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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]

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]

Focusing on the challenges brought about by the devastating COVID-19 pandemic in China and the Chinese government's increasingly stringent regulatory policies, this paper poses the following research questions: During the pandemic and in interactions with the government, why did some non-governmental organizations (NGOs) survive while others were shut down, although most of those that survived were small and medium-sized NGOs? In addressing this question, this paper delves into the strategies adopted by small and medium-sized NGOs to cope with COVID-19. Using data drawn from three years of field observations and research in six major cities in China, this paper finds that four types of small and medium-sized NGOs resorted to different strategies that followed degree of competitiveness and scope of main business. The scarcity of resources resulting to the pandemic plunged NGOs into a competitive survival posture; thus, the strategies for the four types of small and medium-sized NGOs achieved three levels of effectiveness, namely good, medium, and poor. The findings of this paper shed significant light on the diversity and complexity of the survival and development of NGOs under the authoritarian regime of China. [ABSTRACT FROM AUTHOR]

In 2000, during a time when cyber security research was focused on the risks and threats posed by digital systems, the notion of being able to withstand and recover from cyber attacks, also known as cyber resilience, emerged. Recently, this concept has gained increasing attention due to the COVID-19 pandemic and the rapid acceleration of digitalization. While experts acknowledge the distinction between cyber security and cyber resilience, the exact definition and evolution of the latter remain somewhat ambiguous. The aim of this paper is to offer a thorough comprehension of how the notion of cyber resilience has developed throughout history. It delves into the concept of cyber resilience and its progression over time in response to the rising frequency and complexity of cyber threats. Cyber resilience, a new concept, has gained significant recognition as a critical component of cyber security strategy across diverse sectors, encompassing public and private domains alike. It begins with an overview of the definition and key components of cyber resilience and then traces the origin of the concept from its early development in the 2000s. The paper also explores the major milestones and events that have shaped the evolution of this capacity, including changes in technology and societal factors, up to the COVID-19 pandemic outbreak. This study provides valuable insights into future challenges for ensuring the continued resilience of digital infrastructure by examining the historical and contextual factors that have influenced the concept. [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]

Mining is an important enterprise that will supply essential minerals for the country's infrastructural development. Mining is a key industry and a development engine in the Indian economy. The epidemic has had both immediate and long-term effects on the labour and industries in India. Short-term effects include the cessation of mineral production, salary loss due to absenteeism and pandemic limitations, unemployment, and the selling of minerals on the market. The reputation and economic health of industries, fresh mineral deposit exploration, and new mining complex development have all been impacted in long-term. Aside from the mining industry-specific impact of COVID-19, the social fabric of the mining workers has been impacted since they are living in an environment of fear and uncertainty. This paper attempts to analyse the effect of COVID-19 on extractive industries in India. It also focuses the steps which taken by the Indian government. The paper concluded with the negative effect of COVID-19 which disrupts the mining sector and the contribution declined during COVID-19. However, for instance from mineral rich-Odisha, the mining sector takes up by its growth in post COVID-19 period with remarkable increment from negative growth to high positive rate. [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]

Crises constitute ideal opportunities for authoritarian leaders to promote certain narratives, shaping reality in their favor and crafting their own preferred storylines about current events. In other words: they serve authoritarian leaders on a silver platter the opportunity to instrumentalize these unforeseen circumstances to gain domestic political legitimacy by promoting strategic narratives. The COVID-19 pandemic was no exception in this regard. Ever since its onset in early 2020, the Chinese Communist Party (CCP) was among the most active actors worldwide seeking to capitalize on the global crisis for legitimation purposes. Whether applying narratives of governance supremacy, portraying the People's Republic of China as a "global savior," or promoting emotionally appealing nationalistic narratives, the regime used the pandemic as a window of opportunity to rebrand its international role and enhance its domestic legitimacy. When observing the CCP's communication style over the course of 24 pandemic months (2020–2022), however, major shifts become apparent regarding the main narratives crafted in communication with national audiences. Based on this, the paper focuses on the role of such narratives for legitimation claims. Using exemplary media articles collected between the outbreak of the pandemic in China in late 2019 until the harsh Shanghai lockdown in spring 2022, it thus traces the narratives employed by Chinese state elites and explores how they are intertwined with nationalism and broader power claims. [ABSTRACT FROM AUTHOR]

A situation of emergency involving the whole population introduces changes in the dynamics of the health services that are provided. The magnitude of these shifts should be also linked to the medical speciality within which the health benefits are delivered. The aim of the paper was to identify changes in tendencies in inpatient medical service delivery during the COVID-19 pandemic by medical specialties. On the basis of a database extracted for in-patient treatment received from the public payer, a retrospective analysis was carried out. Comparing the values of the dynamics of the services provided in each medical speciality, the period before the COVID-19 pandemic was collated to the years of the pandemic (2020–2021). In the period before COVID-19, positive patient dynamics were observed in more than half of the specialities. Between 2020 and 2021, virtually all specialties reversed the trend and negative dynamics were recorded. The dynamics in 2021 indicate a process of return to the values from 2015 to 2019. Emergency situation has affected the dynamics of healthcare provision in different specialities to various extent. The most resistant to the negative impulses of the state of emergency were the areas that are strictly organisationally and financially defined (e.g. the group of "therapeutic and drug programmes"). [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) remains serious around the world and causes huge deaths and economic losses. Understanding the transmission dynamics of diseases and providing effective control strategies play important roles in the prevention of epidemic diseases. In this paper, to investigate the effect of delays on the transmission of COVID-19, we propose a delayed SEIR model to describe COVID-19 virus transmission, where two delays indicating the incubation and recovery periods are introduced. For this system, we prove its solutions are nonnegative and ultimately bounded with the nonnegative initial conditions. Furthermore, we calculate the disease-free and endemic equilibrium points and analyze the asymptotical stability and the existence of Hopf bifurcations at these equilibrium points. Then, by taking the weighted sum of the opposite number of recovered individuals at the terminal time, the number of exposed and infected individuals during the time horizon, and the system cost of control measures as the cost function, we present a delay optimal control problem, where two controls represent the social contact and the pharmaceutical intervention. Necessary optimality conditions of this optimal control problem are exploited to characterize the optimal control strategies. Finally, numerical simulations are performed to verify the theoretical analysis of the stability and Hopf bifurcations at the equilibrium points and to illustrate the effectiveness of the obtained optimal strategies in controlling the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

The coronavirus pandemic, besides generating health distress, influences the socio-economic conditions of humankind. Every adolescent's lifestyle is affected by the virus. Healthy adolescents are not only key contributors to the forthcoming workforce but also a source of a country's human capital. The purpose of the article is to examine the efficacy of various Asian countries in regulating the spread of the coronavirus among adolescents. In addition to that, the paper also attempts to pinpoint the prime causes of the inefficiency of a country in regulating the same. The paper also examines the behavioural changes among adolescents across Asian countries in pre-and-post pandemic times. In this context, the study identifies the impact of adolescents' tobacco consumption, female political leadership, and accreditation on a country's efficacy to regulate adolescents' coronavirus infection. The study's empirical analysis covers twenty-one Asian countries. By using the Panel Stochastic Production Frontier, the study concludes that Kazakhstan is the most efficient country and Afghanistan is the least efficient country on the list. The inefficiency effects estimates conclude that adolescents' tobacco consumption decreases and good governance practices increase the efficiency of a country in regulating the spread of adolescent coronavirus infection. Additionally, the paper finds no significant behavioural changes among adolescents in pre-and-post pandemic times across Asian countries. The paper concludes with appropriate policy recommendations supported by empirical evidence. The paper also identifies its shortcomings and suggests potential future lines of inquiry. [ABSTRACT FROM AUTHOR]

Jonathan Shay argued that social, relational, and institutional contexts were central to understanding moral injury and conceptualised moral injury as a normative response to the betrayal of an individual's understanding of what is right by a more senior/authoritative "other". Using the conceptual lens of moral injury, this paper investigates academic staff experiences of HE during the COVID-19 pandemic and explores the rapid transition back to face-to-face teaching that took place in autumn 2020. To collect data, we used an online survey that opened in January 2021 and ran until the end of March 2021. A total of 663 complete questionnaires were received across the survey period. The questionnaire was comprised of ten topic-related questions, each of which included follow-up sub-questions and also invited participants to write in additional information. The majority of participants felt that during the course of the COVID-19 pandemic, they had acted in ways that put their own health and wellbeing at risk. Of those who had acted in ways that put their health and wellbeing at risk, they believed that their senior management were the most responsible for them acting in such ways, followed by the UK government. Qualitative data showed a systemic absence of leadership in the sector during the time, a sense of betrayal of staff and students by senior management and the government, and feelings of compulsion to act in ways which put lives at risk. On the basis of these results, we argue that there could be synergies between the situation facing healthcare staff and academics during the pandemic. Many of the experiences of HE academic staff during the pandemic reported to us in this research are resonant with the concepts of betrayal and moral injury and resulted in affective responses which we understand here in relation to feelings of guilt, shame, and anger, leading ultimately to poor mental health and wellbeing. This paper discusses implications for the HE sector going forward. [ABSTRACT FROM AUTHOR]

Though COVID-19 is no longer a pandemic but rather an endemic, the epidemiological situation related to the SARS-CoV-2 virus is developing at an alarming rate, impacting every corner of the world. The rapid escalation of the coronavirus has led to the scientific community engagement, continually seeking solutions to ensure the comfort and safety of society. Understanding the joint impact of medical and non-medical interventions on COVID-19 spread is essential for making public health decisions that control the pandemic. This paper introduces two novel hybrid machine-learning ensembles that combine supervised and unsupervised learning for COVID-19 data classification and regression. The study utilizes publicly available COVID-19 outbreak and potential predictive features in the USA dataset, which provides information related to the outbreak of COVID-19 disease in the US, including data from each of 3142 US counties from the beginning of the epidemic (January 2020) until June 2021. The developed hybrid hierarchical classifiers outperform single classification algorithms. The best-achieved performance metrics for the classification task were Accuracy = 0.912, ROC-AUC = 0.916, and F1-score = 0.916. The proposed hybrid hierarchical ensemble combining both supervised and unsupervised learning allows us to increase the accuracy of the regression task by 11% in terms of MSE, 29% in terms of the area under the ROC, and 43% in terms of the MPP metric. Thus, using the proposed approach, it is possible to predict the number of COVID-19 cases and deaths based on demographic, geographic, climatic, traffic, public health, social-distancing-policy adherence, and political characteristics with sufficiently high accuracy. The study reveals that virus pressure is the most important feature in COVID-19 spread for classification and regression analysis. Five other significant features were identified to have the most influence on COVID-19 spread. The combined ensembling approach introduced in this study can help policymakers design prevention and control measures to avoid or minimize public health threats in the future. [ABSTRACT FROM AUTHOR]

Disruption from the COVID-19 pandemic has caused major upheavals for manufacturing, and has severe implications for production networks, and the demand and supply chains underpinning manufacturing operations. This paper is the first of its kind to pull together research on both—the pandemic-related challenges and the management interventions in a manufacturing context. This systematic literature review reveals the frailty of supply chains and production networks in withstanding the pressures of lockdowns and other safety protocols, including product and workforce shortages. These, altogether, have led to closed facilities, reduced capacities, increased costs, and severe economic uncertainty for manufacturing businesses. In managing these challenges and stabilising their operations, manufacturers are urgently intervening by—investing in digital technologies, undertaking resource redistribution and repurposing, regionalizing and localizing, servitizing, and targeting policies that can help them survive in this altered economy. Based on holistic analysis of these challenges and interventions, this review proposes an extensive research agenda for future studies to pursue. [ABSTRACT FROM AUTHOR]

The governments' isolation measures to contain the transmission of COVID-19 imposed a dilemma for the people at the bottom of the pyramid. Since these people have very unreliable sources of income, a dilemma arises: they must either work under risky conditions or refrain from work and suffer from income cuts. Emergency donations of food and cleaning supplies in a pandemic context might be overlooked by government and civil society actors. This paper aims to model the effects of donations on mitigating the negative effects of COVID-19 on vulnerable communities. Applying the system dynamics method, we simulated the behaviour of the pandemic in Rio de Janeiro (Brazil) communities and the impacts that donations of food and cleaning supplies have in these settings. We administered surveys to the beneficiaries and local organisations responsible for the final distribution of donations to gather information from the field operations. The results show that increasing access to cleaning supplies in communities through donations can significantly reduce coronavirus transmission, particularly in high-density and low-resource areas, such as slums in urban settings. In addition, we also show that food donations can increase the vulnerable population's ability to afford necessities, alleviating the stress caused by the pandemic on this portion of the population. Therefore, this work helps decision-makers (such as government and non-governmental organisations) understand the impacts of donations on controlling outbreaks, especially under COVID-19 conditions, in a low-resource environment and, thus, aid these hard-to-reach populations in a pandemic setting. [ABSTRACT FROM AUTHOR]

The COVID 19 has brought unprecedented changes in the way we communicate. There is a greater accent on Virtual communication. This paper aims to establish a relationship between Emotional intelligence and the effectiveness of Virtual communication on Decision making. This empirical study is based on a sample drawn from 296 working professionals at five different levels of organizational hierarchy. A standardized questionnaire (ɑ = 0.824) was used to collect the responses of Emotional intelligence, Virtual communication, and Decision-making effectiveness. Hierarchical regression using PROCESS Macro model 1 was used to identify the moderating effect of Emotional intelligence on Virtual communication and Decision making effectiveness. Since the p-value (p ≤.007) is found significant, Emotional intelligence acts as a moderator that affects the strength of the relationship between Virtual communication effectiveness and Decision making. Validation of Task Technology fit theory is the theoretical implication of the study. Manipulation of individual dimensions in the model can reduce the dependence on technology for task completion with enhanced performance effectiveness. The findings are relevant to educators, consultants, and any professional who need to adapt Virtual communication platforms on an ongoing basis. Since work-life balance is projected as a constraint in this study, policymakers can consider policy amendments to reduce the stress caused due to Virtual communication which intrudes into their personal space. This empirical study is the first of its kind to benchmark the organizational practice of Emotional intelligence training to enhance Virtual communication and Decision making effectiveness during unprecedented times of pandemic. [ABSTRACT FROM AUTHOR]

By the end of 2021, more than 168 million students across the globe had missed a year of face-to-face schooling due to the COVID-19 pandemic. In NSW, Australia, most students engaged in learning from home for eight weeks during 2020 and a further 14 weeks during 2021. This study provides robust empirical evidence on how two years of disruptions to schooling affected student learning. Drawing on matched data for 3,827 Year 3 and 4 students from 101 NSW government schools, this paper compares student achievement growth in mathematics and reading for 2019 (pre-pandemic) and 2021 (second year of the pandemic) student cohorts. While overall there was no significant difference between cohorts, when analysed by socio-educational advantage, we were surprised to find that students in the lowest band achieved approximately three months' additional growth in mathematics. Arguably, grave concerns about the potentially dire impact of COVID-19 on the learning of disadvantaged students were met by investments that made a difference. We argue that targeted funding and system-wide initiatives to support more equitable outcomes should remain a priority after the pandemic if Australia is to meet its aspirations for excellence and equity. [ABSTRACT FROM AUTHOR]

Recent pandemic outbreaks, including the COVID-19 and SARS, have revealed that supply chains (SCs) are unable to respond to such disasters. To mitigate the destructive impacts and improve the performance of SCs, Operations Research (OR) techniques have been applied to address the issues over the last two decades. The objective of this paper is to develop a network data envelopment analysis (NDEA) model to measure the resilience and sustainability of healthcare SCs in response to the COVID-19 pandemic outbreak. In the proposed NDEA model, for the first time, outputs' weak disposability, chance-constrained programming (CCP), the convexity assumption, and the semi-oriented radial approach are aggregated. Moreover, a modified directional distance function (DDF) measure is developed to measure the overall and divisional efficiency scores. Furthermore, the proposed model can deal with different types of data such as integer-valued data, negative data, stochastic data, ratio data, and undesirable outputs. Also, several useful and interesting properties of the novel efficiency measure are presented. Finally, we measure the performance of 28 healthcare SCs to demonstrate the applicability and capability of our proposed approach. [ABSTRACT FROM AUTHOR]

Introduction: The coronavirus 2019 (COVID-19) pandemic led to a marked decrease in elective surgical volume and orthopaedic device sales. The aim of this paper was to quantify this decrease and the related financial impact on the largest hip/knee arthroplasty companies by: (1) tracking individual hip/knee company valuations; (2) calculating aggregate changes in overall hip/knee arthroplasty market valuations; and (3) quantifying quarterly hip/knee revenues relative to prior years. Materials and methods: Financial data on the top five hip/knee arthroplasty companies by size between January 1, 2019, and October 1, 2020, was collected from a Wall Street financial database, S&P Capital IQ. Changes in valuation of these companies were compared against benchmark market indices, the S&P500 and Vanguard Healthcare ETF. U.S. hip/knee arthroplasty-specific revenue for Q1 and Q2 of 2019 and 2020 was collected from Securities Exchange Commission 10-Q forms. Quarterly revenue changes were calculated using 1-2Q19 revenues as baselines and aggregate to approximate the overall hip/knee arthroplasty market. Results: The top five hip/knee companies lost $179.2 billion (32.7% loss) in market value from pre COVID-19 market highs to COVID-19 market lows (March 2020), while S&P500 and Vanguard Healthcare ETF decreased 36.1 and 33.2%, respectively. From market lows to October 2020, arthroplasty companies rallied 38.6% while the S&P500 and Vanguard Healthcare ETF regained 43.5 and 56.4% respectively. Notably, this occurred while aggregate 1Q/2Q20 revenue lagged 7.1/41.8% relative to 2019, with an overall decrease of $1.58B (24.8%). Conclusions: Similar to the overall market and healthcare sector, the top five hip/knee arthroplasty companies have recovered from their COVID market lows. Our results reveal that the valuations of hip/knee companies remained robust during COVID, even as revenues fell, likely due to strong investor confidence in the industry outlook and the greater overall healthcare system utilization. [ABSTRACT FROM AUTHOR]

Future state prediction for nonlinear dynamical systems is a challenging task. Classical prediction theory is based on a, typically long, sequence of prior observations and is rooted in assumptions on statistical stationarity of the underlying stochastic process. These algorithms have trouble predicting chaotic dynamics, "Black Swans" (events which have never previously been seen in the observed data), or systems where the underlying driving process fundamentally changes. In this paper we develop (1) a global and local prediction algorithm that can handle these types of systems, (2) a method of switching between local and global prediction, and (3) a retouching method that tracks what predictions would have been if the underlying dynamics had not changed and uses these predictions when the underlying process reverts back to the original dynamics. The methodology is rooted in Koopman operator theory from dynamical systems. An advantage is that it is model-free, purely data-driven and adapts organically to changes in the system. While we showcase the algorithms on predicting the number of infected cases for COVID-19 and influenza cases, we emphasize that this is a general prediction methodology that has applications far outside of epidemiology. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 from Wuhan, China in 2019 has spread across the world, with more than 687 million confirmed coronavirus cases still increasing. Vaccines and medicines are one aspect of fighting the pandemic outbreak, but modern Information Technologies, web/ mobile-based technologies, blockchain, and Internet of Things (IoT) devices are being used to control the pandemic outbreak at an earlier/later stage. The IoT devices with sensors, and mobile apps/ websites having self-assessment tests can help in tracking COVID-19 infections. These people's tracking information and self-assessment tests are generating huge amounts of data. This white paper introduces an IoT and cloud-based architectural framework in the COVID-19 pandemic to predict infection risk based on citizens' self-assessments and storage of data in the cloud and the intelligent technique of hesitant Intuitionistic Fuzzy Set (IFS) has been used on the self-assessment dataset to predict the risk. [ABSTRACT FROM AUTHOR]

The post-COVID-19 era has witnessed intensive engagements on latest datasets on COVID-19 experiences and the need for robust data systems to understand emerging policy pathways. There have also been extensive deliberations on how public organisations can deliver beyond immediate concerns with economic recovery and improved livelihoods. This paper draws insights from the Afrobarometer round 9 dataset on how different African governments' economies have been recovering from COVID-19 and how this has affected citizens' well-being in Kenya. The results show that despite the good recovery progress, the government has yet to stabilise high food prices, inflation, debts, job creation, etc. While national policy priorities may explain how this situation plays out, these challenges remain complex and linked to external factors that African governments may have little control over. [ABSTRACT FROM AUTHOR]

This paper problematizes the notion of "intent" through the concept of "involuntary resistance". Departing from the narratives of employees in nursing homes in Sweden during the Covid-19 pandemic in 2020 and 2021, we suggest that neoliberal norms and a local management that capitalizes on social hierarchies (sex, age, class, etc.) were the context of the strong biopolitical state management that occurred due to the Covid-19 pandemic. The friction between different forms of governing became a seedbed for an involuntary resistance with an unclear intent against the state recommendations. This sheds light upon the need to (re)frame the current dominance of specific types of knowledge that are constructed in the field of resistance. We suggest that new paths of thought are needed—within social sciences—that work towards a wider conceptualizing of resistance, which embraces practices that lie outside the common thought of dissent. [ABSTRACT FROM AUTHOR]

This paper addresses the interpretability problem of non-parametric option pricing models by using the explainable artificial intelligence (XAI) approach. We study call options written on the S&P 500 stock market index across three market regimes: pre-COVID-19, COVID-19 market crash, and post-COVID-19 recovery. Our comparative option pricing exercise demonstrates the superiority of the random forest and extreme gradient boosting models for each market regime. We also show that the model's pricing accuracy has worsened from the pre-COVID-19 to the recovery period. Moneyness was the most important price determinants across the market regimes, while the implied volatility and time-to-maturity inputs contributed intermittently to a lesser extent. During the COVID-19 crash, open interest gained more economic importance due to the increased behavioral tendencies of traders consistent with market distress. [ABSTRACT FROM AUTHOR]

This paper evaluates the stock performance of Islamic banks relative to their conventional counterparts during the initial phase of the COVID-19 crisis (from December 31, 2019, to March 31, 2020). Using 426 banks from 48 countries, we find that stock returns of Islamic banks were about 10–13% higher than those of conventional banks after controlling for a host of the bank- and country-level variables. This study explains the Islamic banks' superior crisis stock performance by exploring the potential role of pre-crisis bank efficiency. In a univariate analysis, we document higher non-parametric Data Envelopment Analysis (DEA) efficiency levels for Islamic banks than conventional banks in the year preceding the COVID-19 crisis. Our multivariate regressions show that the risk-adjusted DEA efficiency scores can explain crisis stock returns for Islamic banks but not conventional banks. The evidence is robust to alternative measures of stock returns, efficiency models, and other empirical strategies. Finally, we present insight on the importance of key bank characteristics in determining the stock returns of conventional banks during the crisis period. [ABSTRACT FROM AUTHOR]

The outbreak of the COVID-19 pandemic has adversely affected the most important areas of the modern world. One of the challenges related to counteracting the effects of the pandemic it was necessary to develop methods for the quantitative determination of pharmaceuticals used in the treatment of patients suffering from this disease and its long-term effects. Budesonide (BUD) is a widely available and inexpensive corticosteroid used extensively not only among people suffering from COVID-19, but also asthma and other respiratory diseases. A significant increase in the consumption of drugs containing this component requires the development of new BUD determination methods, especially in real samples. This paper presents a new voltammetric method for BUD determination at renewable silver amalgam film electrode (Hg(Ag)FE). The electrochemical measurements were conduced in the supporting electrolyte containing 80% of methyl alcohol, 0.04 mol L−1 Britton–Robinson buffer (pH 3.0) and 20 mg mL−1 of NaClO4 under optimized differential pulse voltammetry (DPV) parameters. Detailed studies of the behaviour of the BUD on the surface of Hg(Ag)FE demonstrated the quasi-irreversible nature of the diffusion-controlled, two electrons and two protons reduction process. A calibration curve in the range from 1.0 to 290 µg mL−1 shows limit of detection and limit of quantification equal to 0.06 and 0.21 µg mL−1, respectively. The impact of numerous interferences over a wide range of concentrations on BUD signals was analysed and evaluated. The utility of the proposed method was verified by the quantitative analysis of BUD in two pharmaceutical products and the spiked water samples. [ABSTRACT FROM AUTHOR]

Inpatient educational conferences are a key part of internal medicine residency training. Many residencies made conferences virtual during the COVID-19 pandemic, and are now returning to in-person sessions. As we navigate this change, we can seize this opportunity to re-evaluate the role that inpatient conferences serve in resident education. In this paper, we briefly review the history of inpatient educational conferences before offering five recommendations for improvement. Our recommendations include grounding conference formats in educational theory, leveraging the expertise of all potential educators, broadening content to include health equity and justice throughout all curricula, and explicitly focusing on cultivating community among participants. Recognizing that each residency program is different, we anticipate that these recommendations may be implemented differently based on program size, available resources, and current institutional practices. We also include examples of prior successful curricular reforms aligned with our principles. We hope these recommendations ensure inpatient conferences continue to be a central part of residency education for future generations of internal medicine residents. [ABSTRACT FROM AUTHOR]

A primary community prevention approach in Iceland was associated with strong reductions of substance use in adolescents. Two years into the implementation of this prevention model in Chile, the aim of this study was to assess changes in the prevalence of adolescent alcohol and cannabis use and to discuss the impact of the COVID-19 pandemic on the substance use outcomes. In 2018, six municipalities in Greater Santiago, Chile, implemented the Icelandic prevention model, including structured assessments of prevalence and risk factors of substance use in tenth grade high school students every 2 years. The survey allows municipalities and schools to work on prevention with prevalence data from their own community. The survey was modified from an on-site paper format in 2018 to an on-line digital format in a shortened version in 2020. Comparisons between the cross-sectional surveys in the years 2018 and 2020 were performed with multilevel logistic regressions. Totally, 7538 participants were surveyed in 2018 and 5528 in 2020, nested in 125 schools from the six municipalities. Lifetime alcohol use decreased from 79.8% in 2018 to 70.0% in 2020 (X2 = 139.3, p < 0.01), past-month alcohol use decreased from 45.5 to 33.4% (X2 = 171.2, p < 0.01), and lifetime cannabis use decrease from 27.9 to 18.8% (X2 = 127.4, p < 0.01). Several risk factors improved between 2018 and 2020: staying out of home after 10 p.m. (X2 = 105.6, p < 0.01), alcohol use in friends (X2 = 31.8, p < 0.01), drunkenness in friends (X2 = 251.4, p < 0.01), and cannabis use in friends (X2 = 217.7, p < 0.01). However, other factors deteriorated in 2020: perceived parenting (X2 = 63.8, p < 0.01), depression and anxiety symptoms (X2 = 23.5, p < 0.01), and low parental rejection of alcohol use (X2 = 24.9, p < 0.01). The interaction between alcohol use in friends and year was significant for lifetime alcohol use (β = 0.29, p < 0.01) and past-month alcohol use (β = 0.24, p < 0.01), and the interaction between depression and anxiety symptoms and year was significant for lifetime alcohol use (β = 0.34, p < 0.01), past-month alcohol use (β = 0.33, p < 0.01), and lifetime cannabis use (β = 0.26, p = 0.016). The decrease of substance use prevalence in adolescents was attributable at least in part to a reduction of alcohol use in friends. This could be related to social distancing policies, curfews, and homeschooling during the pandemic in Chile that implied less physical interactions between adolescents. The increase of depression and anxiety symptoms may also be related to the COVID-19 pandemic. The factors rather attributable to the prevention intervention did not show substantial changes (i.e., sports activities, parenting, and extracurricular activities). [ABSTRACT FROM AUTHOR]

Strict lockdowns have been employed by many of the world's nations as a public health response to COVID-19. However, concerns have been expressed as to how such public health responses disturb the human ecosystem. In this paper, we report on findings from a longitudinal study of Australian parents in which we investigated how state differences in government-mandated lockdowns affect the relationship well-being (i.e., relationship satisfaction and loneliness) of parents. We situated the study of the relational effects of strict lockdowns within the Vulnerability Stress Adaptation Model (VSAM, Karney & Bradbury, 1995) that considers the role of parents' pre-existing vulnerabilities (i.e., psychological distress and attachment insecurity), life stressors (pre-pandemic and COVID-19 stressors), and adaptive relationship processes (constructive communication and perceived partner support). A total of 1942 parents completed 14 waves of assessments of relationship satisfaction and loneliness over a 13.5-month period as well as baseline assessments of personal vulnerabilities, life stressors, and adaptive relationship processes. Parents with high relationship adaptations and low vulnerabilities evidenced the highest relationship well-being (i.e., high satisfaction and low loneliness) during changes in lockdown restrictions, while parents with moderate relationship adaptations and vulnerabilities experienced the poorest well-being. Differences in state lockdown restrictions (i.e., Victoria [long and strict lockdown policy] vs all other states) were associated with differences in relationship well-being for parents with high relationship adaptations. Specifically, Victorian parents experienced significant declines in relationship well-being compared to non-Victorian parents. Our findings provide novel insights into how government-mandated social restrictions can disrupt the relational ecology of parents. [ABSTRACT FROM AUTHOR]

Introduction: A new national survey has been carried out by the Italian Centers for Cognitive Disorders and Dementias (CCDDs). The aim of this new national survey is to provide a comprehensive description of the characteristics, organizational aspects of the CCDDs, and experiences during the COVID-19 pandemic. Methods: A list of all national CCDDs was requested from the delegates of each Italian region. The online questionnaire is divided in two main sections: a profile section, containing information on location and accessibility, and a data collection form covering organization, services, treatments, activities, and any service interruptions caused by the COVID-19 outbreak. Results: In total, 511 out of 534 (96%) facilities completed the profile section, while 450 out of 534 (84%) CCDDs also completed the data collection form. Almost half of the CCDDs (55.1%) operated for 3 or fewer days a week. About one-third of the facilities had at least two professional figures among neurologists, geriatricians and psychiatrists. In 2020, only a third of facilities were open all the time, but in 2021, two-thirds of the facilities were open. Conclusion: This paper provides an update on the current status of CCDDs in Italy, which still shows considerable heterogeneity. The survey revealed a modest improvement in the functioning of CCDDs, although substantial efforts are still required to ensure the diagnosis and care of patients with dementia. [ABSTRACT FROM AUTHOR]

Objectives: The COVID-19 pandemic has had significant impacts on maternal mental health. We explored the lived experiences of women with perinatal depression and anxiety to elucidate their perceptions of how the pandemic influenced their mental health and access to care. Methods: We conducted a qualitative descriptive study using semi-structured interviews. From March to October 2021, purposive sampling was used to recruit a socio-demographically diverse sample of women with self-reported perinatal depression or anxiety who were pregnant or within one year postpartum between March 2020 and October 2021. Interviews were conducted remotely and thematically analyzed. Results: Fourteen women were interviewed. Three major themes arose. Theme 1, Negative impacts of COVID-19 on symptoms of depression and anxiety, described how the pandemic magnified underlying symptoms of depression and anxiety, increased social isolation, generated anxiety due to fears of COVID-19 infection, and caused economic stress. In theme 2, Negative impacts of COVID-19 on access to and quality of health care, women described stressful and isolating delivery experiences, negative psychological impact of partners not being able to participate in their perinatal health care, interruptions and barriers to mental health treatment, and challenges in using telehealth services for mental health care. Theme 3, Positive impacts of COVID-19 on mental health, identified advantages of increased telehealth access and ability to work and study from home. Conclusions for Practice: The COVID-19 pandemic negatively affected women with perinatal depression and anxiety by magnifying underlying symptoms, increasing stress and social isolation, and disrupting access to mental health care. Findings provide support for policies and interventions to prevent and address social isolation, as well as optimization of telehealth services to prevent and address gaps in perinatal mental health treatment. Significance: What is Already Known on this Subject? Quantitative data suggest that the pandemic increased rates of perinatal mental illness. Yet the perspectives of women with perinatal depression and anxiety on how the pandemic affected their mental health and access to care remain underreported. What this Study adds? This paper offers new insight from the lived experience of women with perinatal depression and anxiety on ways the pandemic negatively and positively affected their mental health and access to mental health care. Implications for interventions, policies, and clinical practice are discussed. [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]

During the COVID-19 pandemic, cancer patients were among the most vulnerable patient groups to the SARS-CoV-2 infection effects. This paper aimed to conduct an umbrella review and meta-meta-analysis to determine the severity of disease in cancer patients affected by COVID-19. The umbrella review and meta-meta-analysis were undertaken according to the PRISMA and MOOSE guidelines. The PubMed/Medline, Web of Science, and Scopus databases were searched for published papers from the start of the pandemic through July 18, 2022. The pooled effect sizes (ES) and odds ratios (ORs) were calculated using a random effect model in the 95% confidence interval (CI) for ICU (Intensive Care Unit) admissions and mortality in cancer patients infected with SARS-CoV-2. Egger's linear regression test, schematic illustrations of funnel plots, and Begg and Mazumdar's rank correlation tests were used to quantify the possibility of publication bias. The pooled ES was calculated based on 1,031,783 participants, and mortality was significantly increased in cancer patients affected by COVID-19 (OR = 2.02, %95 CI: 1.74–2.35, p < 0.001). The pooled ES for ICU admission was also significantly increased in cancer patients infected with SARS-CoV-2 (OR = 1.84, %95 CI: 1.44–2.34, p < 0.001). As a result, this synthesis of systematic reviews and meta-analyses by the meta-meta-analysis method revealed that disease severity is higher in cancer patients affected by COVID-19. Since cancer patients are a more sensitive and specific patient group, they should be evaluated more carefully, especially during the COVID-19 pandemic and other pandemics that may occur in the future. [ABSTRACT FROM AUTHOR]

While the whole world struggles with the COVID-19 pandemic, there are many different measures taken by countries. In this sense, the distribution of free masks to citizens between the ages of 20–65 in Turkey is one of the important measures taken against to spread of the pandemic. This distribution process is carried out through pharmacies and people can obtain their masks from any pharmacy in their area of residence. However, this situation may cause some pharmacies to be very busy, and thus social distance cannot be maintained and health and safety of the people may be threatened. In this paper, we aim to prioritize pharmacies so that only determined pharmacies in certain regions perform mask distribution process to prevent virus transmission. For this purpose, Esenler district is taken into consideration for a pilot study which is one of the risky regions in terms of virus spread in Istanbul, Turkey. Multi-criteria decision-making approach (MCDM) is used because of the necessity of handling many factors in decision-making process and the contradiction of evaluation factors in the prioritization of pharmacies. In order to best model the uncertainty in the decision process, the MCDM approach is applied in a fuzzy environment. In addition, spherical fuzzy AHP and VIKOR MCDM approaches are used as novel hybrid method in this paper. As a result of spherical fuzzy multi-criteria analysis, the pharmacies that need to provide free mask distribution in the Esenler region have been successfully identified. [ABSTRACT FROM AUTHOR]

This paper presents the Cognitive and Social WELL-being (CoSoWELL) project that consists of two components. One is a large corpus of narratives written by over 1000 North American older adults (55+ years old) in five test sessions before and during the first year of the COVID-19 pandemic. The other component is a rich collection of socio-demographic data collected through a survey from the same participants. This paper introduces the first release of the corpus consisting of 1.3 million tokens and the survey data (CoSoWELL version 1.0). It also presents a series of analyses validating design decisions for creating the corpus of narratives written about personal life events that took place in the distant past, recent past (yesterday) and future, along with control narratives. We report results of computational topic modeling and linguistic analyses of the narratives in the corpus, which track the time-locked impact of the COVID-19 pandemic on the content of autobiographical memories before and during the COVID-19 pandemic. The main findings demonstrate a high validity of our analytical approach to unique narrative data and point to both the locus of topical shifts (narratives about recent past and future) and their detailed timeline. We make the CoSoWELL corpus and survey data available to researchers and discuss implications of our findings in the framework of research on aging and autobiographical memories under stress. [ABSTRACT FROM AUTHOR]

In this paper, we address the controversies of epidemic control planning by developing a novel Simulation-Deep Reinforcement Learning (SiRL) model. COVID-19 reminded constituents over the world that government decision-making could change their lives. During the COVID-19 pandemic, governments were concerned with reducing fatalities as the virus spread but at the same time also maintaining a flowing economy. In this paper, we address epidemic decision-making regarding the interventions necessary given of the epidemic based on the purpose of the decision-maker. Further, we intend to compare different vaccination strategies, such as age-based and random vaccination, to shine a light on who should get priority in the vaccination process. To address these issues, we propose a simulation-deep reinforcement learning (DRL) framework. This framework is composed of an agent-based simulation model and a governor DRL agent that can enforce interventions in the agent-based simulation environment. Computational results show that our DRL agent can learn effective strategies and suggest optimal actions given a specific epidemic situation based on a multi-objective reward structure. We compare our DRL agent's decisions to government interventions at different periods of time during the COVID-19 pandemic. Our results suggest that more could have been done to control the epidemic. In addition, if a random vaccination strategy that allows super-spreaders to get vaccinated early were used, infections would have been reduced by 32% at the expense of 4% more deaths. We also show that a behavioral change of fully quarantining 10% of the risky individuals and using a random vaccination strategy leads to a reduction of the death toll by 14% and 27% compared to the age-based vaccination strategy that was implemented and the New Jersey reported data, respectively. We have also demonstrated the flexibility of our approach to be applied to other locations by validating and applying our model to the COVID-19 case in the state of Kansas. [ABSTRACT FROM AUTHOR]

As COVID-19 has spread rapidly, detection of the COVID-19 infection from radiology and radiography images is probably one of the quickest ways to diagnose the patients. Many researchers found the necessity to utilize chest X-ray and chest computed tomography imaging to diagnose COVID-19 infection. In this paper, our objective is to minimize the false negatives and false positives in the detection process. Reduction in the number of false negatives minimizes community spread of the COVID-19 pandemic. Reducing false positives help people avoid mental trauma and wasteful expenses. This paper proposes a novel weighted consensus model to minimize the number of false negatives and false positives without compromising accuracy. In the proposed novel weighted consensus model, the accuracy of individual classification models is normalized. While predicting, different models predict different classes, and the sum of the normalized accuracy for a particular class is then considered based on a predefined threshold value. We used traditional Machine Learning classification algorithms like Linear Regression, Support Vector Machine, k-Nearest Neighbours, Decision Tree, and Random Forest for the weighted consensus experimental evaluation. We predicted the classes, which provided better insights into the condition. The proposed model can perform as well as the existing state-of-the-art technique in terms of accuracy (99.64%) and reduce false negatives and false positives. [ABSTRACT FROM AUTHOR]

This paper reports an ongoing exercise concerning the design of a logistics App to support operations within Farmers' Markets in Mexico. This exercise is part of a wider research agenda focused on 'Supporting Alternative Food Networks' (SAFeNET). This is a research agenda to conceive, build, implement, and develop better-informing decision-making processes that support effective and efficient AFNs (also known as Short Food Supply Chains) logistics operations in a digital environment, through smooth flows of goods and information among producers, AFNs coordinators, and consumers. This view calls for taking a systemic approach to help collectives of people to improve their autonomy and viability. Initial plans were to conduct this collaborative design exercise, using the Viable System Model (VSM) as a conversational tool. Accordingly, a series of face-to-face interviews and a focus group were planned. However, the lockdown due to COVID-19 forced researchers to abandon the face-to-face option and conduct the primary data collection online. The VSM intervention had to be adapted for its use on an online platform, in such a way that the platform would support knowledge building interactively, with a series of participants. This paper describes the format and visual appearance of the online VSM framework, its application, and the lessons learned through this exercise. Two points deserve to be highlighted: First, although the exercise outcome was very valuable for the next stage of the design, the participants' capacity for collective and individual reflection during the workshop was limited. Second, participants continued adding comments via the adopted online visual collaboration platform after the workshop ended, showing an understanding of the process and commitment beyond the researchers' expectations. The outcomes from this experiment are promissory, suggesting that online Systems Thinking interventions deserve further development. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic has exacerbated the pre-existing vulnerabilities and inequalities in societies. In this paper we analyse the categories that have suffered more than others from the pandemic and the restrictions on social life in terms of mental health. We rely on the Serendipity project based on a survey administered between November 2021 and February 2022 to a sample of Italian physicians (n = 1281). The survey aimed to assess the perception of general practitioners, paediatricians, geriatricians, and mental health specialists (psychiatrists, neurologists, child neuropsychiatrists), about changes in the mental health of the population as an effect of the COVID-19 pandemic and the lockdown. The strategies implemented by the doctors interviewed in terms of the intensity of the prevention, emergence, and treatment of mental health interventions, and their association with physicians' characteristics and their opinions on patient vulnerability have been illustrated by means of a multiple correspondence analysis. An overall result of the survey is the consensus of doctors on the worsening of mental health in general population, especially among their patients, due to the pandemic and on the onset of new discomforts. The most exposed individuals to the risk of onset or worsening of mental disorders include women, young people, and patients with psychiatric comorbidity. The paper also illustrates the interventions put in place by the physicians and deemed necessary from a public heath response perspective, that include providing psychoeducation to the general population, improving telehealth services, and increasing financial and human resources for community-based care. [ABSTRACT FROM AUTHOR]

Background: The world is suffering from a new strain of the coronavirus family-Covid-19. This virus strain affected different organs in the human body with a wide range of mild symptoms and moderate signs to severe and deadly ones. Multiple organs can be infected, and one of these organs is the eye. The eye is a vital organ that consists of vascular tissues and is connected to the respiratory tract through the tears and the nasolacrimal duct. Methods: Recent papers and research from PubMed, Researchgate, and Google Scholar were cited and thoroughly discussed. These papers were chosen based on their relevancy, reliability, publication year, published journal, and ease of accessibility to the paper itself. Results: The theory concluded that the ocular surface might consider a pathway for the virus attack and infection causation through the tears and the angiotensin-converting enzyme 2 located in the eye. This article thoroughly reviewed the history, the existing aspects of Covid-19, the ocular system features, and the claims about the possible involvement of the eye in the virus transmission along with the eye infection. There was no consensus on the eye's involvement theory. Conclusion: The authors highlighted the extra work and research needed to be conducted to prove or deny these claims to provide a better understanding of the immune response of the eye to Covid-19 infection. [ABSTRACT FROM AUTHOR]

The African continent has witnessed most health crises including yellow fever, meningitis, cholera, and Ebola. Two recent health crises faced by Ghana have been the Ebola virus and the Covid-19 virus diseases. This paper attempts to compare these two crises to understand what preparedness approaches were used by the government of Ghana during these two crises. Also, the paper attempts to identify what the similarities and differences have been and why these similarities and differences existed in the preparedness towards these crises that happened over different periods and whether Ghana's Covid-19 preparedness was based on lessons from Ebola. Through the policy legacies analytical framework and a review of the literature, the paper argues that Ghana's preparedness shows a lot of similarities from the training of healthcare workers, the health infrastructure introduced, approaches to public engagement, and political decisions made to fight both crises. [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]

In March 2020, the UK was placed in lockdown following the spread of the Covid-19 virus. Just as legitimate workplaces made changes to enable their employees to work from home, the illicit drugs trade also made alternative arrangements, adapting its supply models to ensure continuity of operations. Based upon qualitative interviews with 46 practitioners, this paper assesses how front-line professionals have experienced and perceived the impact of Covid-19 on child criminal exploitation and County Lines drug supply in the UK. Throughout the paper, we highlight perceived adaptations to the County Lines supply model, the impact of lockdown restrictions on detection and law enforcement activities aimed at County Lines, and on efforts to safeguard children and young people from criminal exploitation. Our participants generally believed that the pandemic had induced shifts to County Lines that reflected an ongoing evolution of the drug supply model and changes in understanding or attention because of Covid-19 restrictions, rather than a complete reconstitution of the model itself. Practitioners perceived that Covid-19 has had, and continues to have, a significant impact on some young people's vulnerability to exploitation, on the way in which police and frontline practitioners respond to County Lines and child criminal exploitation, and on the way illegal drugs are being moved and sold. [ABSTRACT FROM AUTHOR]

This paper reviews major structural drivers of place-based health disparities in the context of Canada, an industrialized nation with a strong public health system. Likelihood that the COVID-19 pandemic will facilitate rejuvenation of Canada's northern and remote areas through remote working, advances in online teaching and learning, and the increased use of telemedicine are also examined. The paper concludes by identifying some common themes to address healthcare disparities for northern and remote Canadian residents. [ABSTRACT FROM AUTHOR]

Public protest continued to represent a prominent form of social activism in democratic societies during the COVID-19 pandemic. In Australia, a lack of specific legislation articulating protest rights has meant that, in the context of pandemic restrictions, such events have been treated as illegal mass gatherings. Numerous large protests in major cities have, indeed, stirred significant public debate regarding rights of assembly during COVID-19 outbreaks. The ethics of infringing on protest rights continues to be controversial, with opinion divided as to whether public health goals or human rights should take precedence. This paper applies public health ethical theory to an in-depth analysis of arguments on both sides of the debate. Using the Nuffield Council on Bioethics framework as a backdrop, proportionality and necessity of restrictions are understood as key concepts that are common to both public health and human rights perspectives. The analysis presented here finds a middle-ground between the prevailing arguments on opposing sides and is further able to rationalize the use of protest itself as an important element of a mature public health ethics response to restrictive policy. Thus, this paper aims to influence public health policy and legislation regarding protest rights during public health emergencies. [ABSTRACT FROM AUTHOR]

This paper offers some observations from a practitioner perspective on Swiss measures to support businesses during the Covid-19 pandemic, as a complement to the paper 'Governmental measures in Switzerland against mass bankruptcies during the Covid-19 pandemic' by Rodriguez and Ulli in this volume. A brief overview of the main fiscal and non-fiscal measures is followed by analysis of the reasons for non-use of a major non-fiscal measure (a new moratorium), and some suggestions as to the lessons that can be learned from this for the design of analogous relief policies in future crises. [ABSTRACT FROM AUTHOR]

Fabrizio and Caputo suggested an extraordinary definition of fractional derivative, which has been used in many fields. The SIDARTHE infectious disease model with regard to COVID-19 is studied by the new notion in this paper. Making use of the Banach fixed point theorem, the existence and uniqueness of the model's solution are demonstrated. Then, an efficient method is utilized to deduce the iterative scheme. Finally, some numerical simulations of the model under various fractional orders and parameters are shown. From the computed result, we can see that it not only supports the theoretical demonstration, but also has an intensive insight into the characteristics of the model. [ABSTRACT FROM AUTHOR]

The outburst of the COVID-19 pandemic challenged vulnerable populations such as individuals with significant mental illness. In this fresh focus, we describe the innovative development of the UPSIDES mental health peer support intervention, in face of the COVID-19 pandemic in Israel. While the research program is still ongoing, in this paper we focus on the processes and lessons learned from dealing with the rapidly changing circumstances of the pandemic. We portray additional activities conducted above and beyond the UPSIDES protocol in order to maintain continuation and prevent dropout. We learned that an essential combination of keeping a close adherence with the core peer principles and UPSIDES' systematic program and the use of flexible telecommunication means, helped to maintain social connection and service users' participation throughout these times. The sudden pandemic challenges appeared to level out power imbalances and accelerated the formation of reciprocal and supportive relational interactions within the intervention. These processes highlight experiential knowledge as a unique asset, and peer support services as useful in supporting individuals with significant mental illness throughout COVID-19. [ABSTRACT FROM AUTHOR]

This paper investigates the changes in time use, working conditions and subjective time wealth during the COVID-19 pandemic in Germany. Our analysis draws on panel data collected before and during the first lockdown among 786 employees. It employs a recently developed scale on time wealth which has been suggested as a comprehensive measure to capture the subjective experience of time. We provide separate analyses according to gender and essential occupation. First-difference regressions are applied to examine how changes in time use and changes in working conditions during the lockdown affected subjective time wealth. Our results show a general growth in time wealth during the lockdown which is, among other factors, driven by a decline in work hours and an increase in sleep duration. We also find positive effects on time wealth from decreased time pressure at work, more autonomy in organising one's working day, and an improved reconciliation of work and private life. This study contributes to existing research by identifying key aspects how to improve time wealth among employees. [ABSTRACT FROM AUTHOR]