIG on CGA endorses the adoption of the multidimensional approach to guide the clinical management of older adults during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Unlike in developed countries, most public toilets in China do not provide toilet paper onsite and users must bring their toilet paper. Moreover, an open waste bin is placed in each user's cubicle to collect used toilet paper and tissues. Such practices, which are common in East Asia and central America, have induced a dilemma of toilet paper disposal because some municipalities have removed waste bins from public toilets to prevent virus transmission by fecal matter. As a consequence, users were forced to flush down their used toilet paper and tissues. Yet, it is unknown whether standard toilet paper can be flushed easily without causing issues in sewer operations. Here, we surveyed the conditions of toilets in university campus and other public facilities in different regions across China. We also evaluated the disintegration characteristics of toilet paper products both by conducting online surveys and by physical disintegration experiments. We found that only 15% of toilets provided toilet paper, while open waste bins occurred at nearly all sites. Further, our survey indicated that 82% of toilet paper products sold in China did not give any indication on their flushability, whereas 77% of US products did. Disintegration results showed that none of the five popular, best-selling toilet paper products passed the flushability standard. We propose strategies to solve the current toilet paper dilemma in developing communities. [ABSTRACT FROM AUTHOR]

To study the impact of the COVID-19 pandemic on journal processing times before publication in the field of otolaryngology-head and neck surgery (ORL-HNS). Online search of original papers published in selected ORL-HNS journals in terms of times from submission to acceptance (S-A), acceptance to first online publication (A-P), and submission to online publication (S-P). Papers were divided into those published in the pre-COVID-19 era and those during the COVID-19 era. The latter were further divided into unrelated to COVID-19 and related to COVID-19. A total of 487 articles from 5 selected ORL-HNS journals were included, of which 236 (48.5%) were published during the pre-COVID-19 era and 251 (51.5%) were published during the COVID-19 era. Among them, 180 (37%) papers were not related to COVID-19, and 71 (14.5%) were related to COVID-19. The S-A duration of COVID-19-related articles was significantly shorter compared to papers submitted in the pre-COVID-19 era and to papers submitted in the COVID-19 era but unrelated to COVID-19 (median 6–34 days compared to 65–125 and 46–127, respectively) in all 5 journals. The most prominent reductions in S-A and S-P times were documented in the laryngology and otology/neurotology disciplines, respectively. Processing times of the included papers were significantly shorter in most of the selected ORL-HNS journals during the COVID-19 era compared to the pre-COVID-19 era. COVID-19-related papers were processed more rapidly than non-COVID-19-related papers. These findings testify to the possibility of markedly expediting S-P times and hopefully set a precedent for post-pandemic publishing schedules. [ABSTRACT FROM AUTHOR]

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SARS-CoV-2 has mutated many times since the onset of the COVID-19 pandemic, and the omicron is currently the most dominant variant. Determining the specific strain of the virus is beneficial in providing proper care and containment of the disease. We have previously reported a novel method of counting the number of particle immunoagglutination on a paper microfluidic chip using a smartphone-based fluorescence microscope. A single-copy-level detection was demonstrated from clinical saline gargle samples. In this work, we further evaluated two different SARS-CoV-2 monoclonal antibodies to spike vs. nucleocapsid antigens for detecting omicron vs. delta and spike vs. nucleocapsid proteins. The SARS-CoV-2 monoclonal antibody to nucleocapsid proteins could distinguish omicron from delta variants and nucleocapsid from spike proteins. However, such distinction could not be found with the monoclonal antibody to spike proteins, despite the numerous mutations found in spike proteins among variants. This result may suggest a clue to the role of nucleocapsid proteins in recognizing different variants. [ABSTRACT FROM AUTHOR]

One of the pandemics that have caused many deaths is the Coronavirus disease 2019 (COVID-19). It first appeared in late 2019, and many deaths are increasing day by day until now. Therefore, the early diagnosis of COVID-19 has become a salient issue. Additionally, the current diagnosis methods have several demerits, and a new investigation is required to enhance the diagnosis performance. In this paper, a set of phases are performed, such as collecting data, filtering and augmenting images, extracting features, and classifying ECG images. The data were obtained from two publicly available ECG image datasets, and one of them contained COVID ECG reports. A set of preprocessing methods are applied to the ECG images, and data augmentation is performed to balance the ECG images based on the classes. A deep learning approach based on a convolutional neural network (CNN) is performed for feature extraction. Four different pre-trained models are applied, such as Vgg16, Vgg19, ResNet-101, and Xception. Moreover, an ensemble of Xception and the temporary convolutional network (TCN), which is named ECGConvnet, is proposed. Finally, the results obtained from the former models are fed to four main classifiers. These classifiers are softmax, random forest (RF), multilayer perception (MLP), and support vector machine (SVM). The former classifiers are used to evaluate the diagnosis ability of the proposed methods. The classification scenario is based on fivefold cross-validation. Seven experiments are presented to evaluate the performance of the ECGConvnet. Three of them are multi-class, and the remaining are binary class diagnosing. Six out of seven experiments diagnose COVID-19 patients. The aforementioned experimental results indicated that ECGConvnet has the highest performance over other pre-trained models, and the SVM classifier showed higher accuracy in comparison with the other classifiers. The resulting accuracies from ECGConvnet based on SVM are (99.74%, 98.6%, 99.1% on the multi-class diagnosis tasks) and (99.8% on one of the binary-class diagnoses, while the remaining achieved 100%). It is possible to develop an automatic diagnosis system for COVID based on deep learning using ECG data. [ABSTRACT FROM AUTHOR]

Presented study explores the knowledge domain of psychological research published in 2020 and 2021. Metadata from 156,942 psychology papers available in Scopus were analyzed using citation analysis and bibliographic mapping techniques. Having in mind the ubiquity of the COVID-19 pandemic and the numerous ways it has affected people's lives, the fact that COVID-19-related papers represent only 2% to 7% of the total academic production in psychology may seem rather low. However, these papers have attracted much more attention from the public than non-COVID papers. They were also cited two to eight times more frequently, depending on the measure used, and account for 16% to 19% of total citations to psychology papers. Results show that early-stage researchers and those who had fewer articles in Scopus have benefited more from publishing COVID papers. They have managed to boost their average citation rates to the level of their colleagues who were much longer active and previously had higher citedness. Results indicate that the authors citing behavior largely follows the cumulative advantage pattern. Psychological research in general is mainly focused on mental health, anxiety, depression, and stress. This trend is even more fostered due to the pandemic since some of these topics are often analyzed as typical emotional reactions to COVID-19. Other relevant issues are also very well covered, except for the question how scientific results are communicated to the public. The role of "hot" papers was elaborated from the perspective of research evaluation practice. [ABSTRACT FROM AUTHOR]

Objectives: To establish a consensus protocol for telerehabilitation in speech therapy for voice disorders. Methods: The study was conducted according to a modified Delphi method. Twenty speech therapist or laryngologist experts of the French Society of Phoniatrics and Laryngology assessed 24 statements of voice telerehabilitation with a 10-point visual analog scale ranging from 1 (totally disagree) to 10 (totally agree). The statements were accepted if more than 80% of the experts rated the item with a score of ≥ 8/10. The statements with ≥ 8/10 score by 60–80% of experts were improved and resubmitted to voting until they were validated or rejected. Results: The French Society of Phoniatrics and Laryngology experts validated 10, 6, and 2 statements after the first, second and third voting round, respectively. Seven statements did not reach agreement threshold and were rejected. The validated statements included recommendations for setting (N = 4), medical/speech history (N = 2), subjective voice evaluations (N = 3), objective voice quality measurements (N = 3), and voice rehabilitation (N = 5). The experts agreed for a follow-up consisting of combined telerehabilitation and in-office rehabilitation. The final protocol may be applied in context of pandemic but could be assessed out of pandemic period for patients located in rural regions. Conclusions: This Delphi study established the first telerehabilitation protocol of the French Society of Phoniatrics and Laryngology for patients with voice disorders. Future controlled studies are needed to assess its feasibility, reliability, and the patient perception about telerehabilitation versus in-office rehabilitation. [ABSTRACT FROM AUTHOR]

My Turn is software used to manage several Covid-19 mass vaccination campaigns in California. The objective of this article is to describe the use of My Turn at two points of dispensing in California and comment on process improvements to reduce manual tasks of six identified processes of vaccination–registration, scheduling, administration, documentation, follow-up, and digital vaccine record–and paper. We reviewed publicly available documents of My Turn and patients vaccinated at George R. Moscone Convention Center in San Francisco and Oakland Coliseum Community Vaccination Clinic. For publicly available documents of My Turn, we examined videos of My Turn on YouTube, and documentation from EZIZ, the website for the California Vaccines for Children Program. For patients, we examined publicly available vaccination record cards on Instagram and Google. At the George R. Moscone Convention Center, 329,608 vaccines doses were given. At the Oakland Coliseum Community Vaccination Clinic, more than 500,000 vaccine doses were administered. The use of My Turn can be used to reduce manual tasks and paper for mass vaccinating patients against Covid-19. [ABSTRACT FROM AUTHOR]

Recently, an article by Seneff et al. entitled "Innate immunosuppression by SARS-CoV-2 mRNA vaccinations: The role of G-quadruplexes, exosomes, and MicroRNAs" was published in Food and Chemical Toxicology (FCT). Here, we describe why this article, which contains unsubstantiated claims and misunderstandings such as "billions of lives are potentially at risk" with COVID-19 mRNA vaccines, is problematic and should be retracted. We report here our request to the editor of FCT to have our rebuttal published, unfortunately rejected after three rounds of reviewing. Fighting the spread of false information requires enormous effort while receiving little or no credit for this necessary work, which often even ends up being threatened. This need for more scientific integrity is at the heart of our advocacy, and we call for large support, especially from editors and publishers, to fight more effectively against deadly disinformation. [ABSTRACT FROM AUTHOR]

In 2020 COVID-19 led to an unprecedented stream of papers being submitted to journals. Scientists and physicians all around the globe were in need for information about this new disease. In this climate, many articles were accepted after extremely fast peer-reviews to provide the scientific community with the latest discoveries and knowledge. Unfortunately, this also led to articles retraction due to authors' misconduct or errors in methodology and/or conclusions. The aim of this study is to investigate the number and characteristics of retracted papers, and to explore the main causes that led to retraction. We conducted a systematic review on retracted articles, using PubMed as data source. Our inclusion criteria were the following: English-language retracted articles that reported original data, results, opinions or hypotheses on COVID-19 and Sars-CoV-2. Twenty-seven retracted articles were identified, mainly reporting observational studies and opinion pieces. Many articles published during the first year of the pandemic have been retracted, mainly due to the authors' scientific misconduct. Duplications, plagiarism, frauds and absence of consent, were the main reasons for retractions. In modern medicine, researchers are required to publish frequently, and, especially during situations like the COVID-19 pandemic, when articles were rapidly published, gaps in peer-reviews system and in the path to scientific publication arose. [ABSTRACT FROM AUTHOR]

Due to the recent pandemic of coronavirus, known as the COVID-19 outbreak, the supply chains have been impacted most significantly. Manufacturers of certain items have experienced a substantial increase in demand, and on the other hand, raw materials supply, to produce those items, has reduced because of supply failure. To overcome these challenges, this paper proposes some strategies to improve service level during an extraordinary pandemic outbreak, such as COVID-19, for the most wanted products such as toilet paper. This study considers meeting the increased demand of the customers for an essential product of daily life like toilet paper during a pandemic is beyond the traditional economic objective, i.e., increase profit, of the manufacturers. Instead, this should be more about the social responsibility of all the manufactures to ensure that they can serve more customers. Motivated by this and taking toilet paper as an example of the product, we first analyzed the current scenario of the manufacturing and the demand for the product and then proposed some strategies to deal with this unprecedented risk and analyzed the results. We have compared the results, using hypothetical data, between the current scenario and proposed strategies. The result shows that sharing information and resources from all manufacturers to produce under a single brand, emergency sourcing, producing basic quality items, and packing in the smallest sizes have a significant positive impact on the service level. This paper first investigates the strategies for a high-demand and essential item during a pandemic situation and proposes strategies to deal with this unique, extraordinary disruption. [ABSTRACT FROM AUTHOR]

Infectious diseases are among the leading causes of mortality worldwide. A new coronavirus named severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) was identified in Wuhan, China in 2019, and the World Health Organization (WHO) declared its outbreak, coronavirus disease 2019 (COVID-19), as a global pandemic in 2020. COVID-19 can spread quickly from person to person. One of the most challenging issues is to identify the infected individuals and prevent potential spread of SARS-CoV-2. Recently, anti-SARS-CoV-2 immunoglobulin M (IgM) and immunoglobulin G (IgG) antibody tests using immunochromatographic methods have been used as a complement to current detection methods and have provided information of the approximate course of COVID-19 infection. However, blood sampling causes pain and poses risks of infection at the needle puncture site. In this study, a novel patch sensor integrating porous microneedles and an immunochromatographic assay (PMNIA) was developed for the rapid detection of anti-SARS-CoV-2 IgM/IgG in dermal interstitial fluid (ISF), which is a rich source of protein biomarkers, such as antibodies. Biodegradable porous microneedles (MNs) made of polylactic acid were fabricated to extract ISF from human skin by capillary effect. The extracted ISF was vertically transported and flowed into the affixed immunoassay biosensor, where specific antibodies could be detected colorimetrically on-site. Anti-SARS-CoV-2 IgM/IgG antibodies were simultaneously detected within 3 min in vitro. Moreover, the limit of detection of anti-SARS-CoV-2 IgM and IgG concentrations was as low as 3 and 7 ng/mL, respectively. The developed device integrating porous MNs and immunochromatographic biosensors is expected to enable minimally invasive, simple, and rapid anti-SARS-CoV-2 IgM/IgG antibody testing. Furthermore, the compact size of the MN and biosensor-integrated device is advantageous for its widespread use. The proposed device has great potential for rapid screening of various infectious diseases in addition to COVID-19 as an effective complementary method with other diagnostic tests. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic forced use of face masks up to billions of masks per day globally. Though an important and necessary measure for control of the pandemic, use of masks also poses some inherent risks. One of those risks is inhalation of microplastics released from the mask materials. Since most of the mask materials are made from plastic/polymers, they always have the potential to expose the user to fragmented microplastics. To estimate the amount of inhalable microplastic exuded from masks, an experiment simulating real-life scenario of mask usage was performed. The study included collection of microplastics oozed out from the masks on to a filter paper followed by staining and fluorescence detection of the total number of microplastics using a microscope. Both used and new masks were studied. Based on the emission wavelength, the microplastics were found to be belonging to three different categories, namely blue, green and red emitting microplastics respectively. The number of microplastic particles emitted per mask over a period of usage of 8 h was about 5000 to 9000 for new masks and about 6500 to 15,000 for used masks respectively. The estimation of polymer type of plastic in the mask fabrics was also carried out using Raman and FTIR spectroscopy. [ABSTRACT FROM AUTHOR]

The COVID-19 Psychological Wellbeing Study was designed and implemented as a rapid survey of the psychosocial impacts of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known as COVID-19 in residents across the United Kingdom. This study utilised a longitudinal design to collect online survey based data. The aim of this paper was to describe (1) the rationale behind the study and the corresponding selection of constructs to be assessed; (2) the study design and methodology; (3) the resultant sociodemographic characteristics of the full sample; (4) how the baseline survey data compares to the UK adult population (using data from the Census) on a variety of sociodemographic variables; (5) the ongoing efforts for weekly and monthly longitudinal assessments of the baseline cohort; and (6) outline future research directions. We believe the study is in a unique position to make a significant contribution to the growing body of literature to help understand the psychological impact of this pandemic and inform future clinical and research directions that the UK will implement in response to COVID-19. [ABSTRACT FROM AUTHOR]

In light of the accumulating evidence for survival benefit coming from the use of macrolides for community-acquired pneumonia (CAP), a group of experts from the field of internal medicine and infectious diseases frame a position statement on the use of macrolides for the management of bacterial CAP and for infection by the novel coronavirus (COVID-19). The statement is framed taking into consideration existing publications and own research experience. The main content of this statement is that the combination of one β-lactam and a macrolide should be the first treatment of choice for patients with severe bacterial CAP. Severity is assessed as scoring 2 or more points on the CURB65 scoring system of severity or as pneumonia severity index III to V or C-reactive protein more than 150 mg/l; the suggested macrolide is either azithromycin or clarithromycin. The experts also suggest that in COVID-19 pneumonia, the combination of one β-lactam and a macrolide should be reserved only when there is strong suspicion of bacterial co-infection. [ABSTRACT FROM AUTHOR]

The global coronavirus disease 2019 (COVID-19) pandemic has had significant economic and social impacts on billions of people worldwide since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, China, in November 2019. Although polymerase chain reaction (PCR)-based technology serves as a robust test to detect SARS-CoV-2 in patients with COVID-19, there is a high demand for cost-effective, rapid, comfortable, and accurate point-of-care diagnostic tests in medical facilities. This review introduces the SARS-CoV-2 viral structure and diagnostic biomarkers derived from viral components. A comprehensive introduction of a paper-based diagnostic platform, including detection mechanisms for various target biomarkers and a COVID-19 commercial kit is presented. Intrinsic limitations related to the poor performance of currently developed paper-based devices and unresolved issues are discussed. Furthermore, we provide insight into novel paper-based diagnostic platforms integrated with advanced technologies such as nanotechnology, aptamers, surface-enhanced Raman spectroscopy (SERS), and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas. Finally, we discuss the prospects for the development of highly sensitive, accurate, cost-effective, and easy-to-use point-of-care COVID-19 diagnostic methods. [ABSTRACT FROM AUTHOR]

Patients with cancer are at higher risk of more severe COVID-19 infection and have more associated complications. The position paper describes the management of cancer patients, especially those receiving anticancer treatment, during the COVID-19 pandemic. Dyspnea is a common emergency presentation in patients with cancer with a wide range of differential diagnoses, including pulmonary embolism, pleural disease, lymphangitis, and infection, of which SARS-CoV-2 is now a pathogen to be considered. Screening interviews to determine whether patients may be infected with COVID-19 are imperative to prevent the spread of infection, especially within healthcare facilities. Cancer patients testing positive with no or minimal symptoms may be monitored from home. Telemedicine is an option to aid in following patients without potential exposure. Management of complications of systemic anticancer treatment, such as febrile neutropenia (FN), is of particular importance during the COVID-19 pandemic where clinicians aim to minimize patients' risk of infection and need for hospital visits. Outpatient management of patients with low-risk FN is a safe and effective strategy. Although the MASCC score has not been validated in patients with suspected or confirmed SARS-CoV-2, it has nevertheless performed well in patients with a range of infective illnesses and, accordingly, it is reasonable to expect efficacy in the clinical setting of COVID-19. Risk stratification of patients presenting with FN is a vital tenet of the evolving sepsis and pandemic strategy, necessitating access to locally formulated services based on MASCC and other national and international guidelines. Innovative oncology services will need to utilize telemedicine, hospital at home, and ambulatory care services approaches not only to limit the number of hospital visits but also to anticipate the complications of the anticancer treatments. [ABSTRACT FROM AUTHOR]

In recent months the COVID-19 (also known as SARS-CoV-2 and Coronavirus) pandemic has spread throughout the world. In parallel, extensive scholarly research regarding various aspects of the pandemic has been published. In this work, we analyse the changes in biomedical publishing patterns due to the pandemic. We study the changes in the volume of publications in both peer reviewed journals and preprint servers, average time to acceptance of papers submitted to biomedical journals, international (co-)authorship of these papers (expressed by diversity and volume), and the possible association between journal metrics and said changes. We study these possible changes using two approaches: a short-term analysis through which changes during the first six months of the outbreak are examined for both COVID-19 related papers and non-COVID-19 related papers; and a longitudinal approach through which changes are examined in comparison to the previous four years. Our results show that the pandemic has so far had a tremendous effect on all examined accounts of scholarly publications: A sharp increase in publication volume has been witnessed and it can be almost entirely attributed to the pandemic; a significantly faster mean time to acceptance for COVID-19 papers is apparent, and it has (partially) come at the expense of non-COVID-19 papers; and a significant reduction in international collaboration for COVID-19 papers has also been identified. As the pandemic continues to spread, these changes may cause a slow down in research in non-COVID-19 biomedical fields and bring about a lower rate of international collaboration. [ABSTRACT FROM AUTHOR]

Methodological mistakes, data errors, and scientific misconduct are considered prevalent problems in science that are often difficult to detect. In this study, we explore the potential of using data from Twitter for discovering problems with publications. In this case study, we analyzed tweet texts of three retracted publications about COVID-19 (Coronavirus disease 2019)/SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and their retraction notices. We did not find early warning signs in tweet texts regarding one publication, but we did find tweets that casted doubt on the validity of the two other publications shortly after their publication date. An extension of our current work might lead to an early warning system that makes the scientific community aware of problems with certain publications. Other sources, such as blogs or post-publication peer-review sites, could be included in such an early warning system. The methodology proposed in this case study should be validated using larger publication sets that also include a control group, i.e., publications that were not retracted. [ABSTRACT FROM AUTHOR]

This paper will explore the key findings identified in the five arts discipline-specific papers which comprise this special theme issue. Each of the participant researchers have situated Dance, Drama, Media Arts, Music and Visual Arts within the context of the Australian Curriculum: The Arts and what they characterise as its social justice imperatives. A narrative phenomenological approach has been adopted to enable the participant researchers to socially co-construct an analysis of their experiences working with the Australian Curriculum: The Arts including challenges, implications and the future for their respective discipline areas and the Arts overall. The three key themes from these collective voices revealed a quality arts education is an entitlement for every child and young person; the Arts provide important opportunities for children and young people from diverse backgrounds and cultures to demonstrate their learning, express themselves and participate; and arts educators and the Arts industry need to work together to strengthen community understanding about the value of the Arts in education. This process provided important insights into how exposure and engagement with the Arts shape the ways in which children and young people make meaning in their lives, enhance their overall wellbeing, increase their sense of social responsibility and contribute to a socially-just society. [ABSTRACT FROM AUTHOR]

The rapid worldwide spread of the Coronavirus disease (COVID-19) crisis has put health systems under pressure to a level never experienced before, putting intensive care units in a position to fail to meet an exponentially growing demand. The main clinical feature of the disease is a progressive arterial hypoxemia which rapidly leads to ARDS which makes the use of intensive care and mechanical ventilation almost inevitable. The difficulty of health systems to guarantee a corresponding supply of resources in intensive care, together with the uncertain results reported in the literature with respect to patients who undergo early conventional ventilation, make the search for alternative methods of oxygenation and ventilation and potentially preventive of the need for tracheal intubation, such as non-invasive respiratory support techniques particularly valuable. In this context, the Emergency Department, located between the area outside the hospital and hospital ward and ICU, assumes the role of a crucial junction, due to the possibility of applying these techniques at a sufficiently early stage and being able to rapidly evaluate their effectiveness. This position paper describes the indications for the use of non-invasive respiratory support techniques in respiratory failure secondary to COVID-19-related pneumonia, formulated by the Non-invasive Ventilation Faculty of the Italian Society of Emergency Medicine (SIMEU) on the base of what is available in the literature and on the authors' direct experience. Rationale, literature, tips & tricks, resources, risks and expected results, and patient interaction will be discussed for each one of the escalating non-invasive respiratory techniques: standard oxygen, HFNCO, CPAP, NIPPV, and awake self-repositioning. The final chapter describes our suggested approach to the failing patient. [ABSTRACT FROM AUTHOR]

Achieving community immunity against the coronavirus disease 2019 (COVID-19) depends on vaccinating the largest number of people within a specific period while taking all precautionary measures. To address this problem, this paper presents a smart parking system that will help the health crisis management committee to vaccinate the largest number of people with the minimum period of time while ensuring that all precautionary measures are followed, through a set of algorithms. These algorithms seek to ensure a uniform distribution of persons in parking. This paper proposes a novel complex system for smart parking and nine algorithms to address the NP-hard problem. The experimental results demonstrate the performance of the proposed algorithms in terms of gap and time. Applying these algorithms to smart cities to ensure precautionary measures against COVID-19 can help fight against this pandemic. [ABSTRACT FROM AUTHOR]

According to existing research, in the general scientific backdrop, individuals prefer to employ old and well-established knowledge to promote scientific advancement, resulting in the progress of science in a set direction. When the disruption event COVID-19 occurred, however, people's demand for breakthrough research, such as vaccinations or treatments, became increasingly pressing. Under such circumstances, can the accumulated coronavirus-related knowledge still give solid support for COVID-19 research? The manner of utilizing and absorbing new knowledge in the citing publications is reflected in the reference analysis. To investigate this proposition, we employ reference analysis to conduct retrospectives on relevant scientific articles. We locate 309,517 related papers and their references in the CORD-19 data from 2000 to 2021. We analyze the knowledge support capacity of previous studies from three aspects: the quantity, timeliness, and textual support of references. Among them, textual support is divided into lexical, topic, and semantic support, which are respectively based on TF-IDF, LDA, and fine-tuned sentence-BERT. Our findings demonstrate that COVID-19 has caused unprecedented destruction of the original knowledge support pattern in the early stages of research (which is at odds with the knowledge support pattern in the general scientific background). The long-term accumulated and non-direct knowledge provides brief support for the COVID-19 investigation. Follow-up research will swiftly replace outdated information with new study findings. The appeal of the scientific community has moved from "return to the past" to "innovative alternatives". We divide the process into three stages: rearrangement, iteration, and growth. The loss in knowledge support capacity following a disruptive event such as COVID-19 enhances the difficulty of research. However, it cannot be ignored that it has also considerably sped the pace of knowledge production. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has caused drastic changes in the publishing framework which allowed for the quick review and rapid publication of manuscripts in order to quickly share vital information about this new viral pandemic to the general public and scientists. Alarms have been raised for the potential for misconduct in COVID-19 research. The purpose of this study is to determine the presence of plagiarism in COVID-19 papers across infectious disease journals. Methods: COVID-19 related research and review articles published in infectious disease journals were collected. Each manuscript was optimized and uploaded to Turnitin, which is a similarity checking tool. Similarity reports were manually checked for events of true plagiarism using an 80% threshold, performed via human judgment. Results: In this cross-sectional study, 41.61% (n = 129) of manuscripts were deemed plagiarized out of a total of 310 papers that were analyzed. Plagiarism was identified in 35.07% of reviews (n = 47), and 46.6% of original research (n = 82). Among the plagiarized papers, the median number of copied sentences was 3 IQR 4. The highest recorded similarity report was 60%, and the highest number of copied sentences was 85. The discussion section of these articles was the most problematic area, with the average number of copied sentences in that section being 6.25 ± 10.16. The average time to judge all manuscripts was 2.45 ± 3.09 min. Among all the plagiarized papers, 72.09% belonged to papers where the similarity report was ≤ 15% (n = 93). No significant differences were found with regards to plagiarism events among the quartiles. Conclusions: Plagiarism is prevalent in COVID-19 publications. All similarity reports should be supplemented with human judgment. [ABSTRACT FROM AUTHOR]

Furthermore, it has been reported that MS patients using anti-CD20 therapy have suppressed antibody response to infection with the novel coronavirus (SARS-CoV-2) and to some vaccines (not against COVID-19) [[1], [3]-[5]]. Dear Sirs, We read with great interest the paper by Khayat Khoei et al. which presented negative anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) antibody response after Pfizer SARS-CoV-2 vaccination in a patient with relapsing-remitting multiple sclerosis (RRMS) on ocrelizumab [[1]]. [Extracted from the article]

Given the pandemic situation, there is an urgent need for an accurate test to monitor antibodies anti-SARS-CoV-2, providing crucial epidemiological and clinical information to monitor the evolution of coronavirus disease in 2019 (COVID-19) and to stratify the immunized and asymptomatic population. Therefore, this paper describes a new cellulose-based test strip for rapid and cost-effective quantitative detection of antibodies to SARS-CoV2 virus by colorimetric transduction. For this purpose, Whatman paper was chemically modified with sodium metaperiodate to introduce aldehyde groups on its surface. Subsequently, the spike protein of the virus is covalently bound by forming an imine group. The chemical control of cellulose paper modification was evaluated by Fourier transform infrared spectroscopy, thermogravimetry and contact angle analysis. Colorimetric detection of the antibodies was performed by a conventional staining method using Ponceau S solution as the dye. Color analysis was performed after image acquisition with a smartphone using Image J software. The color intensity varied linearly with the logarithm of the anti-S concentration (from 10 ng/mL to 1 μg/mL) in 500-fold diluted serum samples when plotted against the green coordinate extracted from digital images. The test strip was selective in the presence of nucleocapsid antibodies, urea, glucose, and bovine serum albumin with less than 15% interference, and detection of antibodies in human serum was successfully performed. Overall, this is a simple and affordable design that can be readily used for mass population screening and does not require sophisticated equipment or qualified personnel. [ABSTRACT FROM AUTHOR]

The present work aims to give an overview on the international scientific papers related to the territorial spreading of SARS-CoV-2, with a specific focus upon applied quantitative geography and territorial analysis, to define a general structure for epidemiological geography research. The target publications were based on GIS spatial analysis, both in the sense of topological analysis and descriptive statistics or lato sensu geographical approaches. The first basic purpose was to organize and enhance the vast knowledge developments generated hitherto by the first pandemic that was studied "on-the-fly" all over the world. The consequent target was to investigate to what extent researchers in geography were able to draw scientifically consistent conclusions about the pandemic evolution, as well as whether wider generalizations could be reasonably claimed. This implied an analysis and a comparison of their findings. Finally, we tested what geographic approaches can say about the pandemic and whether a reliable spatial analysis routine for mapping infectious diseases could be extrapolated. We selected papers proposed for publication during 2020 and 209 articles complied with our parameters of query. The articles were divided in seven categories to enhance existing commonalities. In some cases, converging conclusions were extracted, and generalizations were derived. In other cases, contrasting or inconsistent findings were found, and possible explanations were provided. From the results of our survey, we extrapolated a routine for the production of epidemiological geography analyses, we highlighted the different steps of investigation that were attained, and we underlined the most critical nodes of the methodology. Our findings may help to point out what are the most critical conceptual challenges of epidemiological mapping, and where it might improve to engender informed conclusions and aware outcomes. [ABSTRACT FROM AUTHOR]

Aim: To nuance the discussion on the suggested absence of the risk-compensation phenomenon in times of COVID-19. Subject and methods: In many countries, behavioral restrictions for COVID-19 prevention started with asking people to stay 1.5 m away from each other. To further prevent the spread of the virus, governments made it mandatory for people to wear facemasks in situations where keeping the 1.5-m distance was not possible. This triggered a discussion among behavioral scientists regarding whether making face-masks mandatory might lead to the undesirable side effect that people would be less compliant with the 1.5-m distance rule: risk compensation. Mantzari et al. (2020) published a paper claiming that risk compensation was a non-existing phenomenon. Czyprionka et al. (2020) repeated the same claim, referring to the same original publications. We performed a rapid review of the existing literature and identified 19 papers that presented original data on studies that identified the consequences of wearing a facemask. Results: The evidence for risk compensation is inconclusive. Risk compensation may occur with the encouraged use of face coverings. However, it may not always be present, especially when there are other social processes in play, such as respecting other people's choices. Conclusion: Inconclusive evidence doesn't mean that risk compensation should be ignored or that potential public health interventions shouldn't be implemented. The introduction of mandatory face masks should, therefore, always be accompanied by a theory- and evidence-based health promotion campaign to prevent the possible negative effects of distancing. Carefully applying social psychological insights to guide people in their decision to wear masks when needed and to do so correctly, may overcome potential risk compensation and thereby optimize COVID-19 preventive efforts. Highlights: The evidence for risk compensation – in this case, keeping less distance while wearing a mask for COVID-19 prevention – is inconclusive. Risk compensation should not be a reason to refrain from implementing an evidence-based health promotion intervention. The implementation of health promotion interventions should always be combined with additional interventions to reduce the chance that risk compensation will lessen the intended effect. [ABSTRACT FROM AUTHOR]

One of the most important problems for research is the problem of time series clustering. Clustering is important in the tasks of identifying common dynamic changes between series and searching for patterns in the behavior of dynamics and, finally, for forecasting. The article discusses the problem of assessing the statistical significance of clustering. Currently, there are a number of approaches to assessing significance. These include asymptotic criteria, as well as criteria based on comparison of clustering results on analyzed groups with clustering results on simulated data, which are generated on the basis of the null hypothesis of group homogeneity. However, these approaches cannot be used to solve many time series clustering problems because of the difficulty of proving that convergence conditions are met and because of the difficulty of choosing an adequate null hypothesis and specification of the distribution from which the data are generated. The paper proposes an alternative approach designed to assess the significance of hierarchical agglomerative clustering using the maximum of a set of correlation coefficients calculated for different time lag values as a measure of similarity between time series. The approach is based on comparing the clustering results obtained from the original lagged correlation matrix with the clustering results obtained from the original one by random permutations of off-diagonal elements while maintaining symmetry. The paper presents the results of applying the developed method to the problem of temporal clustering, containing the values of the daily increase in the number of COVID-19 illnesses. [ABSTRACT FROM AUTHOR]

In the face of complex and changeable uncertain environments, corporate resilience is the crucial foundation for survival and sustainable development, and enhancing corporate resilience becomes an important goal for governments. In this context, this paper investigates the impact of government subsidies, as a typical government tool, on corporate resilience in crises. Based on the panel data of 2315 listed companies in China Shanghai and Shenzhen A-share market during the COVID-19 pandemic, this paper finds that: (1) government subsidies received before and during the crises can both enhance corporate resilience in crises. (2) Government subsidies enhance corporate resilience by alleviating financial constraints and boosting confidence. (3) The crises improve the efficiency of subsidies used by corporates, resulting in the enhancement of subsidies received during the crises being more pronounced than those received before the crises. This paper deepens the understanding of government subsidies' roles in crises, enriches the literature on government subsidies and corporate resilience, and provides a reference for improving government subsidies policy and enhancing corporate resilience. The government should increase government subsidies to mitigate the negative impact of uncertainty shocks on corporates and improve corporates' ability to respond to risks, and pay attention to the timing of subsidies to maximize the efficiency of government subsidies at the same time. [ABSTRACT FROM AUTHOR]

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person. This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions: Stress overload associated pathologies Male and female health Planned pregnancies Periodontal health Eye disorders Inflammatory disorders, wound healing and pain management with associated complications Metabolic disorders and suboptimal body weight Cardiovascular pathologies Cancers Stroke, particularly of unknown aetiology and in young individuals Sleep medicine Sports medicine Improved individual outcomes under pandemic conditions such as COVID-19. [ABSTRACT FROM AUTHOR]

The COVID-19 global health crisis forced border closings, strained resources and tightened funding, forcing humanitarian organisations to innovate. This paper aims to identify gaps in the literature on innovation in humanitarian supply chains, and to develop an appropriate framework for future research through a systematic literature review. We use a systematic literature review approach and synthesis the discussion of innovation in humanitarian supply chains after reviewing 43 papers. The synthesis identifies the different contexts for and outcomes of innovation in humanitarian supply chains. Our findings indicate that research on innovation in humanitarian supply chains is an underdeveloped topic. Gaps we identified in regards to the humanitarian context are: (1) a limited discussion of the contribution by the beneficiary to the supply chain; (2) a limited discussion of reconstruction innovations; (3) a lack of study on field application for complex innovations; (4) the lack of discussion of the role of individual knowledge in humanitarian supply chain innovation and finally (5) a lack of study of position innovations where humanitarian organisations use supply chains as a way to market effectively towards donors. [ABSTRACT FROM AUTHOR]

In recent years, emerging technologies have gained popularity and being implemented in different fields. Thus, critical leading-edge technologies such as artificial intelligence and other related technologies (blockchain, simulation, 3d printing, etc.) are transforming the operations and other traditional fields and proving their value in fighting against unprecedented COVID-19 pandemic outbreaks. However, due to this relation's novelty, little is known about the interplay between emerging technologies and COVID-19 and its implications to operations-related fields. In this vein, we mapped the extant literature on this integration by a structured literature review approach and found essential outcomes. In addition to the literature mapping, this paper's main contributions were identifying literature scarcity on this hot topic by operations-related fields; consequently, our paper emphasizes an urgent call to action. Also, we present a novel framework considering the primary emerging technologies and the operations processes concerning this pandemic outbreak. Also, we provided an exciting research agenda and four propositions derived from the framework, which are collated to operations processes angle. Thus, scholars and practitioners have the opportunity to adapt and advance the framework and empirically investigate and validate the propositions for this and other highly disruptive crisis. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects host cells following binding with the cell surface ACE2 receptors, thereby leading to coronavirus disease 2019 (COVID-19). SARS-CoV-2 causes viral pneumonia with additional extrapulmonary manifestations and major complications, including acute myocardial injury, arrhythmia, and shock mainly in elderly patients. Furthermore, patients with existing cardiovascular comorbidities, such as hypertension and coronary heart disease, have a worse clinical outcome following contraction of the viral illness. A striking feature of COVID-19 pandemics is the high incidence of fatalities in advanced aged patients: this might be due to the prevalence of frailty and cardiovascular disease increase with age due to endothelial dysfunction and loss of endogenous cardioprotective mechanisms. Although experimental evidence on this topic is still at its infancy, the aim of this position paper is to hypothesize and discuss more suggestive cellular and molecular mechanisms whereby SARS-CoV-2 may lead to detrimental consequences to the cardiovascular system. We will focus on aging, cytokine storm, NLRP3/inflammasome, hypoxemia, and air pollution, which is an emerging cardiovascular risk factor associated with rapid urbanization and globalization. We will finally discuss the impact of clinically available CV drugs on the clinical course of COVID-19 patients. Understanding the role played by SARS-CoV2 on the CV system is indeed mandatory to get further insights into COVID-19 pathogenesis and to design a therapeutic strategy of cardio-protection for frail patients. [ABSTRACT FROM AUTHOR]

The aim of this paper is to contribute to a better understanding of musician identity learning. Identity is a significant driving-force behind many artistic vocations. However, identity may also pose challenges such as vulnerability, burnout and conflict of commitment. The paper focuses on musician identity, based on interviews with classical and rock musicians during the COVID-19 pandemic. Analyses reveal that the musicians are either in integrating or situating musician identity learning, two different processes discussed as dynamically interrelated and depending on life situation. The paper argues that breaks of normality accentuate challenges stemming from musician identity and that the proposed learning processes are responses to those challenges, which is previously under-explored. The paper concludes that many musicians or other artistic practitioners likely struggle to de-centralize their identity in order to foster a sustainable vocational career and personal growth, and that temporary career breaks may provide necessary relief and learning space. [ABSTRACT FROM AUTHOR]

COVID-19 outbreak has caused a devastating impact on the daily lives of people, public health, and economic progress of infected countries. It has become a leading cause of substantial mortality and morbidity around the world. The emergence of new variants of virus has posed severe challenges for humanitarian society. Information and Communication Technology (ICT) has played a vital role in this pandemic and offered various promising innovations to control its dissemination. The current research study presents a scientometric analysis on the literature of ICT-assisted COVID-19 research. In this paper, ICT has been classified into six major categories; artificial intelligence and medical imaging, mobile technology, ubiquitous computing, big data analytics, social media platforms, and printing technology. It extensively examines the role of these technologies in COVID-19 by applying various empirical approaches such as co-citation analysis, publication and citation behavior analysis, participating nations, and knowledge mapping of scientific literature using visualization tool CiteSpace. Furthermore, it provides a visual approach to identify developing paths, evolution trends, research hotspots, cluster analysis, and potential future directions in medical informatics. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has triggered panic-buying behavior around the globe. As a result, many essential supplies were consistently out-of-stock at common point-of-sale locations. Even though most retailers were aware of this problem, they were caught off guard and are still lacking the technical capabilities to address this issue. The primary objective of this paper is to develop a framework that can systematically alleviate this issue by leveraging AI models and techniques. We exploit both internal and external data sources and show that using external data enhances the predictability and interpretability of our model. Our data-driven framework can help retailers detect demand anomalies as they occur, allowing them to react strategically. We collaborate with a large retailer and apply our models to three categories of products using a dataset with more than 15 million observations. We first show that our proposed anomaly detection model can successfully detect anomalies related to panic buying. We then present a prescriptive analytics simulation tool that can help retailers improve essential product distribution in uncertain times. Using data from the March 2020 panic-buying wave, we show that our prescriptive tool can help retailers increase access to essential products by 56.74%. [ABSTRACT FROM AUTHOR]

The World Health Organization has designated vaccine hesitancy and vaccine confidence among the most pressing issues in global health. The COVID-19 pandemic has made vaccine hesitancy and vaccine confidence particularly salient and urgent. The purpose of this special issue is to highlight a broad range of perspectives on these critical issues. We have included a total of 30 papers that address issues related to vaccine hesitancy and vaccine confidence across multiple levels of the Socio-Ecological Model. We have organized the empirical papers into the following sections: individual-level beliefs, minority health and health disparities, social media and conspiracy beliefs, and interventions. In addition to the empirical papers, three commentaries are included in this special issue. [ABSTRACT FROM AUTHOR]

An increasing interest in a healthy lifestyle raises questions about optimal body weight. Evidently, it should be clearly discriminated between the standardised "normal" body weight and individually optimal weight. To this end, the basic principle of personalised medicine "one size does not fit all" has to be applied. Contextually, "normal" but e.g. borderline body mass index might be optimal for one person but apparently suboptimal for another one strongly depending on the individual genetic predisposition, geographic origin, cultural and nutritional habits and relevant lifestyle parameters—all included into comprehensive individual patient profile. Even if only slightly deviant, both overweight and underweight are acknowledged risk factors for a shifted metabolism which, if being not optimised, may strongly contribute to the development and progression of severe pathologies. Development of innovative screening programmes is essential to promote population health by application of health risks assessment, individualised patient profiling and multi-parametric analysis, further used for cost-effective targeted prevention and treatments tailored to the person. The following healthcare areas are considered to be potentially strongly benefiting from the above proposed measures: suboptimal health conditions, sports medicine, stress overload and associated complications, planned pregnancies, periodontal health and dentistry, sleep medicine, eye health and disorders, inflammatory disorders, healing and pain management, metabolic disorders, cardiovascular disease, cancers, psychiatric and neurologic disorders, stroke of known and unknown aetiology, improved individual and population outcomes under pandemic conditions such as COVID-19. In a long-term way, a significantly improved healthcare economy is one of benefits of the proposed paradigm shift from reactive to Predictive, Preventive and Personalised Medicine (PPPM/3PM). A tight collaboration between all stakeholders including scientific community, healthcare givers, patient organisations, policy-makers and educators is essential for the smooth implementation of 3PM concepts in daily practice. [ABSTRACT FROM AUTHOR]

A theory to analyze complex scenarios facing threats with competing factors and limited resources has been introduced. The scenarios are modeled as closed systems. Hamilton's principle of stationary action is used to conceive a theory in which competing factors dispute available resources to minimize undesirable outcomes. The result indicates that the minimum response is obtained by a combination of the competing factors weighted by their corresponding criticalities. The theory has been applied to the COVID-19 pandemic with two competing factors: Health and Economy. As main result, to minimize the total number of deaths, the recommendation is to balance the emphasis on both factors. This implies to give more emphasis to the economic factor, by avoiding restrict interventions like lockdowns and business closures. The model may evolve from a qualitative to a quantitative status, allowing for computational simulations aimed at validations and forecasting. As such, this approach may become a useful tool for strategic decision-making regarding resources allocations to reduce guessing in scenarios full of uncertainties. [ABSTRACT FROM AUTHOR]

This article aims to provide guidance on prevention and treatment of COVID-19 in patients with genetic obesity. Key principals of the management of patients with genetic obesity during COVID-19 pandemic for patients that have contracted COVID-19 are to be aware of: possible adrenal insufficiency (e.g., POMC deficiency, PWS); a more severe course in patients with concomitant immunodeficiency (e.g., LEP and LEPR deficiency), although defective leptin signalling could also be protective against the pro-inflammatory phenotype of COVID-19; disease severity being masked by insufficient awareness of symptoms in syndromic obesity patients with intellectual deficit (in particular PWS); to adjust medication dose to increased body size, preferably use dosing in m2; the high risk of malnutrition in patients with Sars-Cov2 infection, even in case of obesity. Key principals of the obesity management during the pandemic are to strive for optimal obesity management and a healthy lifestyle within the possibilities of the regulations to prevent weight (re)gain and to address anxiety within consultations, since prevalence of anxiety for COVID-19 is underestimated. [ABSTRACT FROM AUTHOR]

This paper discloses a convenient and effective tritiation of 5-aminolevulinic acid (5-ALA). The synthetic method involves a direct tritium labelling of 5-ALA itself. The initial purification and subsequent repurifications of [3H] 5-ALA are described. The analysis, storage conditions and stability of [3H] 5-ALA are also discussed. [ABSTRACT FROM AUTHOR]

Coronavirus Disease 2019 (COVID-19), which is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), surprised the world in December 2019 and has threatened the lives of millions of people. Countries all over the world closed worship places and shops, prevented gatherings, and implemented curfews to stand against the spread of COVID-19. Deep Learning (DL) and Artificial Intelligence (AI) can have a great role in detecting and fighting this disease. Deep learning can be used to detect COVID-19 symptoms and signs from different imaging modalities, such as X-Ray, Computed Tomography (CT), and Ultrasound Images (US). This could help in identifying COVID-19 cases as a first step to curing them. In this paper, we reviewed the research studies conducted from January 2020 to September 2022 about deep learning models that were used in COVID-19 detection. This paper clarified the three most common imaging modalities (X-Ray, CT, and US) in addition to the DL approaches that are used in this detection and compared these approaches. This paper also provided the future directions of this field to fight COVID-19 disease. [ABSTRACT FROM AUTHOR]

This paper explores the social impacts of COVID-19 on migrants living in three major African cities: Accra, Johannesburg, and Nairobi. Given the importance of social support networks to mobile populations, particularly in areas with limited access to essential services, understanding how the pandemic disrupted social relations underscores the broader health and economic impacts of COVID-19 on migrant communities. Using a large scale 2021 survey of nine migrant neighborhoods located across three African mega-cities, we comparatively analyze migrant social interactions during the first year of the pandemic. We find that while migrant social interactions decreased in Accra and Nairobi, living in Johannesburg was significantly associated with unchanged or increased social interactions in the first year of the pandemic. We situate these findings with municipal and country-level variation of COVID-19 policy responses within each city. In particular, we illuminate how the severity of the pandemic and response in South Africa may have catalyzed opportunities for migrants to increase social engagements within their everyday lives. By understanding how compound challenges impacted migrant life, this paper contributes to the emerging area of comparative studies on the effects of COVID-19 on migrant populations, and urban populations within the Global South more broadly. [ABSTRACT FROM AUTHOR]

The eHealth sector has witnessed significant growth due to technological advancements, facilitating care delivery in patients' homes and moving away from traditional hospital settings. Blockchain and the Internet of Things (IoT) play pivotal roles in enhancing healthcare services, offering features such as remote patient monitoring, streamlined electronic medical record (EMR) management, drug traceability, and effective disease control, particularly during events like the COVID-19 pandemic. The growing utilization of IoT devices brings about security challenges, including concerns related to data integrity and device authentication. This paper proposes the integration of blockchain technology as a robust solution. Leveraging its decentralized and tamper-resistant features, blockchain establishes trust among diverse IoT devices, ensuring the integrity of IoT data. Additionally, smart contracts enhance device authentication, fortifying overall security by addressing vulnerabilities associated with centralization. Regarding the management of eHealth, this survey begins with an overview of the industry, highlighting IoT-related challenges in healthcare. It explores various IoT applications in eHealth and discusses how blockchain can effectively address obstacles in healthcare management through IoT. Notably, the paper provides insights into examining consensus algorithm parameters within blockchain systems, clarifying the methodology used to assess and optimize these critical components. The survey extends to a thorough review of existing research on integrating blockchain-based IoT in eHealth. Finally, it presents an overview of challenges and potential solutions for implementing blockchain-based IoT in the eHealth sector. This comprehensive survey aims to empower stakeholders by providing insights to enhance patient care in this dynamic and evolving field. [ABSTRACT FROM AUTHOR]

This paper aims to identify herding biases and assess the inefficiency of Ethereum using an inefficiency index (MLM). Additionally, it investigates the nonlinear dynamical properties of Ethereum by estimating the MFDFA, aiming to deduce the impact of COVID-19 on Ethereum's performance. The paper also captures abnormal changes resulting from COVID-19-related events and assesses their influence on the Ethereum market response. The empirical results show that Ethereum was multifractal before the pandemic and became less fractal in the period following the outbreak using Generalized Hurst Exponent (GHE) estimation. Based on the MLM measure of efficiency, we found Ethereum to be more efficient in the first phase of the pandemic than before it, and as in the Hausdorff topology, the pandemic reduced herd bias. The event study analysis took into account specific events related to the pandemic and showed that each led to significant abnormal returns in the Ethereum market. The results reported are used to empirically establish differences in the value of Ethereum before and during the COVID-19 pandemic. The results are useful in a general sense for traders, investors, and policy makers because they provide new information about market trading opportunities and social responses. [ABSTRACT FROM AUTHOR]

Estimating the impact of COVID-19 on the multiple dimensions of child well-being requires quasi-random variation in exposure to it, which is unlikely to occur during a pandemic. Recent developments in econometrics have highlighted the relevance of subjective evaluations of treatment effects in the absence of randomization. This paper delivers new evidence, based on primary data collected in Luxembourg in Spring 2021 about their subjective appraisal of the effects of COVID-19 on multiple dimensions of children's well-being. Effects are recovered through specific survey questions, asking children to compare actual outcomes with counterfactual ones, that they believe would have occurred in the absence of COVID-19. Children report negative effects of COVID-19 on subjective health and on schooling outcomes, as well as disruptions on the time used to interact with the family. The paper explores the sources of heterogeneity behind these results. [ABSTRACT FROM AUTHOR]

Based on a dynamic panel data model, this paper estimates the impact of lockdown policies on inflation with U.S. metropolitan-level data from the Bureau of Labor Statistics. After controlling for the unit/time fixed effects and several aggregate demand/supply shifters, lockdown policies created a mild inflationary effect nationwide, though the individual effect was heterogeneous. This study novelly analyzes the political economy of coronavirus disease policy and the subsequent economic outcomes. In particular, the inflationary impact was most pronounced for Republican-governed states that switched votes from President Trump in 2016 to President (elect) Biden in 2020, suggesting price stability is a source of voting behavior. On the contrary, lockdown policies caused deflation in Democratic-governed states where unemployment rates and public compliance with lockdown measures were presumably higher. The results indicate that the economic consequences of public policies depend critically on the political partisanship of the region. [ABSTRACT FROM AUTHOR]