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Goal: This study was developed to explicate underlying organizational factors contributing to the deterioration of primary care clinicians' mental health during the COVID-19 pandemic., Methods: Using data from the Larry A. Green Center for the Advancement of Primary Health Care for the Public Good's national survey of primary care clinicians from March 2020 to March 2022, a multidisciplinary team analyzed more than 11,150 open-ended comments. Phase 1 of the analysis happened in real-time as surveys were returned, using deductive and inductive coding. Phase 2 used grounded theory to identify emergent themes. Qualitative findings were triangulated with the survey's quantitative data., Principal Findings: The clinicians shifted from feelings of anxiety and uncertainty at the start of the pandemic to isolation, lack of fulfillment, moral injury, and plans to leave the profession. The frequency with which they spoke of depression, burnout, and moral injury was striking. The contributors to this distress included crushing workloads, worsening staff shortages, and insufficient reimbursement. Consequences, both felt and anticipated, included fatigue and demoralization from the inability to manage escalating workloads. Survey findings identified responses that could alleviate the mental health crisis, namely: (1) measuring and customizing workloads based on work capacity; (2) quantifying resources needed to return to sufficient staffing levels; (3) promoting state and federal support for sustainable practice infrastructures with less administrative burden; and (4) creating patient visits of different lengths to rebuild relationships and trust and facilitate more accurate diagnoses., Practical Applications: Attention to clinicians' mental health should be rapidly directed to on-demand, confidential mental health support so they can receive the care they need and not worry about any stigma or loss of license for accepting that help. Interventions that address work-life balance, workload, and resources can improve care, support retention of the critically important primary care workforce, and attract more trainees to primary care careers., (Copyright © 2024 Foundation of the American College of Healthcare Executives.)

Summary: Virtual education is a promising tool for expanding surgical training and continuing education. The authors present their preferred platforms for virtual surgical education, and discuss security and privacy concerns. Maintaining communication and keeping sessions engaging require special consideration when education is done virtually. The limitations to virtual education may soon be mitigated by new technologies. In this article, the authors aim to describe the benefits, current modalities, tips for use, and future directions for virtual education as it pertains to plastic surgeons and trainees during the current coronavirus pandemic., (Copyright © 2021 by the American Society of Plastic Surgeons.)

Background: The COVID-19 pandemic demanded quick exchanges between experts and institutions supporting governments to provide evidence-based information in response to the crisis. Initially, there was no regular cross-country forum in the field of population health. This paper describes the set-up and benefits of implementing such a forum., Methods: A group of public health practitioners from academia, national public health institutes and ministries of health decided in April 2020 to meet bi-monthly to discuss a vast array of population health topics in a structured format called a Rapid Exchange Forum (REF). An ad-hoc mailing group was established to collect responses to questions brought forward in the forum from at least five countries within 24 h. This endeavour, which evolved as network of networks was awarded an EU grant in autumn 2020 and was called PHIRI (Population Health Information Research Infrastructure)., Results: Responses from up to 31 countries were compiled and shared immediately via the European Health Information Portal. This exchange was complemented by special REFs that focused on the advantages and disadvantages of vaccination, for example. By July 2023, 54 REFs had taken place with topics going beyond COVID-19., Conclusion: The REF demonstrated its value for quick yet evidence-based cross-country exchange in times of crisis and was highly appreciated by countries and European Commission. It demonstrated its sustainability even after the acute crisis by expanding the topics covered and managing to continue exchange with the aim of capacity building and mutual learning, making it a true EU response and coordination mechanism., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Public Health Association.)

This paper combines considerations from ethics, medicine and public health policy to articulate and defend a systematic case for mask wearing mandates (MWM). The paper argues for two main claims of general interest in favour of MWM. First, MWM provide a more effective, just and fair way to tackle the ongoing COVID-19 pandemic than policy alternatives such as laissez-faire approaches, mask wearing recommendations and physical distancing measures. And second, the proffered objections against MWM may justify some exemptions for specific categories of individuals, but do not cast doubt on the justifiability of these mandates. Hence, unless some novel decisive objections are put forward against MWM, governments should adopt MWM., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: Governments faced formidable challenges in coordinating public health responses to the COVID-19 pandemic. This study aims to enhance the understanding of effective organizational leadership during crises by investigating the factors influencing the turnover of health leaders during the COVID-19 pandemic in Brazil., Design/methodology/approach: Using primary data encompassing all appointments and dismissals of federal and state health secretaries, this paper conducted a quantitative analysis of the relational and reputational factors that contributed to leader turnover during the COVID-19 pandemic. This paper also examined whether leaders' management and public health experience increase the duration of tenure., Findings: States encountered significant challenges in retaining experienced and effective leadership during the health emergency, primarily due to political conflicts in policymaking and, to a lesser extent, allegations of corruption. Furthermore, leaders with expertise in public health were found to be less likely to be removed from office. However, managerial experience did not prolong the tenure of state health secretaries during the emergency., Research Limitations/implications: Since most health leaders have public health and management experience, the contributions of each factor to the duration of a secretary's tenure are difficult to separate and analyze separately., Practical Implications: This study provides empirical insights into what factors drive health leader turnover during major health emergencies., Social Implications: During major health emergencies, health leaders often strongly disagree with elected officials on the response. This paper test how crisis leadership theories help explain state health leaders' duration in one of the world's largest public health systems during the COVID-19 pandemic. This paper find that policy disagreements contributed to significant turnover., Originality/value: To the best of the authors' knowledge, this paper is the first that are aware of that uses novel primary data on public health executive leader characteristics and turnover causes in the context of the COVID-19 pandemic. It provides empirical evidence contributing to the crisis leadership literature by examining health leader turnover in one of the world's largest public health systems., (© Emerald Publishing Limited.)

Objectives: Belgium experienced multiple COVID-19 waves that hit various groups in the population, which changed the mortality pattern compared to periods before the pandemic. In this study, we investigated the geographical excess mortality trend in Belgium during the first year of the COVID-19 pandemic., Methods: We retrieved the number of deaths and population data in 2020 based on gender, age, and municipality of residence, and we made a comparison with the mortality data in 2017-2019 using a spatially discrete model., Results: Excess mortality was significantly associated with age, gender, and COVID-19 incidence, with larger effects in the second half of 2020. Most municipalities had higher risks of mortality with a number of exceptions in the northeastern part of Belgium. Some discrepancies in excess mortality were observed between the north and south regions., Conclusions: This study offers useful insight into excess mortality and will aid local and regional authorities in monitoring mortality trends., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Aim: Identify and map international evidence regarding innovations led by or involving advanced practice nurses in response to COVID-19., Background: COVID-19 necessitated unprecedented innovation in the organization and delivery of healthcare. Although advanced practice nurses have played a pivotal role during the pandemic, evidence of their contributions to innovations has not been synthesized. Evidence is needed to inform policies, practices, and research about the optimal use of advanced practice nurses., Methods: A scoping review was conducted and reported using the PRISMA-ScR checklist. Electronic databases were searched for peer-reviewed articles published between January 2020 and December 2021. Papers were included that focused on innovations emerging in response to COVID-19 and involved advanced practice nurses., Results: Fifty-one articles were included. Four themes were identified including telehealth, supporting and transforming care, multifaceted approaches, and provider education. Half of the articles used brief and mostly noncomparative approaches to evaluate innovations., Conclusion: This is the first synthesis of international evidence examining the contributions of advanced practice nurses during the pandemic. Advanced practice nurses provided leadership for the innovation needed to rapidly respond to healthcare needs resulting from COVID-19. Innovations challenged legislative restrictions on practice, enabled implementation of telehealth and new models of care, and promoted evidence-informed and patient-centered care., Implications for Practice: Advanced practice nurses led, designed, implemented, and evaluated innovations in response to COVID-19. They facilitated the use of telehealth, supported or transformed models of care, and enabled health providers through education, mentorship, and mental health support., Implication for Policy: Advanced practice nurses are a critical resource for innovation and health system improvement. Permanent removal of legislative and regulatory barriers to their full scope of practice is needed., (© 2023 International Council of Nurses.)

Background: The COVID-19 pandemic forced governments, multilateral public health organisations and research institutions to undertake research quickly to inform their responses to the pandemic. Most COVID-19-related studies required swift approval, creating ethical and practical challenges for regulatory authorities and researchers. In this paper, we examine the landscape of ethics review processes in Africa during public health emergencies (PHEs)., Methods: We searched four electronic databases (Web of Science, PUBMED, MEDLINE Complete, and CINAHL) to identify articles describing ethics review processes during public health emergencies and/or pandemics. We selected and reviewed those articles that were focused on Africa. We charted the data from the retrieved articles including the authors and year of publication, title, country and disease(s) reference, broad areas of (ethical) consideration, paper type, and approach., Results: Of an initial 4536 records retrieved, we screened the titles and abstracts of 1491 articles, and identified 72 articles for full review. Nine articles were selected for inclusion. Of these nine articles, five referenced West African countries including Liberia, Guinea and Sierra Leone, and experiences linked to the Ebola virus disease. Two articles focused on South Africa and Kenya, while the other two articles discussed more general experiences and pitfalls of ethics review during PHEs in Africa more broadly. We found no articles published on ethics review processes in Africa before the 2014 Ebola outbreak, and only a few before the COVID-19 outbreak. Although guidelines on protocol review and approval processes for PHEs were more frequently discussed after the 2014 Ebola outbreak, these did not focus on Africa specifically., Conclusions: There is a gap in the literature about ethics review processes and preparedness within Africa during PHEs. This paper underscores the importance of these processes to inform practices that facilitate timely, context-relevant research that adequately recognises and reinforces human dignity within the quest to advance scientific knowledge about diseases. This is important to improve fast responses to PHEs, reduce mortality and morbidity, and enhance the quality of care before, during, and after pandemics., (© 2024. The Author(s).)

In this paper, we present findings from four separate studies using different data sources and methods to examine Chinese attitudes toward the United States amid the COVID-19 pandemic. The empirical results consistently indicate a marked and significant decline in Chinese attitudes toward the US between late 2019 and the end of 2022. Using a quasi-experimental design and granular survey data that exploit daily variations in public opinion, we offer additional evidence that the decline in Chinese attitudes toward the United States followed a distinct pattern not true for Chinese attitudes toward other countries. Specifically, the rise in Chinese unfavorability toward the United States closely corresponded to the heightened Chinese attention to the pandemic's progression in the United States. These results collectively suggest a causal effect of COVID-19, shedding light on how public health crises, international relations, and media jointly shape the increasing enmity between the two great powers., Competing Interests: Competing interests statement:The authors declare no competing interest.

Is there a "missing device" for respiratory personal protection? Does it exist an easy-to-use device, allowing extensive use in everyday settings by the population, maximizing tolerability and low visual and physical invasiveness protecting from a wide range of threats including airborne pathogens, hence including the particle range of fine and ultrafine particles? Looking at the recent past, in the urgency of finding ready-to-use solutions for the respiratory protection of the population during the outbreak of the SARS-CoV-2 pandemic, devices for occupational safety have been used, such as filtering face masks. These are devices intended for workers operating during work shifts in environments characterized by potential high risk, known a priori, often directly sensible; this makes wearers motivated to tolerate discomfort for a given period to face a localized risk, and safety managers determined to supervise compliance with usage specifications. Their use by general population has implied known shortcomings, such as weak compatibility with relational work and activities, low tolerability during prolonged use, low compliance with the proper use of the device, all of this lessening actual protection. The need for a new perspective has emerged, targeting effectiveness in whole daily life, rather than punctual efficacy. Nasal filters are promising candidates to protect individuals throughout the day during the most varied activities, but they lack a systematic definition as a device and as a product; it follows that the high complexity needed to reach an effective performance envelop is generally underestimated. By reviewing available literature, the present paper draws on the experience from the pandemic and infers systematic product specifications and characterization methods for a new, effective personal respiratory protection device; these specifications are compared with the stringent constraints associated with the endonasal applications and, based on air filtration state of the art, quantifies the need for technology disruption and outlining possible new development paths., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

The coronavirus disease 2019 (COVID-19) pandemic has affected our lives in all aspects, including key fields such as social interaction and economic supply chains. The field of chemical, biological, radiological, nuclear, and explosive substances (CBRNE) was already directly affected by the pandemic in that the COVID-19 virus is, in a sense, a biological agent. This paper elaborates on how the field of CBRNE has changed as a result of the COVID-19 pandemic. It does so by drawing on the results of an interview study with CBRNE practitioners (Fire Brigades, Law Enforcement Agencies, etc.) conducted as part of the European Union project PReparedness against CBRNE threats through cOmmon Approaches between security praCTItioners and the VulnerablE civil society, as well as findings from research literature on links between CBRNE and COVID-19. This paper highlights four areas where the influence of the pandemic on the CBRNE field has been evident. The four areas are as follows: preparedness for CBRNE incidents and likelihood of future CBRNE incidents (with a focus on terrorist attacks), CBRNE training and education, increased awareness of CBRNE-related behaviors and measures among the general public, and greater awareness of the needs of vulnerable groups (older people, etc.).

Nursing is the largest health profession, with nearly 4 million providers practicing across acute, primary, and public health care settings. In response to the pandemic, nursing schools halted on-site course delivery and redesigned programs to attenuate risks to students and faculty. Key challenges faced by schools included financial cutbacks, rapid increases in online learning technology, maintaining student academic progression, disruption to clinical learning opportunities, and meeting accreditation standards, while addressing the stress and loss experienced by faculty, staff, and students. Despite challenges, nursing organizations provided guidance for decision making, new learning resources, and faculty development opportunities. Schools of nursing leveraged their resources to redesign nursing curricula, strengthen partnerships for student clinical experiences, and address needs of the community. Nursing education will look different from its prepandemic profile in the future. Lessons learned during the pandemic point to gaps in nursing education, particularly related to disaster and public health preparedness, health equity, and technology. The American Association of Colleges of Nursing's new Essentials-standards for professional nursing education-were finalized during the pandemic and reflect these lessons. The need for nurse scientists to conduct emergency response research was made evident. The importance of strong academic-practice partnerships was highlighted for rapid communication, flexibility, and responses to dynamic environments. For the future, nursing education and practice must collaborate to ensure that students and practicing nurses are prepared to address emergencies and pandemics, as well as the needs of vulnerable populations., Competing Interests: Other disclosures: The authors of this paper have no personal, professional, or monetary conflicts of interest to disclose., (Copyright © 2021 by the Association of American Medical Colleges.)

The novel coronavirus disease (COVID-19) pandemic has profoundly impacted the global economy and human health. The paper mainly proposed an improved susceptible-exposed-infected-recovered (SEIR) epidemic model with media coverage and limited medical resources to investigate the spread of COVID-19. We proved the positivity and boundedness of the solution. The existence and local asymptotically stability of equilibria were studied and a sufficient criterion was established for backward bifurcation. Further, we applied the proposed model to study the trend of COVID-19 in Shanghai, China, from March to April 2022. The results showed sensitivity analysis, bifurcation, and the effects of critical parameters in the COVID-19 model.

Background and Aims: The impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women, especially those with gestational diabetes mellitus (GDM), has yet to be fully understood. This review aims to examine the interaction between GDM and COVID-19 and to elucidate the pathophysiological mechanisms underlying the comorbidity of these two conditions., Methods: We performed a systematic literature search using the databases of PubMed, Embase, and Web of Science with appropriate keywords and MeSH terms. Our analysis included studies published up to January 26, 2023., Results: Despite distinct clinical manifestations, GDM and COVID-19 share common pathophysiological characteristics, which involve complex interactions across multiple organs and systems. On the one hand, infection with severe acute respiratory syndrome coronavirus 2 may target the pancreas and placenta, resulting in β-cell dysfunction and insulin resistance in pregnant women. On the other hand, the hormonal and inflammatory changes that occur during pregnancy could also increase the risk of severe COVID-19 in mothers with GDM. Personalized management and close monitoring are crucial for treating pregnant women with both GDM and COVID-19., Conclusions: A comprehensive understanding of the interactive mechanisms of GDM and COVID-19 would facilitate the initiation of more targeted preventive and therapeutic strategies. There is an urgent need to develop novel biomarkers and functional indicators for early identification and intervention of these conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Research Trust of DiabetesIndia (DiabetesIndia) and National Diabetes Obesity and Cholesterol Foundation (N-DOC). Published by Elsevier Ltd. All rights reserved.)

At the beginning of 2020, the world was faced with the challenge of the coronavirus disease 2019 (COVID-19) pandemic announced by the WHO on March 11, caused by the betacoronavirus type 2 of the severe acute respiratory syndrome (SARS-CoV-2), which had profound health, sociological and even economic consequences. The quickly implemented and large-scale research resulted in the introduction of widely available vaccines that reduced the further development of the pandemic and antivirals against SARS-CoV-2. Currently, 11 antiviral drugs (Tixagevimab/Cilgavimab, Regdanvimab, Casirivimab/Imdevimab, Sotrovimab, Nirmatrelvir/Ritonavir, Remdesivir, Molnupiravir, Baricitinib, Anakinra, Tocilizumab, Vilobelimab) have been approved or conditionally approved by the European Medicines Agency and/or by the Food and Drug Administration and are available on the pharmaceutical market. The progress in the pathophysiological description of the SARS-CoV-2 infection has allowed the identif i cation of potential targets for drugs against SARS-CoV-2: inhibitors of intracellular entry of the virus (the interaction between the viral spike (S) protein and the cellular angiotensin converting enzyme-2; ACE2 receptor), inhibitors of viral and cellular proteases, and immunomodulatory drugs (antagonists of pro-inf l ammatory cytokines or complement components). Novel agents against SARS-CoV-2 are also sought among the previously routinely used drugs as their repositioning and among plant-derived compounds. It is expected that ongoing research should result in the introduction of new drugs used in COVID-19 in the near future. The article brief l y describes the current epidemiological situation regarding COVID-19 and the currently used vaccines. Moreover, the paper outlines currently used and researched potential drugs in the pharmacotherapy of this disease.

The SARS-CoV-2 pandemic led to a huge increase in global pathogen genome sequencing efforts, and the resulting data are becoming increasingly important to detect variants of concern, monitor outbreaks, and quantify transmission dynamics. However, this rapid up-scaling in data generation brought with it many IT infrastructure challenges. In this paper, we report about developing an improved system for genomic epidemiology. We (i) highlight key challenges that were exacerbated by the pandemic situation, (ii) provide data infrastructure design principles to address them, and (iii) give an implementation example developed by the Swiss SARS-CoV-2 Sequencing Consortium (S3C) in response to the COVID-19 pandemic. Finally, we discuss remaining challenges to data infrastructure for genomic epidemiology. Improving these infrastructures will help better detect, monitor, and respond to future public health threats., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

We have come a long way since the start of the COVID-19 pandemic-from hoarding toilet paper and wiping down groceries to sending our children back to school and vaccinating billions. Over this period, the global community of epidemiologists and evolutionary biologists has also come a long way in understanding the complex and changing dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19. In this Review, we retrace our steps through the questions that this community faced as the pandemic unfolded. We focus on the key roles that mathematical modeling and quantitative analyses of empirical data have played in allowing us to address these questions and ultimately to better understand and control the pandemic.

Background: The hospitalization of children during the COVID-19 pandemic has affected their physical and mental health. Pediatric nurses have faced challenges in providing high-quality nursing care for children and their families. However, the pediatric nursing care recommendations for COVID-19 patients in the hospital setting remain unclear. The current scoping review provides recommendations for nursing interventions for pediatric COVID-19 patients in the hospital setting., Methods and Findings: The selected articles containing management and nursing recommendations for COVID-19 that have occurred in pediatric patients ages 0-19 years old. A search strategy was developed and implemented in seven databases. We included peer-reviewed articles that reported observational or interventional studies, as well as policy papers, guides or guidelines, letters and editorials, and web articles. A total of 134 articles and other documents relevant to this review were included. We categorized the results based on The Nursing Intervention Classification (NIC) taxonomy which consists of six domains (e.g., Physiological: Basic); eleven classes (e.g., Nutrition Support); and eighteen intervention themes (e.g., Positioning, Family Presence Facilitation, Family Support, and Discharge Planning)., Conclusion: Apart from the intervention of physical problems, there is a need to promote patient- and family-centered care, play therapy, and discharge planning to help children and families cope with their new situation., Competing Interests: The authors have declared that no competing interests exist.

Introduction: Neuropsychiatric symptoms are common in patients with mild cognitive impairment and dementia. This symptomatology can appear or be exacerbated with changes in routine and in the patient's usual environment. The lockdown situation during the COVID-19 pandemic has meant a drastic and unexpected change in the daily life of the general population, with a particular impact on the most physically and mentally vulnerable groups, including patients with cognitive impairment., Aim: To know the impact of lockdown measures imposed due to the COVID-19 pandemic on neuropsychiatric symptomatology in people with mild cognitive impairment and dementia., Materials and Methods: Exploratory systematic review, in accordance with the PRISMA guidelines, of Pubmed and Psycinfo databases papers published from January 2020 to April 2021 which related confinement due to COVID-19 with the presentation or worsening of neuropsychiatric symptoms in patients with mild cognitive impairment mild or dementia., Results: Worsening of neuropsychiatric symptoms was observed in patients with dementia and mild cognitive impairment, especially agitation/aggression, anxiety, depression and apathy. Neuropsychiatric symptoms were more common in patients with dementia than in those with mild cognitive impairment, although their typology varied depending on the severity of dementia., Conclusions: During lockdown a worsening in the psychobehavioral area has been observed in people with mild cognitive impairment or dementia. Therefore, considerations arise on the need of promoting social contact in people with mild cognitive impairment and dementia, avoiding situations of isolation and low stimulation.

The emergence and rapid global spread of the new Delta and, more recently, Omicron variants of SARS-CoV-2 pose a daunting public health emergency. Being an RNA virus, the Covid-19 virus is continuing to mutate, resulting in the emergence of new variants with high transmissibility, such as the recently discovered Omicron variant. In this paper, we consider the conditions that may facilitate viral mutations and the emergence of variants with the ability to evade immunity. Here, we have discussed the importance of vaccination with the currently available vaccines. These vaccines are highly effective at preventing serious disease, hospitalization, and death from Covid-19. However, the antibody response induced by these vaccines is short-lasting and there are reports of breakthrough infections. A stable and persistent interaction between T follicular helper cells and germinal center B cells is needed for robust B cell memory response. We discussed the potential reasons behind the breakthrough infections and underscored the importance of developing better second-generation vaccines that may not necessitate frequent booster immunizations and are preventive in nature. This may involve the development of multivalent vaccines and creating vaccines against other viral proteins including conserved proteins. Vaccine hesitancy remains a notable hurdle for implementing vaccination. Furthermore, we recommend different approaches to increase vaccine acceptance, which is a critical translational component of a successful vaccine strategy. These perspectives on overcoming the pandemic's current challenges provide strategies to contain SARS-CoV-2 globally., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The aim of this review was threefold: (a) to retrieve all SARS-CoV-2 evidences published by Italian neonatologists working in maternity centers and NICUs during the pandemic; (b) to summarize current evidence for the management of term and preterm infants with a SARS-CoV-2-related illness; and (c) to provide an update for dealing with the second wave of COVID-19 and discuss open questions. A review was conducted using MEDLINE/PubMed and the national COVID-19 registry of the Italian Society of Neonatology including citations from December 1, 2019 to October 28, 2020. Sixty-three articles were included. Collected data were divided into the following topics: (a) antenatal management, (b) management in delivery room, (c) postnatal management, (d) mother-baby dyad and breastfeeding management, (e) neonatal emergency transport system reorganization, (f) parents' management and perspective during SARS-CoV-2 pandemic, and (g) future perspective. Evidences have evolved over the pandemic period and the current review can be useful in the management of the mother-neonate dyad during SARS-CoV-2 future waves. Italian neonatologists have played an active role in producing official guidelines and reporting data that have contributed to improve the care of neonates. A joint European action plan is mandatory to face COVID-19 in neonates with more awareness. IMPACT: A joint European action plan is mandatory to face COVID-19 in neonates with more awareness. This review summarizes the available evidences from neonatal COVID-19 management in Italy analyzing all the published paper in this specific field of interest. The current review can be useful in the management of the mother-neonate dyad during the SARS-CoV-2 future waves., (© 2021. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

This study aimed to assess the current status of India's COVID-19 research from the top 100 most cited papers, using bibliometrics methods and indicators and suggest strengths and weaknesses. Publications on COVID-19 research from India between December 2019 and 22 August 2023 were retrieved from the Scopus database. From 37101 studies retrieved, the first top 100 Highly Cited Papers (HCPs) having received 270 to 2931 citations, were identified. The top 100 most cited Indian papers were published from 2020 to 2023, with the majority (75) in the year 2021, followed by 24 in 2022. They were cited a total of 56661 times (average - 566.61 times). The 242 authors of these HCPs were from 159 Indian organizations, and the articles were published in 60 journals. 29 % and 59 % of these HCPs received external funding support and were involved in international collaborations, respectively. There was poor collaboration among Indian research institutions and a dearth of funding from India. None of the Indian HCPs figured in the global 100 HCPs. Although citations of research papers published from India increased during COVID-19, limited collaboration, inadequate funding, and subpar publications hindered Indian scientists. To enhance India's research landscape, we propose dismantling barriers, nurturing collaboration, and encouraging knowledge exchange among domestic institutions. • A profile of the top 100 highly cited papers from Indian authors of COVID-19 research is presented. • There is limited global visibility and poor collaboration in Indian research. • Indian research and funding organizations need to increase funding and collaborations. [ABSTRACT FROM AUTHOR]

European countries struggled to fight against the second and the third waves of the COVID-19 pandemic, as the Test-Trace-Isolate (TTI) strategy widely adopted over the summer and early fall 2020 failed to contain the spread of the disease effectively. This paper sheds light on the effectiveness of such a strategy in two European countries (Spain and Italy) by analysing data from June to December 2020, collected via a large-scale online citizen survey with 95,251 and 43,393 answers in Spain and Italy, respectively. Our analysis describes several weaknesses in each of the three pillars of the TTI strategy: Test, Trace, and Isolate. We find that 40% of respondents had to wait more than 48 hours to obtain coronavirus tests results, while literature has shown that a delay of more than one day might make tracing all cases inefficient. We also identify limitations in the manual contact tracing capabilities in both countries, as only 29% of respondents in close contact with a confirmed infected individual reported having been contact traced. Moreover, our analysis shows that more than 45% of respondents report being unable to self-isolate if needed. We also analyse the mitigation strategies deployed to contain the second wave of coronavirus. We find that these interventions were particularly effective in Italy, where close contacts were reduced by more than 20% in the general population. Finally, we analyse the participants' perceptions about the coronavirus risk associated with different daily activities. We observe that they are often gender- and age-dependent, and not aligned with the actual risk identified by the literature. This finding emphasises the importance of deploying public-health communication campaigns to debunk misconceptions about SARS-CoV-2. Overall, our work illustrates the value of online citizen surveys to quickly and efficiently collect large-scale population data to support and evaluate policy decisions to combat the spread of infectious diseases, such as coronavirus., (© 2022. The Author(s).)

In the present paper, we aimed to determine the influence of various non-pharmaceutical interventions (NPIs) enforced during the first wave of COVID-19 across countries on the spreading rate of COVID-19 during the second wave. For this purpose, we took into account national-level climatic, environmental, clinical, health, economic, pollution, social, and demographic factors. We estimated the growth of the first and second wave across countries by fitting a logistic model to daily-reported case numbers, up to the first and second epidemic peaks. We estimated the basic and effective (second wave) reproduction numbers across countries. Next, we used a random forest algorithm to study the association between the growth rate of the second wave and NPIs as well as pre-existing country-specific characteristics. Lastly, we compared the growth rate of the first and second waves of COVID-19. The top three factors associated with the growth of the second wave were body mass index, the number of days that the government sets restrictions on requiring facial coverings outside the home at all times, and restrictions on gatherings of 10 people or less. Artificial intelligence techniques can help scholars as well as decision and policy-makers estimate the effectiveness of public health policies, and implement "smart" interventions, which are as efficacious as stringent ones., (© 2022. The Author(s).)

Fungal infections or mycosis cause a wide range of diseases in humans and animals. The incidences of community acquired; nosocomial fungal infections have increased dramatically after the emergence of COVID-19 pandemic. The increase in number of patients with immunodeficiency / immunosuppression related diseases, resistance to existing antifungal compounds and availability of limited therapeutic options has triggered the search for alternative antifungal molecules. In this direction, antifungal peptides (AFPs) have received a lot of interest as an alternative to currently available antifungal drugs. Although the AFPs are produced by diverse population of living organisms, identifying effective AFPs from natural sources is time-consuming and expensive. Therefore, there is a need to develop a robust in silico model capable of identifying novel AFPs in protein sequences. In this paper, we propose Deep-AFPpred, a deep learning classifier that can identify AFPs in protein sequences. We developed Deep-AFPpred using the concept of transfer learning with 1DCNN-BiLSTM deep learning algorithm. The findings reveal that Deep-AFPpred beats other state-of-the-art AFP classifiers by a wide margin and achieved approximately 96% and 94% precision on validation and test data, respectively. Based on the proposed approach, an online prediction server is created and made publicly available at https://afppred.anvil.app/. Using this server, one can identify novel AFPs in protein sequences and the results are provided as a report that includes predicted peptides, their physicochemical properties and motifs. By utilizing this model, we identified AFPs in different proteins, which can be chemically synthesized in lab and experimentally validated for their antifungal activity., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Coronavirus disease 2019 (COVID-19) has attracted research interests from all fields. Phylogenetic and social network analyses based on connectivity between either COVID-19 patients or geographic regions and similarity between syndrome coronavirus 2 (SARS-CoV-2) sequences provide unique angles to answer public health and pharmaco-biological questions such as relationships between various SARS-CoV-2 mutants, the transmission pathways in a community and the effectiveness of prevention policies. This paper serves as a systematic review of current phylogenetic and social network analyses with applications in COVID-19 research. Challenges in current phylogenetic network analysis on SARS-CoV-2 such as unreliable inferences, sampling bias and batch effects are discussed as well as potential solutions. Social network analysis combined with epidemiology models helps to identify key transmission characteristics and measure the effectiveness of prevention and control strategies. Finally, future new directions of network analysis motivated by COVID-19 data are summarized., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

A comprehensive analysis of omics data can require vast computational resources and access to varied data sources that must be integrated into complex, multi-step analysis pipelines. Execution of many such analyses can be accelerated by applying the cloud computing paradigm, which provides scalable resources for storing data of different types and parallelizing data analysis computations. Moreover, these resources can be reused for different multi-omics analysis scenarios. Traditionally, developers are required to manage a cloud platform's underlying infrastructure, configuration, maintenance and capacity planning. The serverless computing paradigm simplifies these operations by automatically allocating and maintaining both servers and virtual machines, as required for analysis tasks. This paradigm offers highly parallel execution and high scalability without manual management of the underlying infrastructure, freeing developers to focus on operational logic. This paper reviews serverless solutions in bioinformatics and evaluates their usage in omics data analysis and integration. We start by reviewing the application of the cloud computing model to a multi-omics data analysis and exposing some shortcomings of the early approaches. We then introduce the serverless computing paradigm and show its applicability for performing an integrative analysis of multiple omics data sources in the context of the COVID-19 pandemic., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Currently, the global report of COVID-19 cases is around 110 million, and more than 2.43 million related death cases as of February 18, 2021. Viruses continuously change through mutation; hence, different virus of SARS-CoV-2 has been reported globally. The United Kingdom (UK), South Africa, Brazil, and Nigeria are the countries from which these emerged variants have been notified and now spreading globally. Therefore, these countries have been selected as a research sample for the present study. The datasets analyzed in this study spanned from March 1, 2020, to January 31, 2021, and were obtained from the World Health Organization website. The study used the Autoregressive Integrated Moving Average (ARIMA) model to forecast coronavirus incidence in the UK, South Africa, Brazil, and Nigeria. ARIMA models with minimum Akaike Information Criterion Correction (AICc) and statistically significant parameters were chosen as the best models in this research. Accordingly, for the new confirmed cases, ARIMA (3,1,14), ARIMA (0,1,11), ARIMA (1,0,10), and ARIMA (1,1,14) models were chosen for the UK, South Africa, Brazil, and Nigeria, respectively. Also, the model specification for the confirmed death cases was ARIMA (3,0,4), ARIMA (0,1,4), ARIMA (1,0,7), and ARIMA (Brown); models were selected for the UK, South Africa, Brazil, and Nigeria, respectively. The results of the ARIMA model forecasting showed that if the required measures are not taken by the respective governments and health practitioners in the days to come, the magnitude of the coronavirus pandemic is expected to increase in the study's selected countries., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Cai Li et al.)

Dietary adequacy and diversity during the lactation period are necessary to ensure good health and nutrition among women and children. Behavioral interventions pertaining to health and nutrition counselling during pregnancy and lactation are critical for awareness about dietary diversity. The issue assumes salience for marginalized communities because of the Covid-19 pandemic and associated economic and societal disruptions. This paper assesses the dietary patterns among 400 lactating mothers in the tribal-dominated district of Palghar in Maharashtra, India in 2020. The study is based on primary data regarding consumption of 10 food groups among women across 10 food groups based on 24-hour recall period. The primary outcome variable was binary information regarding Minimum Dietary Diversity defined as consumption from at least 5 food groups. Econometric analysis based on multilevel models and item-response theory is applied to identify food groups that were most difficult to be received by mothers during the early and late lactation period. We find that the daily diet of lactating mothers in Palghar primarily consists of grains, white roots, tubers, and pulses. In contrast, the intake of dairy, eggs, and non-vegetarian food items is much lower. Only Half of the lactating women (56.5 percent; 95% CI: 37.4; 73.8) have a minimum diversified diet (MDD). The prevalence of lactating women with MDD was higher among households with higher income (73.1 percent; 95% CI: 45.2; 89.9) than those in lower income group (50.7 percent; 95% CI: 42.3; 58.9). Lactating Women (in early phase) who received health and nutrition counseling services are more likely (OR: 2.37; 95% CI: 0.90; 6.26) to consume a diversified diet. Food groups such as fruits, meat, poultry, fish, nuts, and seeds were among the rare food items in daily diet. The dietary pattern lacking in fruits, nuts, and heme (iron) sources indicates more significant risks of micronutrient deficiencies. The findings call for improving dietary diversity among lactating mothers, particularly from the marginalized communities, and are driven by low consumption of dairy products or various fruits and vegetables. Among the different food items, the consumption of micronutrient-rich seeds and nuts is most difficult to be accessed by lactating mothers. Also, diet-centric counseling and informing lactating mothers of its benefits are necessary to increase dietary diversity for improving maternal and child nutrition., Competing Interests: No Author have competing interests.

The significant morbidity and mortality of coronavirus disease 19 (COVID-19) prompted a global race to develop new therapies. These include interventions using cell- or cell-derived products, several of which are being tested in well-designed, properly controlled clinical trials. Yet, the search for cell-based COVID-19 treatments has also been fraught with hyperbolic claims; flouting of crucial regulatory, scientific, and ethical norms; and distorted communication of research findings. In this paper, we critically examine ethical issues and public communication challenges related to the development of cell-based therapeutics for COVID-19. Drawing on the lessons learned from this ongoing process, we argue against the rushed development of cell-based interventions. We conclude by outlining ways to improve the ethical conduct of cell-based clinical investigations and public communication of therapeutic claims., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Policy changes are often necessary to contain the detrimental impact of epidemics such as those brought about by coronavirus disease (COVID-19). In the earlier phases of the emergence of COVID-19, China was the first to impose strict restrictions on movement (lockdown) on January 23rd, 2020. A strategy whose effectiveness in curtailing COVID-19 was yet to be determined. We, therefore, sought to study the impact of the lockdown in reducing the incidence of COVID-19., Methods: Daily cases of COVID-19 that occurred in China which were registered between January 12th and March 30th, 2020, were extracted from the Johns Hopkins CSSE team COVID-19 ArcGIS® dashboards. Daily cases reported were used as data points in the series. Two interrupted series models were run: one with an interruption point of 23 January 2020 (model 1) and the other with a 14-day deferred interruption point of 6th February (model 2). For both models, the magnitude of change (before and after) and linear trend analyses were measured, and β -coefficients reported with 95% confidence interval (CI) for the precision., Results: Seventy-eight data points were used in the analysis. There was an 11% versus a 163% increase in daily cases in models 1 and 2, respectively, in the preintervention periods ( p ≤ 0.001). Comparing the period immediately following the intervention points to the counterfactual, there was a daily increase of 2,746% ( p < 0.001) versus a decline of 207% ( p = 0.802) in model 2. However, in both scenarios, there was a statistically significant drop in the daily cases predicted for this data and beyond when comparing the preintervention periods and postintervention periods ( p < 0.001)., Conclusion: There was a significant decrease the COVID-19 daily cases reported in China following the institution of a lockdown, and therefore, lockdown may be used to curtail the burden of COVID-19., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Mooketsi Molefi et al.)

Stay-at-home orders and shutdowns of non-essential businesses are powerful, but socially costly, tools to control the pandemic spread of SARS-CoV-2. Mass testing strategies, which rely on widely administered frequent and rapid diagnostics to identify and isolate infected individuals, could be a potentially less disruptive management strategy, particularly where vaccine access is limited. In this paper, we assess the extent to which mass testing and isolation strategies can reduce reliance on socially costly non-pharmaceutical interventions, such as distancing and shutdowns. We develop a multi-compartmental model of SARS-CoV-2 transmission incorporating both preventative non-pharmaceutical interventions (NPIs) and testing and isolation to evaluate their combined effect on public health outcomes. Our model is designed to be a policy-guiding tool that captures important realities of the testing system, including constraints on test administration and non-random testing allocation. We show how strategic changes in the characteristics of the testing system, including test administration, test delays, and test sensitivity, can reduce reliance on preventative NPIs without compromising public health outcomes in the future. The lowest NPI levels are possible only when many tests are administered and test delays are short, given limited immunity in the population. Reducing reliance on NPIs is highly dependent on the ability of a testing program to identify and isolate unreported, asymptomatic infections. Changes in NPIs, including the intensity of lockdowns and stay at home orders, should be coordinated with increases in testing to ensure epidemic control; otherwise small additional lifting of these NPIs can lead to dramatic increases in infections, hospitalizations and deaths. Importantly, our results can be used to guide ramp-up of testing capacity in outbreak settings, allow for the flexible design of combined interventions based on social context, and inform future cost-benefit analyses to identify efficient pandemic management strategies., Competing Interests: The authors have declared that no competing interests exist.

An operationally implementable predictive model has been developed to forecast the number of COVID-19 infections in the patient population, hospital floor and ICU censuses, ventilator and related supply chain demand. The model is intended for clinical, operational, financial and supply chain leaders and executives of a comprehensive healthcare system responsible for making decisions that depend on epidemiological contingencies. This paper describes the model that was implemented at NorthShore University HealthSystem and is applicable to any communicable disease whose risk of reinfection for the duration of the pandemic is negligible., Competing Interests: The authors have declared that no competing interests exist.

Understanding and monitoring the epidemiological time delay dynamics of SARS-CoV-2 infection provides insights that are key to discerning changes in the phenotype of the virus, the demographics impacted, the efficacy of treatment, and the ability of the health service to manage large volumes of patients. This paper analyses how the pandemic has evolved in the United Kingdom through the temporal changes to the epidemiological time delay distributions for clinical outcomes. Using the most complete clinical data presently available, we have analysed, through a doubly interval censored Bayesian modelling approach, the time from infection to a clinical outcome. Across the pandemic, for the periods that were defined as epidemiologically distinct, the modelled mean ranges from 8.0 to 9.7 days for infection to hospitalisation, 10.3 to 15.0 days for hospitalisation to death, and 17.4 to 24.7 days for infection to death. The time delay from infection to hospitalisation has increased since the first wave of the pandemic. A marked decrease was observed in the time from hospitalisation to death and infection to death at times of high incidence when hospitals and ICUs were under the most pressure. There is a clear relationship between age groups that is indicative of the youngest and oldest demographics having the shortest time delay distributions before a clinical outcome. A statistically significant difference was found between genders for the time delay from infection to hospitalisation, which was not found for hospitalisation to death. The results by age group indicate that younger demographics that require clinical intervention for SARS-CoV-2 infection are more likely to require earlier hospitalisation that leads to a shorter time to death, which is suggestive of the largely more vulnerable nature of these individuals that succumb to infection. The distinction found between genders for exposure to hospitalisation is revealing of gender healthcare seeking behaviours., Competing Interests: The authors have declared that no competing interests exist. The authors were employed by the Department of Health and Social Care but received no specific funding for this study.

Examining the spread of macroeconomic phenomena between countries has become increasingly popular after the 2008 economic crisis, but the recent COVID-19 pandemic rendered this issue much more relevant as it shed more light on the risks arising from strongly interconnected economies. This paper intends to extend previous studies in this line by examining the relationship between trade openness and business cycle synchronization. It extends the scope of previous analyses in three areas. First, we use a Granger-causality approach to identify synchronization. Second, trade is broken down to the sector level and third, we distinguish between upstream and downstream connections. These developments allow for a directed approach in the analysis. We use conditional logit regressions to estimate the effect of trade openness on the probability of shock-transmission. The results presented in this study contribute to the literature in two ways. First, in addition to revealing a positive effect of aggregate two-way trade on shock-contagion, it also points out that this overall effect hides diverse behavior in specific trading sectors as well as upstream and downstream channels. Second, while some sectors are not significant channels of shock-transmission in either directions, upstream channels seem to be important in agriculture while downstream channels dominate machinery and other manufactures. Also, there are sectors (chemicals and related products) trade in which affects shock-transmission negatively., Competing Interests: The authors have declared that no competing interests exist.

In this study we propose a Coronavirus Disease 2019 (COVID-19) mathematical model that stratifies infectious subpopulations into: infectious asymptomatic individuals, symptomatic infectious individuals who manifest mild symptoms and symptomatic individuals with severe symptoms. In light of the recent revelation that reinfection by COVID-19 is possible, the proposed model attempt to investigate how reinfection with COVID-19 will alter the future dynamics of the recent unfolding pandemic. Fitting the mathematical model on the Kenya COVID-19 dataset, model parameter values were obtained and used to conduct numerical simulations. Numerical results suggest that reinfection of recovered individuals who have lost their protective immunity will create a large pool of asymptomatic infectious individuals which will ultimately increase symptomatic individuals with mild symptoms and symptomatic individuals with severe symptoms (critically ill) needing urgent medical attention. The model suggests that reinfection with COVID-19 will lead to an increase in cumulative reported deaths. Comparison of the impact of non pharmaceutical interventions on curbing COVID19 proliferation suggests that wearing face masks profoundly reduce COVID-19 prevalence than maintaining social/physical distance. Further, numerical findings reveal that increasing detection rate of asymptomatic cases via contact tracing, testing and isolating them can drastically reduce COVID-19 surge, in particular individuals who are critically ill and require admission into intensive care., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2021 Isaac Mwangi Wangari et al.)

The emergence of a new acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), the cause of the 2019-nCOV disease (COVID-19), has caused a pandemic and a global health crisis. Rapid human-to-human transmission, even from asymptomatic individuals, has led to the quick spread of the virus worldwide, causing a wide range of clinical manifestations from cold-like symptoms to severe pneumonia, acute respiratory distress syndrome (ARDS), multiorgan injury, and even death. Therefore, using rapid and accurate diagnostic methods to identify the virus and subsequently select appropriate and effective treatments can help improvement of patients and control the pandemic. So far, various treatment regimens along with prophylactic vaccines have been developed to manage COVID-19-infected patients. Among these, antibody-based therapies, including neutralizing antibodies (against different parts of the virus), polyclonal and monoclonal antibodies, plasma therapy, and high-dose intravenous immunoglobulin (IVIG) have shown promising outcomes in accelerating and improving the treatment process of patients, avoiding the viral spreading widely, and managing the pandemic. In the current review paper, different types and applications of therapeutic antibodies in the COVID-19 treatment are comprehensively discussed., (© 2021 Wiley Periodicals LLC.)

Psoriasis is a chronic inflammatory skin disease that is characterized by well-demarcated erythematous plaques with a silver scale. Although many new and emerging therapeutic agents are often sufficient to control the disease, there is still a need for alternative treatment options in challenging cases. Extracorporeal photopheresis (ECP) has been applied to many T-cell-mediated diseases to restore immune homeostasis and treat psoriasis effectively. In this paper, we present a psoriasis patient who did not respond to methotrexate, narrowband ultraviolet B, or acitretin. Because of a diagnosis of non-Hodgkin lymphoma, the patient had contraindications for cyclosporine, fumaric acid esters, and biologics but achieved remission with a total of 12 sessions of ECP in two and a half months. Although exacerbation was recorded after polymerase chain reaction (PCR) confirmed coronavirus 2019 (COVID-19) disease infection at the end of the first month, scores from the psoriasis area severity index (PASI) and dermatological life quality index (DLQI) were regressed significantly within two and a half months. ECP seems to provide an effective and rapid response for psoriasis and should be considered for psoriasis patients who fail to respond or have contraindications to existing treatments., (Copyright © 2021. Published by Elsevier Ltd.)

In an effort to establish a consensus position on the ethical principles and ideals that should guide vaccine allocation during the Covid-19 pandemic, various organizations, including the Centers for Disease Control (CDC) and National Academies of Science, Engineering, and Medicine, released sample allocation frameworks to help guide government entities charged with distributing vaccine doses. One area of agreement among these reports is that front line health care workers, especially those who come into regular contact with Covid-19 patients, ought to be afforded highest priority. But this convergence, though significant, raises questions concerning the ethics of vaccine distribution among those highest-priority health care workers: If a hospital has inadequate supply to vaccinate its entire workforce, which of its essential workers should it prioritize? In this paper, we begin with a general overview of ethical questions of vaccine administration before narrowing our focus to some of the most pressing theoretical and practical issues hospital officials must face in building justifiable and actionable frameworks for vaccinating their workers. We discuss and assess some potential ambitions of hospital allocation plans, concentrating especially on the goal of protecting the community from catastrophic loss of life. Finally, we consider some specific questions hospitals will encounter when developing distribution guidelines that aim to realize this aspiration.

Background: Severe coronavirus disease-2019 (COVID-19) can progress to an acute respiratory distress syndrome (ARDS), which involves alveolar infiltration by activated neutrophils. The beta-blocker metoprolol has been shown to ameliorate exacerbated inflammation in the myocardial infarction setting., Objectives: The purpose of this study was to evaluate the effects of metoprolol on alveolar inflammation and on respiratory function in patients with COVID-19-associated ARDS., Methods: A total of 20 COVID-19 patients with ARDS on invasive mechanical ventilation were randomized to metoprolol (15 mg daily for 3 days) or control (no treatment). All patients underwent bronchoalveolar lavage (BAL) before and after metoprolol/control. The safety of metoprolol administration was evaluated by invasive hemodynamic and electrocardiogram monitoring and echocardiography., Results: Metoprolol administration was without side effects. At baseline, neutrophil content in BAL did not differ between groups. Conversely, patients randomized to metoprolol had significantly fewer neutrophils in BAL on day 4 (median: 14.3 neutrophils/µl [Q1, Q3: 4.63, 265 neutrophils/µl] vs median: 397 neutrophils/µl [Q1, Q3: 222, 1,346 neutrophils/µl] in the metoprolol and control groups, respectively; P = 0.016). Metoprolol also reduced neutrophil extracellular traps content and other markers of lung inflammation. Oxygenation (PaO 2 :FiO 2 ) significantly improved after 3 days of metoprolol treatment (median: 130 [Q1, Q3: 110, 162] vs median: 267 [Q1, Q3: 199, 298] at baseline and day 4, respectively; P = 0.003), whereas it remained unchanged in control subjects. Metoprolol-treated patients spent fewer days on invasive mechanical ventilation than those in the control group (15.5 ± 7.6 vs 21.9 ± 12.6 days; P = 0.17)., Conclusions: In this pilot trial, intravenous metoprolol administration to patients with COVID-19-associated ARDS was safe, reduced exacerbated lung inflammation, and improved oxygenation. Repurposing metoprolol for COVID-19-associated ARDS appears to be a safe and inexpensive strategy that can alleviate the burden of the COVID-19 pandemic., Competing Interests: Funding Support and Author Disclosures Mr Clemente-Moragón is supported by a fellowship from the Ministerio de Ciencia e Innovación (FPU2017/01932). The CNIC is supported by the ISCIII, the Ministerio de Ciencia e Innovación, and the Pro CNIC Foundation. Dr Ibáñez is supported by the European Commission (ERC-CoG grant No 819775) and by the Spanish Ministry of Science and Innovation (MCN; “RETOS 2019” grant No PID2019-107332RB-I00). Dr Oliver is supported by funds from the Comunidad de Madrid Programa de Atracción de Talento (2017-T1/BMD-5185). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

This paper quantifies the net impact (direct and indirect effects) of the pandemic on the United States population in 2020 using three metrics: excess deaths, life expectancy, and total years of life lost. The findings indicate there were 375,235 excess deaths, with 83% attributable to direct, and 17% attributable to indirect effects of COVID-19. The decrease in life expectancy was 1.67 years, translating to a reversion of 14 years in historical life expectancy gains. Total years of life lost in 2020 was 7,362,555 across the USA (73% directly attributable, 27% indirectly attributable to COVID-19), with considerable heterogeneity at the individual state level., Competing Interests: The authors have declared that no competing interests exist.

The coronavirus disease 2019 (COVID-19) pandemic threatens human species with mortality rate of roughly 2%. We can hardly predict the time of herd immunity against and end of COVID-19 with or without success of vaccine. One way to overcome the situation is to define what delineates disease severity and serves as a molecular target. The most successful analogy is found in BCR-ABL in chronic myeloid leukemia, which is the golden biomarker, and simultaneously, the most effective molecular target. We hypothesize that S100 calcium-binding protein A8 (S100A8) is one such molecule. The underlying evidence includes accumulating clinical information that S100A8 is upregulated in severe forms of COVID-19, pathological similarities of the affected lungs between COVID-19 and S100A8-induced acute respiratory distress syndrome (ARDS) model, homeostatic inflammation theory in which S100A8 is an endogenous ligand for endotoxin sensor Toll-like receptor 4/Myeloid differentiation protein-2 (TLR4/MD-2) and mediates hyper-inflammation even after elimination of endotoxin-producing extrinsic pathogens, analogous findings between COVID-19-associated ARDS and pre-metastatic lungs such as S100A8 upregulation, pulmonary recruitment of myeloid cells, increased vascular permeability, and activation coagulation cascade. A successful treatment in an animal COVID-19 model is given with a reagent capable of abrogating interaction between S100A8/S100A9 and TLR4. In this paper, we try to verify our hypothesis that S100A8 governs COVID-19-associated ARDS., (© 2021 The Authors. The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology.)

Abstract: Full attention must be given to the follow-up of patients recovered from Coronavirus disease 2019, which developed in Wuhan, China in December 2019. Among the most serious issues since the emergence of the Severe Acute Respiratory Syndrome Coronavirus 2 has been whether those who had it can experience a second episode of infection and what that implies for immunity. The earlier studies on COVID-19 disease focused primarily on the epidemiological, clinical, and radiological characteristics of patients with CO-VID-19. However, conclusions of these studies still require to be warranted by more careful design, larger sample size and statistically well structured studies. COVID-19 is an under-studied infection, and several aspects of viral transmission and clinical progress remain at present unclear. There is a concern about the persistence of SARS-CoV-2 on various surfaces and in the respiratory system of patients who have survi-ved. One of the most concerning issues since the emergence of the SARS-CoV-2 is persistence in patients and whether patients can be re-infected. After hospital discharge, recovered patients were reported to have positive SARS-CoV-2 test in China, Japan, and South Korea. In addition to the persistence of the virus, SARS-CoV-2 re-infection may occur in survivors. In this paper, we focused on the evidence of persistence and re-infection of SARS-CoV-2.

Abstract: After SARS-CoV-2 vaccines development came at an unprecedented speed, ensuring safe and efficient mass immunization, vaccine delivery be-came the major public health mandate. Although mass-vaccination sites have been identified as essential to curb COVID-19, their organization and functioning is challenging. In this paper we present the planning, implementation and evalua-tion of a massive vaccination center in Lombardy - the largest Region in Italy and the most heavily hit by the pandemic. The massive hub of Novegro (Milan), managed by the Gruppo Ospedaliero San Donato, opened in April 2021. The Novegro mass-immunization model was developed building a la-yout based on the available scientific evidence, on comparative analysis with other existing models and on the experience of COVID-19 immunization delivery of Gruppo Ospedaliero San Donato. We propose a "vaccine islands" mass-immunization model, where 4 physicians and 2 nurses operate in each island, with up to 10 islands functioning at the same time, with the capacity of providing up to 6,000 vaccinations per day. During the first week of activity a total of 37,900 doses were administered (2,700/day), most of them with Pfizer vaccine (85.8%) and first doses (70.9%). The productivity was 10.5 vaccines/hour/vaccine station. Quality, efficiency and safety were boosted by ad-hoc personnel training, quality technical infrastructure and the presence of a shock room. Constant process monitoring allowed to identify and promptly tackle process pitfalls, including vaccine refusals (0.36%, below expectations) and post-vaccinations adverse reactions (0.4%). Our innovative "vaccine islands" mass-immunization model might be scaled-up or adapted to other settings. The Authors consider that sharing best practices in immunization delivery is fundamen-tal to achieve population health during health emergencies.

The COVID-19 pandemic is a huge challenge to education systems. Most governments around the world have temporarily closed schools, universities, and colleges. At the same time, teachers and students are encouraged to use the online and distance learning programs and platforms as an alternative. In the present study, we proposed a series of innovative solutions in Medical Molecular Biology education during the COVID-19 pandemic in China, including a flipped classroom model, live streaming course, chat Apps, and scientific papers on COVID-19 as additional learning material. Our results demonstrated that these innovations not only help teachers to maintain the teaching process as usual but also be useful for protecting students from psychological trauma. Our study indicates that online education with a well-designed workflow for conducting provides an alternative approach for teachers to maintain quality education during the onset of the emerging crisis., (© 2021 International Union of Biochemistry and Molecular Biology.)

While there has been much speculation on how the pandemic has affected work location patterns and home location choices, there is sparse evidence regarding the impacts that COVID-19 has had on amenity visits in American cities, which typically constitute over half of all urban trips. Using aggregate app-based GPS positioning data from smartphone users, this study traces the changes in amenity visits in Somerville, MA from January 2019 to December 2020, describing how visits to particular types of amenities have changed as a result of business closures during the public health emergency. Has the pandemic fundamentally shifted amenity-oriented travel behavior or is consumer behavior returning to pre-pandemic trends? To address this question, we calibrate discrete choice models that are suited to Census block-group level analysis for each of the 24 months in a two-year period, and use them to analyze how visitors' behavioral responses to various attributes of amenity clusters have shifted during different phases of the pandemic. Our findings suggest that in the first few months of the pandemic, amenity-visiting preferences significantly diverged from expected patterns. Even though overall trip volumes remained far below normal levels throughout the remainder of the year, preferences towards specific cluster attributes mostly returned to expected levels by September 2020. We also construct two scenarios to explore the implications of another shutdown and a full reopening, based on November 2020 consumer behavior. While government restrictions have played an important role in reducing visits to amenity clusters, our results imply that cautionary consumer behavior has played an important role as well, suggesting a likely long and slow path to economic recovery. By drawing on mobile phone location data and behavioral modeling, this paper offers timely insights to help decision-makers understand how this unprecedented health emergency is affecting amenity-related trips and where the greatest needs for intervention and support may exist., Competing Interests: The authors have declared that no competing interests exist.

The Coronavirus Disease 2019 (COVID-19) is the first known pandemic caused by a coronavirus. Its causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appears to be capable of infecting different mammalian species. Recent detections of this virus in pet, zoo, wild, and farm animals have compelled inquiry regarding the zoonotic (animal-to-human) and reverse zoonotic (human-to-animal) transmissibility of SARS-CoV-2 with the potential of COVID-19 pandemic evolving into a panzootic. It is important to monitor the global spread of disease and to assess the significance of genomic changes to support prevention and control efforts during a pandemic. An understanding of the SARS-CoV-2 epidemiology provides opportunities to prevent the risk of repeated re-infection of humans and requires a robust One Health-based investigation. This review paper describes the known properties and the existing gaps in scientific knowledge about the zoonotic and reverse zoonotic transmissibility of the novel virus SARS-CoV-2 and the COVID-19 disease it causes., (Copyright © 2021. Published by Elsevier B.V.)

Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events such as natural disasters, political unrest, and terrorism. The COVID-19 pandemic is a catastrophic event that has raised a number of psychological issues such as depression given abrupt social changes and lack of employment. Advancements of deep learning-based language models have been promising for sentiment analysis with data from social networks such as Twitter. Given the situation with COVID-19 pandemic, different countries had different peaks where rise and fall of new cases affected lock-downs which directly affected the economy and employment. During the rise of COVID-19 cases with stricter lock-downs, people have been expressing their sentiments in social media. This can provide a deep understanding of human psychology during catastrophic events. In this paper, we present a framework that employs deep learning-based language models via long short-term memory (LSTM) recurrent neural networks for sentiment analysis during the rise of novel COVID-19 cases in India. The framework features LSTM language model with a global vector embedding and state-of-art BERT language model. We review the sentiments expressed for selective months in 2020 which covers the major peak of novel cases in India. Our framework utilises multi-label sentiment classification where more than one sentiment can be expressed at once. Our results indicate that the majority of the tweets have been positive with high levels of optimism during the rise of the novel COVID-19 cases and the number of tweets significantly lowered towards the peak. We find that the optimistic, annoyed and joking tweets mostly dominate the monthly tweets with much lower portion of negative sentiments. The predictions generally indicate that although the majority have been optimistic, a significant group of population has been annoyed towards the way the pandemic was handled by the authorities., Competing Interests: The authors have declared that no competing interests exist.