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The pandemic of coronavirus disease (COVID)-19 is a global threat, causing high mortality, especially in the elderly. The main symptoms and the primary cause of death are related to interstitial pneumonia. Viral entry also into myocardial cells mainly via the angiotensin converting enzyme type 2 (ACE2) receptor and excessive production of pro-inflammatory cytokines, however, also make the heart susceptible to injury. In addition to the immediate damage caused by the acute inflammatory response, the heart may also suffer from long-term consequences of COVID-19, potentially causing a post-pandemic increase in cardiac complications. Although the main cause of cardiac damage in COVID-19 remains coagulopathy with micro- (and to a lesser extent macro-) vascular occlusion, open questions remain about other possible modalities of cardiac dysfunction, such as direct infection of myocardial cells, effects of cytokines storm, and mechanisms related to enhanced coagulopathy. In this opinion paper, we focus on these lesser appreciated possibilities and propose experimental approaches that could provide a more comprehensive understanding of the cellular and molecular bases of cardiac injury in COVID-19 patients. We first discuss approaches to characterize cardiac damage caused by possible direct viral infection of cardiac cells, followed by formulating hypotheses on how to reproduce and investigate the hyperinflammatory and pro-thrombotic conditions observed in the heart of COVID-19 patients using experimental in vitro systems. Finally, we elaborate on strategies to discover novel pathology biomarkers using omics platforms. [ABSTRACT FROM AUTHOR]

Background The National Institutes of Health (NIH) mobilized more than $4 billion in extramural funding for the COVID-19 pandemic. Assessing the research output from this effort is crucial to understanding how the scientific community leveraged federal funding and responded to this public health crisis. Methods NIH-funded COVID-19 grants awarded between January 2020 and December 2021 were identified from NIH Research Portfolio Online Reporting Tools Expenditures and Results using the "COVID-19 Response" filter. PubMed identifications of publications under these grants were collected and the NIH iCite tool was used to determine citation counts and focus (eg, clinical, animal). iCite and the NIH's LitCOVID database were used to identify publications directly related to COVID-19. Publication titles and Medical Subject Heading terms were used as inputs to a machine learning–based model built to identify common topics/themes within the publications. Results and Conclusions We evaluated 2401 grants that resulted in 14 654 publications. The majority of these papers were published in peer-reviewed journals, though 483 were published to preprint servers. In total, 2764 (19%) papers were directly related to COVID-19 and generated 252 029 citations. These papers were mostly clinically focused (62%), followed by cell/molecular (32%), and animal focused (6%). Roughly 60% of preprint publications were cell/molecular-focused, compared with 26% of nonpreprint publications. The machine learning–based model identified the top 3 research topics to be clinical trials and outcomes research (8.5% of papers), coronavirus-related heart and lung damage (7.3%), and COVID-19 transmission/epidemiology (7.2%). This study provides key insights regarding how researchers leveraged federal funding to study the COVID-19 pandemic during its initial phase. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is an unprecedented healthcare emergency causing mortality and illness across the world. Although primarily affecting the lungs, the SARS-CoV-2 virus also affects the cardiovascular system. In addition to cardiac effects, e.g. myocarditis, arrhythmias, and myocardial damage, the vasculature is affected in COVID-19, both directly by the SARS-CoV-2 virus, and indirectly as a result of a systemic inflammatory cytokine storm. This includes the role of the vascular endothelium in the recruitment of inflammatory leucocytes where they contribute to tissue damage and cytokine release, which are key drivers of acute respiratory distress syndrome (ARDS), in disseminated intravascular coagulation, and cardiovascular complications in COVID-19. There is also evidence linking endothelial cells (ECs) to SARS-CoV-2 infection including: (i) the expression and function of its receptor angiotensin-converting enzyme 2 (ACE2) in the vasculature; (ii) the prevalence of a Kawasaki disease-like syndrome (vasculitis) in COVID-19; and (iii) evidence of EC infection with SARS-CoV-2 in patients with fatal COVID-19. Here, the Working Group on Atherosclerosis and Vascular Biology together with the Council of Basic Cardiovascular Science of the European Society of Cardiology provide a Position Statement on the importance of the endothelium in the underlying pathophysiology behind the clinical presentation in COVID-19 and identify key questions for future research to address. We propose that endothelial biomarkers and tests of function (e.g. flow-mediated dilatation) should be evaluated for their usefulness in the risk stratification of COVID-19 patients. A better understanding of the effects of SARS-CoV-2 on endothelial biology in both the micro- and macrovasculature is required, and endothelial function testing should be considered in the follow-up of convalescent COVID-19 patients for early detection of long-term cardiovascular complications. [ABSTRACT FROM AUTHOR]

We are witnessing an unparalleled pandemic caused by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) associated with coronavirus disease 2019 (COVID-19). Current data show that SARS-CoV-2 results in mild flu-like symptoms in the majority of healthy and young patients affected. Nevertheless, the severity of COVID-19 respiratory syndrome and the risk of adverse or catastrophic outcomes are increased in patients with pre-existing cardiovascular disease. Patients with adult congenital heart disease (ACHD)—by definition—have underlying cardiovascular disease. Many patients with ACHD are also afflicted with residual haemodynamic lesions such as valve dysfunction, diminished ventricular function, arrhythmias or cyanosis, have extracardiac comorbidities, and face additional challenges regarding pregnancy. Currently, there are emerging data of the effect of COVID-19 on ACHD patients, but many aspects, especially risk stratification and treatment considerations, remain unclear. In this article, we aim to discuss the broad impact of COVID-19 on ACHD patients, focusing specifically on pathophysiology, risk stratification for work, self-isolation, hospitalization, impact on pregnancy, psychosocial health, and longer-term implications for the provision of ACHD care. [ABSTRACT FROM AUTHOR]

Background COVID-19 is the most rapidly expanding coronavirus outbreak in the past 2 decades. To provide a swift response to a novel outbreak, prior knowledge from similar outbreaks is essential. Results Here, we study the volume of research conducted on previous coronavirus outbreaks, specifically SARS and MERS, relative to other infectious diseases by analyzing >35 million articles from the past 20 years. Our results demonstrate that previous coronavirus outbreaks have been understudied compared with other viruses. We also show that the research volume of emerging infectious diseases is very high after an outbreak and decreases drastically upon the containment of the disease. This can yield inadequate research and limited investment in gaining a full understanding of novel coronavirus management and prevention. Conclusions Independent of the outcome of the current COVID-19 outbreak, we believe that measures should be taken to encourage sustained research in the field. [ABSTRACT FROM AUTHOR]

Summary: The occurrence of antineutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV) has been reported since the coronavirus disease 2019 (COVID-19) vaccination, but whether there is a causal relationship or coincidence remains to be verified. We combined the term COVID-19 vaccination with each word of AAV to search for case reports and case series published in PubMed, EMBASE, and Web of Science databases before 13 March 2023. A total of 56 patients who developed AAV after COVID-19 vaccination were identified from 44 research centers. Of the 56 subjects, 43 (76.7%) were vaccinated with the mRNA vaccine, followed by the adenovirus vaccine (14.3%) and inactivated vaccine (9.0%) (P = 0.015). Compared with relapsed AAV, new-onset AAV patients had at least two other diseases previously (P < 0.001). Twenty-five (44.6%) patients presented symptoms after the first injection, and the medium onset time was 12 (1–77) days, while Twenty-eight (50.0%) patients developed symptoms after the second dose, and their medium period was 14 (1–60) days. Forty-four (78.5%) patients achieved remission after immunosuppressive agents, plasma exchange, and hemodialysis. One (1.8%) patient died from progressive respiratory failure and nine (16.1%) did not recover, leaving five patients permanently dependent on hemodialysis. Pathogenic ANCA may be activated by enhanced immune response and epitope spreading after COVID-19 vaccination and induced the occurrence of AAV, especially in genetically susceptible populations. The occurrence of antineutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV) has been reported since the coronavirus disease 2019 (COVID-19) vaccination, but whether there is a causal relationship or coincidence remains to be verified. This paper explores the occurrence of AAV, especially in genetically susceptible populations. [ABSTRACT FROM AUTHOR]

Background Early reports on the pandemic nature of coronavirus disease 2019 (COVID-19) directed the nephrology community to develop infection prevention and control (IPC) guidance. We aimed to make an inventory of strategies that dialysis centres followed to prevent infection with COVID-19 in the first pandemic wave. Methods We analyzed IPC measures taken by hemodialysis centres treating patients presenting with COVID-19 between 1 March 2020 and 31 July 2020 and that completed the European Renal Association COVID-19 Database centre questionnaire. Additionally, we made an inventory of guidelines published in European countries to prevent spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in dialysis centres. Results Data from 73 dialysis units located in and bordering Europe were analyzed. All participating centres implemented IPC measures to mitigate the impact of SARS-CoV-2 during the first pandemic wave. Measures mentioned most often included triage with questions before entering the dialysis ward, measuring body temperature, hand disinfection, masking for all patients and staff, and personal protective equipment for staff members. These measures were also recommended in most of the 14 guidelines that were identified in the inventory of national guidelines and were also scored as being among the most important measures by the authors of this paper. Heterogeneity existed between centres and national guidelines regarding the minimal distance between dialysis chairs and recommendations regarding isolation and cohorting. Conclusions Although variation existed, measures to prevent transmission of SARS-CoV-2 were relatively similar across centres and national guidelines. Further research is needed to assess causal relationships between measures taken and spread of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 pandemic has alerted people of the threat caused by viruses. Vaccine is the most effective way to prevent the disease from spreading. The interaction between antibodies and antigens will clear the infectious organisms from the host. Identifying B-cell epitopes is critical in vaccine design, development of disease diagnostics and antibody production. However, traditional experimental methods to determine epitopes are time-consuming and expensive, and the predictive performance using the existing in silico methods is not satisfactory. This paper develops a general framework to predict variable-length linear B-cell epitopes specific for human-adapted viruses with machine learning approaches based on Protvec representation of peptides and physicochemical properties of amino acids. QR decomposition is incorporated during the embedding process that enables our models to handle variable-length sequences. Experimental results on large immune epitope datasets validate that our proposed model's performance is superior to the state-of-the-art methods in terms of AUROC (0.827) and AUPR (0.831) on the testing set. Moreover, sequence analysis also provides the results of the viral category for the corresponding predicted epitopes with high precision. Therefore, this framework is shown to reliably identify linear B-cell epitopes of human-adapted viruses given protein sequences and could provide assistance for potential future pandemics and epidemics. [ABSTRACT FROM AUTHOR]

The haemagglutination test (HAT)-field protocol described here is an optimization of the recently published HAT, for the detection of antibodies directed against the receptor binding domain (RBD) of the SARS-Cov-2 virus. HAT and HAT-field are both based on haemagglutination triggered by a single reagent, the IH4-RBD recombinant protein. A sample of IH4-RBD sufficient for several thousand tests or a plasmid encoding IH4-RBD can be obtained from the authors of our first paper. Using titration of IH4-RBD, HAT-field now allows a quantitative assessment of antibody levels in a single step, using a few microliters of whole blood, such as can be obtained by finger prick, and requires only very simple disposable equipment. Because it is based on a single soluble reagent, the test can be adapted very simply and rapidly to detect antibodies against variants of the SARS-CoV-2, or conceivably against different pathogens. HAT-field appears well suited to provide quantitative assessments of the serological protection of populations as well as individuals, and given its very low cost, the stability of the IH4-RBD reagent in the adapted buffer and the simplicity of the procedure, could be deployed pretty much anywhere, including in the poorest countries and the most remote corners of the globe. [ABSTRACT FROM AUTHOR]

The global pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2, has led to a dramatic loss of human life worldwide. Despite many efforts, the development of effective drugs and vaccines for this novel virus will take considerable time. Artificial intelligence (AI) and machine learning (ML) offer promising solutions that could accelerate the discovery and optimization of new antivirals. Motivated by this, in this paper, we present an extensive survey on the application of AI and ML for combating COVID-19 based on the rapidly emerging literature. Particularly, we point out the challenges and future directions associated with state-of-the-art solutions to effectively control the COVID-19 pandemic. We hope that this review provides researchers with new insights into the ways AI and ML fight and have fought the COVID-19 outbreak. [ABSTRACT FROM AUTHOR]

Background Previous research indicates that coronavirus disease 2019 (COVID-19) infection may have a role in triggering immunoglobulin A (IgA) nephropathy. However, limited research has explored the clinical implications of COVID-19 infection in individuals already diagnosed with IgA nephropathy. This study aimed to determine whether COVID-19 infection independently affects the subsequent trajectory of kidney function in IgA nephropathy patients. Methods This was a single-center cohort study. The study included 199 patients diagnosed with IgA nephropathy. The COVID-19 infection status was determined using a combined method: a questionnaire and the Health Code application, both administered at the end of 2022 in northern China. Kidney function trajectory was assessed by the estimated glomerular filtration rate (eGFR), calculated based on serum creatinine levels measured during follow-up outpatient visits. The primary endpoint of interest was the eGFR trajectory. Results Out of the 199 participants, 75% (n  = 181) reported a confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, determined through antigen or polymerase chain reaction tests, accounting for 79% (n  = 143) of the infected patients. A significant majority (98%) experienced mild to moderate symptoms. Over a median follow-up period of 10.7 months post-COVID-19 infection, notable clinical events included gross hematuria in 30 patients (16.6%), which normalized within an average of 3 days. Additionally, a 2-fold increase in proteinuria or progression to the nephrotic range was observed in 10 individuals (5.5%). No cases of acute kidney injury were noted. COVID-19 exposure was associated with an absolute change in eGFR of 2.98 mL/min/1.73 m2 per month (95% confidence interval 0.46 to 5.50). However, in a fully adjusted model, the estimated changes in eGFR slope post-COVID-19 were –0.39 mL/min/1.73 m2 per month (95% confidence interval –0.83 to 0.06, P  = .088) which included the possibility of no significant effect. Notably, a higher rate of kidney function decline was primarily observed in patients with a baseline eGFR <45 mL/min/1.73 m2 [–0.56 mL/min/1.73 m2 (–1.11 to –0.01), P  = .048]. In the cohort, there were few instances of severe COVID-19 cases. The absence of long-term follow-up outcomes was observed. Conclusions Overall, mild to moderate COVID-19 infection does not appear to significantly exacerbate the subsequent decline in kidney function among IgA nephropathy patients, particularly in those with preserved baseline kidney function. [ABSTRACT FROM AUTHOR]

Virus-like particle (VLP) vaccines had shown great potential during the COVID-19 pandemic, and was thought to be the next generation of antiviral vaccine technology due to viromimetic structures. However, the time-consuming and complicated processes in establishing a current recombinant-protein–based VLP vaccine has limited its quick launch to the out-bursting pandemic. To simplify and optimize VLP vaccine design, we herein report a kind of viromimetic polymer nanoparticle vaccine (VPNVax), with subunit receptor-binding domain (RBD) proteins conjugated to the surface of polyethylene glycol- b -polylactic acid (PEG- b -PLA) nanoparticles for vaccination against SARS-CoV-2. The preparation of VPNVax based on synthetic polymer particle and chemical post-conjugation makes it possible to rapidly replace the antigens and construct matched vaccines at the emergence of different viruses. Using this modular preparation system, we identified that VPNVax with surface protein coverage of 20%–25% had the best immunostimulatory activity, which could keep high levels of specific antibody titers over 5 months and induce virus neutralizing activity when combined with an aluminum adjuvant. Moreover, the polymer nano-vectors could be armed with more immune-adjuvant functions by loading immunostimulant agents or chemical chirality design. This VPNVax platform provides a novel kind of rapidly producing and efficient vaccine against different variants of SARS-CoV-2 as well as other viral pandemics. [ABSTRACT FROM AUTHOR]

Motivation The epidemic at the beginning of this year, due to a new virus in the coronavirus family, is causing many deaths and is bringing the world economy to its knees. Moreover, situations of this kind are historically cyclical. The symptoms and treatment of infected patients are, for better or worse even for new viruses, always the same: more or less severe flu symptoms, isolation and full hygiene. By now man has learned how to manage epidemic situations, but deaths and negative effects continue to occur. What about technology? What effect has the actual technological progress we have achieved? In this review, we wonder about the role of robotics in the fight against COVID. It presents the analysis of scientific articles, industrial initiatives and project calls for applications from March to now highlighting how much robotics was ready to face this situation, what is expected from robots and what remains to do. Results The analysis was made by focusing on what research groups offer as a means of support for therapies and prevention actions. We then reported some remarks on what we think is the state of maturity of robotics in dealing with situations like COVID-19. [ABSTRACT FROM AUTHOR]

Background During the coronavirus disease 2019 pandemic, a nucleic acid test is frequently conducted to identify positive cases. Compared with a hospital-based strategy, whole-community nucleic acid testing displays a unique advantage in rapid screening of a massive population. Yet a management plan to ensure ample and contamination-free sample collection is lacking. The objective of the current study was to establish an efficient operational mode of whole-community nucleic acid testing by management of a sample collection team and to provide a reference for joint prevention work to contain the spread of severe acute respiratory syndrome coronavirus 2. Methods The efficient operation of nucleic acid testing within the community was implemented by urgent setting up of sample collection teams, efficient allocation of medical supplies, optimization of management procedures and coordination among multiple working departments. Results A total of 21 585 nucleic acid samples were collected within 3 d, while no one was missed or experienced a cross infection. No falls, heatstroke, disputes or other adverse events occurred. Conclusions Under the emergency setting of nucleic acid testing of a large population, a management system with orderly organization, clear division of responsibilities and standardized operational procedures should be formulated. [ABSTRACT FROM AUTHOR]

Background To understand the impact of the COVID-19 pandemic on mortality, this study investigates overall, sex- and age-specific excess all-cause mortality in 20 countries, during 2020. Methods Total, sex- and age-specific weekly all-cause mortality for 2015–2020 was collected from national vital statistics databases. Excess mortality for 2020 was calculated by comparing weekly 2020 observed mortality against expected mortality, estimated from historical data (2015–2019) accounting for seasonality, long- and short-term trends. Crude and age-standardized rates were analysed for total and sex-specific mortality. Results Austria, Brazil, Cyprus, England and Wales, France, Georgia, Israel, Italy, Northern Ireland, Peru, Scotland, Slovenia, Sweden, and the USA displayed substantial excess age-standardized mortality of varying duration during 2020, while Australia, Denmark, Estonia, Mauritius, Norway, and Ukraine did not. In sex-specific analyses, excess mortality was higher in males than females, except for Slovenia (higher in females) and Cyprus (similar in both sexes). Lastly, for most countries substantial excess mortality was only detectable (Austria, Cyprus, Israel, and Slovenia) or was higher (Brazil, England and Wales, France, Georgia, Italy, Northern Ireland, Sweden, Peru and the USA) in the oldest age group investigated. Peru demonstrated substantial excess mortality even in the <45 age group. Conclusions This study highlights that excess all-cause mortality during 2020 is context dependent, with specific countries, sex- and age-groups being most affected. As the pandemic continues, tracking excess mortality is important to accurately estimate the true toll of COVID-19, while at the same time investigating the effects of changing contexts, different variants, testing, quarantine, and vaccination strategies. [ABSTRACT FROM AUTHOR]

STUDY QUESTION How did the first two coronavirus disease 2019 (COVID-19) waves affect fertility rates in the USA? SUMMARY ANSWER States differed widely in how their fertility rates changed following the COVID-19 outbreak and these changes were influenced more by state-level economic, racial, political, and social factors than by COVID-19 wave severity. WHAT IS KNOWN ALREADY The outbreak of the COVID-19 pandemic contributed to already declining fertility rates in the USA, but not equally across states. Identifying drivers of differential changes in fertility rates can help explain variations in demographic shifts across states in the USA and motivate policies that support families in general, not only during crises. STUDY DESIGN, SIZE, DURATION This is an ecological study using state-level data from 50 US states and the District of Columbia (n = 51). The study period extends from 2020 to 2021 with historical data from 2016 to 2019. We identified Wave 1 as the first apex for each state after February 2020 and Wave 2 as the second apex, during Fall/Winter 2020–2021. PARTICIPANTS/MATERIALS, SETTING, METHODS State-level COVID-19 wave severity, defined as case acceleration during each 3-month COVID-19 wave (cases/100 000 population/month), was derived from 7-day weekly moving average COVID-19 case rates from the US Centers for Disease Control and Prevention (CDC). State-level fertility rate changes (change in average monthly fertility rate/100 000 women of reproductive age (WRA)/year) were derived from the CDC Bureau of Vital Statistics and from 2020 US Census and University of Virginia 2021 population estimates 9 months after each COVID-19 wave. We performed univariate analyses to describe national and state-level fertility rate changes following each wave, and simple and multivariable linear regression analyses to assess the relation of COVID-19 wave severity and other state-level characteristics with fertility rate changes. MAIN RESULTS AND THE ROLE OF CHANCE Nationwide, fertility dropped by 17.5 births/month/100 000 WRA/year following Wave 1 and 9.2 births/month/100 000 WRA/year following Wave 2. The declines following Wave 1 were largest among majority-Democrat, more non-White states where people practiced greater social distancing. Greater COVID-19 wave severity was associated with steeper fertility rate decline post-Wave 1 in simple regression, but the association was attenuated when adjusted for other covariates. Adjusting for the economic impact of the pandemic (hypothesized mediator) also attenuated the effect. There was no relation between COVID-19 wave severity and fertility rate change following Wave 2. LIMITATIONS, REASONS FOR CAUTION Our study harnesses state-level data so individual-level conclusions cannot be inferred. There may be residual confounding in our multivariable regression and we were underpowered to detect some effects. WIDER IMPLICATIONS OF THE FINDINGS The COVID-19 pandemic initially impacted the national fertility rate but, overall, the fertility rate rebounded to the pre-pandemic level following Wave 2. Consistent with prior literature, COVID-19 wave severity did not appear to predict fertility rate change. Economic, racial, political, and social factors influenced state-specific fertility rates during the pandemic more than the severity of the outbreak alone. Future studies in other countries should also consider whether these factors account for internal heterogeneity when examining the impact of the COVID-19 pandemic and other crises on fertility. STUDY FUNDING/COMPETING INTEREST(S) L.G.K. received funding from the National Institute of Environmental Health Sciences (R00ES030403), M.C. from the National Science Foundation Graduate Research Fellowship Program (20-A0-00-1005789), and M.L. and E.S. from the National Institute of Environmental Health Sciences (R01ES032808). None of the authors have competing interests. TRIAL REGISTRATION NUMBER N/A. [ABSTRACT FROM AUTHOR]

Context During the COVID-19 pandemic, both people with underlying diseases and previously healthy people were infected with SARS-CoV-2. In our institute, most hospitalized patients underwent chest computed tomography (CT) to evaluate pulmonary involvement and complication of COVID-19. There are currently limited data regarding thyroid CT incidentalomas in healthy people. Objective We aimed to investigate the prevalence and predictors of thyroid incidentalomas among hospitalized patients with COVID-19. Methods A single-center retrospective study included hospitalized patients aged ≥15 years with COVID-19 who underwent chest CT during April 2020 and October 2021. Thyroid incidentalomas were reviewed and identified by an experienced radiologist. Logistic regression analysis was used to determine predictors for thyroid incidentalomas. Results In the 1326 patients (mean age 49.4 years and 55.3% female) that were included, the prevalence of thyroid incidentalomas was 20.2%. Patients with thyroid incidentalomas were older (59.6 years vs 46.8 years, P <.001) and more often female than those without incidentalomas (63.4% vs 53.2%, P =.003). On multivariate analysis, only female sex (OR 1.56; 95% CI 1.17-2.07) and older age (OR 1.04; 95% CI 1.03-1.05) were significantly associated with thyroid incidentalomas. Conclusion In COVID-19 patients, the prevalence of thyroid incidentalomas identified on chest CT was higher (20.2%) than in previous studies in the general population (<1% to 16.8%). Female sex and older age were independent factors associated with thyroid incidentalomas. [ABSTRACT FROM AUTHOR]

The Covid-19 caused by the SARS-CoV-2 virus has shown how inadequate institutional strategies interact with, and exacerbate, social inequalities, thus impacting upon the intensity of the harm produced and amplifying negative consequences. One of the lessons from this pandemic, which happens against the background of other, interconnected systemic crises, is the urgency of adopting a 'whole-of-society' approach to determining what does and what does not work in the context of a health emergency response. However, how can institutional performance in health emergency response be assessed? How to make sense of success or failure? We argue that the adoption of a risk governance approach sheds light on institutional performance in the response to health emergencies. Risk governance is particularly pertinent in situations where the potential for extreme consequences is considered high, where there are enormous uncertainties regarding the consequences and where different values are present and in dispute. Based on a documentary evidence review, we analyse the Brazilian response to Covid-19 by considering: (1) how the Brazilian federal government performed on its central role of managing the national response, (2) the reactions from other actors prompted by this performance and (3) the main observed effects emerging from this scenario. We argue that the Brazilian federal government response was weak in five risk governance parameters that are essential in a health crisis response: risk communication, transparency and accessibility of data, negotiation between actors, social cohesion and public participation and decisions based on technical and scientific evidence, resources and contexts. The neglect of risk governance parameters, combined with an attempt to spread doubt, confusion and disinformation—which could be termed a 'governance by chaos'—is an important element for making sense of the effects and controversies surrounding Covid-19 in Brazil. [ABSTRACT FROM AUTHOR]

Objective: This work aims to review and discuss controversial topics in the field of vitamin D, SARS-CoV-2 infection, and COVID-19. Methods: The International Conferences “Controversies in Vitamin D” are a series of workshops that started in 2017 featuring international experts and leaders in vitamin D research and clinical practice. The fifth annual conference was held in Stresa, Italy, September 15 to 18, 2021. Evidence: Before the event, participants reviewed available studies on their assigned topic, drafted a related abstract, and presented their findings at the time of the conference. Relevant literature that became available since was also discussed within the panel and updated accordingly. Consensus: Before the event, the drafted abstracts had been merged to prepare a preliminary document. After the conference presentations, in-depth discussions in open sessions led to consensus. The document was subsequently modified according to discussions and up-to-date literature inclusion. Conclusions: There is quite consistent evidence for an association between low 25 OH vitamin D (25(OH)D) levels and poor COVID-19 outcomes, despite heterogeneous publications of variable quality. However, the low vitamin D status in COVID-19 patients might also reflect reverse causality. Vitamin D supplementation might have a positive role in COVID-19 prevention. The evidence supporting a beneficial effect of vitamin D treatment in decreasing the risk of COVID-19 complications is conflicting. Conclusive statements regarding the beneficial effect of vitamin D in this context await high-quality, randomized controlled trials. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that was first identified in December 2019 and emerged into an ongoing global pandemic. Both the pandemic itself and the associated public restrictive measures of social mobility established with different intensity over different periods in various countries have significantly affected the everyday activities and lifestyles of people all over the world. The impact of lockdown and quarantine measures on hypertension incidence and blood pressure (BP) control is an important topic that requires further investigation. The aim of this review is: a) to present the current evidence regarding the actual effects of public restrictive measures on BP levels and control, originating primarily from studies investigating the impact of public restrictive measures on BP control with the use of various BP phenotypes; b) to summarize the possible pandemic-related effects of factors known to affect BP levels, including both traditional (e.g. dietary habits including alcohol and sodium intake, body weight, smoking and physical activity) and non-traditional (e.g. sleep patterns, air pollution, environmental noise, delayed diagnosis and medication adherence) ones. [ABSTRACT FROM AUTHOR]

Introduction Little is known about the impact of the coronavirus on sexual behavior, function, and satisfaction. Aim The aim of the present study was to systematically review people's sexual function and behaviors and their changes in sexual activities during the COVID-19 pandemic. Methods Comprehensive searches in PubMed, Web of Science, and Scopus were conducted with keywords in accordance with MeSH terms: COVID-19, SARS-CoV-2, coronavirus, sexual health, sexual function, sexual dysfunctions, sexuality, sexual orientation, sexual activities, and premarital sex. Two reviewers independently assessed full-text articles according to predefined criteria: original design, English studies, and investigating either the general population or sexual minorities. Results Risk of bias in the studies was assessed by the Newcastle-Ottawa Scale, and data were pooled via random effects meta-analyses. We utilized the standardized mean difference to evaluate the effects of the COVID-19 pandemic on sexual activity, functioning, and satisfaction. We included 19 studies in the analysis and 11 studies in the meta-analysis, with a sample size of 12 350. To investigate sexual activity changes, a sample size of 8838 was entered into the subgroup analysis, which showed a significant decrease in both genders (5821 women, P <.033; 3017 men, P <.008). A subgroup meta-analysis showed that the sexual function of men and women during the COVID-19 pandemic significantly declined (3974 women, P <.001; 1427 men, P <.001). Sexual desire and arousal decreased in both genders, though mainly in women. In investigating sexual satisfaction changes during the COVID-19 pandemic, a meta-analysis with a sample size of 2711 showed a significant decrease (P <.001). The most indicative changes in sexual behaviors during the pandemic were the increase in masturbating and usage of sex toys. Greater COVID-19 knowledge was associated with lower masturbation, oral sex, and vaginal sex. The more protective behaviors were associated with less hugging, kissing, cuddling, genital touching, watching porn with a partner, and vaginal sex. Conclusion The COVID-19 pandemic led to increased challenges and changes for individuals' sexual behaviors. Efforts for preventive strategies should therefore be concentrated between pandemics, while ensuring that there is information available to the population during a pandemic for help in times of psychological distress or crisis. [ABSTRACT FROM AUTHOR]

Computational prediction of T cell epitopes is a crucial component in the development of novel vaccines. T cells in a healthy vertebrate host can recognize as non-self only those peptides that are present in the parasite's proteins but absent in the host's proteins. This principle enables us to determine the current and past host specificity of a parasite and to predict peptides capable of eliciting a T cell response. Building upon the detailed mapping of T cell clone specificity for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) antigens, we employed Monte Carlo tests to determine that empirically confirmed T cell-stimulating peptides have a significantly increased proportion of pentapeptides, hexapeptides and heptapeptides not found in the human proteome (P  < 0.0001, Cohen's d  > 4.9). We observed a lower density of potential pentapeptide targets for T cell recognition in the spike protein from the human-adapted SARS-CoV-2 ancestor compared to 10 other SARS-CoV-2 proteins originating from the horseshoe bat-adapted ancestor. Our novel method for predicting T cell immunogenicity of SARS-CoV-2 peptides is four times more effective than previous approaches. We recommend utilizing our theory-based method where efficient empirically based algorithms are unavailable, such as in the development of certain veterinary vaccines, and combining it with empirical methods in other cases for optimal results. [ABSTRACT FROM AUTHOR]

The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a critical challenge. A new algorithm, iDRO (i ntegrated d eep-learning-based m R NA o ptimization), is developed to optimize multiple components of mRNA sequences based on given amino acid sequences of target protein. Considering the biological constraints, we divided iDRO into two steps: open reading frame (ORF) optimization and 5′ untranslated region (UTR) and 3′UTR generation. In ORF optimization, BiLSTM-CRF (bidirectional long-short-term memory with conditional random field) is employed to determine the codon for each amino acid. In UTR generation, RNA-Bart (bidirectional auto-regressive transformer) is proposed to output the corresponding UTR. The results show that the optimized sequences of exogenous genes acquired the pattern of human endogenous gene sequence. In experimental validation, the mRNA sequence optimized by our method, compared with conventional method, shows higher protein expression. To the best of our knowledge, this is the first study by introducing deep-learning methods to integrated mRNA sequence optimization, and these results may contribute to the development of mRNA therapeutics. [ABSTRACT FROM AUTHOR]

This cross-sectional study evaluated the long-term health effects of coronavirus disease 2019 (COVID-19) in Jianghan District (Wuhan, China). The results showed that 61.4% of COVID-19 patients reported at least one symptom and 8.8% had depressive symptoms at the 17-month follow-up. The proportion of patients with chest radiographic abnormalities in Fangcang shelter hospitals and designated COVID-19 hospitals was 31.6% and 41.1%, respectively, and the proportion of patients with impaired pulmonary diffusion capacity in these hospitals was 52.8% and 60.9%, respectively. Female sex (odds ratio [OR] = 1.48, 95% confidence interval [CI]: 1.16–1.88), severe disease (OR = 1.46, 95% CI: 1.01–2.10) and a higher number of initial symptoms (OR = 1.31, 95% CI: 1.23–1.40) were associated with the development of sequelae symptoms at 17 months. This study involving community-dwelling COVID-19 adults may help determine the long-term effects of COVID-19 during the first pandemic wave. Nonetheless, larger follow-up studies are needed to characterize the post-COVID-19 condition. [ABSTRACT FROM AUTHOR]

Following the global COVID-19 pandemic, nanotechnology has been at the forefront of research efforts and enables the fast development of diagnostic tools, vaccines and antiviral treatment for this novel virus (SARS-CoV-2). In this review, we first summarize nanotechnology with regard to the detection of SARS-CoV-2, including nanoparticle-based techniques such as rapid antigen testing, and nanopore-based sequencing and sensing techniques. Then we investigate nanotechnology as it applies to the development of COVID-19 vaccines and anti-SARS-CoV-2 nanomaterials. We also highlight nanotechnology for the post-pandemic era, by providing tools for the battle with SARS-CoV-2 variants and for enhancing the global distribution of vaccines. Nanotechnology not only contributes to the management of the ongoing COVID-19 pandemic but also provides platforms for the prevention, rapid diagnosis, vaccines and antiviral drugs of possible future virus outbreaks. [ABSTRACT FROM AUTHOR]

Novel coronavirus disease infection (coronavirus disease 2019, COVID-19) was declared a global pandemic in March 2020 and since then has become a major public health problem. The prevalence of COVID-19 infection and acute kidney injury (AKI) is variable depending on several factors such as race/ethnicity and severity of illness. The pathophysiology of renal involvement in COVID-19 infection is not entirely clear, but it could be in part explained by the viral tropism in the kidney parenchyma. AKI in COVID-19 infection can be either by direct invasion of the virus or as a consequence of immunologic response. Diverse studies have focused on the effect of COVID-19 on glomerulonephritis (GN) patients or the 'novo' GN; however, the effect of COVID-19 in acute tubulointerstitial nephritis (ATIN) has been scarcely studied. In this article, we present five cases with different spectrums of COVID-19 infection and ATIN that may suggest that recent diagnosis of ATIN is accompanied by a worse clinical prognosis in comparison with long-term diagnosed ATIN. [ABSTRACT FROM AUTHOR]

The worldwide shortage of vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection while the pandemic still remains uncontrolled has led many countries to the dilemma of whether or not to vaccinate previously infected persons. Understanding the level of protection conferred by previous infection compared with that of vaccination is important for policy-making. We analyzed an updated individual-level database of the entire population of Israel to assess the protection provided by both prior infection and vaccination in preventing subsequent SARS-CoV-2 infection, hospitalization with coronavirus disease 2019 (COVID-19), severe disease, and death due to COVID-19. Outcome data were collected from December 20, 2020, to March 20, 2021. Vaccination was highly protective, with overall estimated effectiveness of 94.5% (95% confidence interval (CI): 94.3, 94.7) for documented infection, 95.8% (95% CI: 95.2, 96.2) for hospitalization, 96.3% (95% CI: 95.7, 96.9) for severe illness, and 96.0% (95% CI: 94.9, 96.9) for death. Similarly, the overall estimated level of protection provided by prior SARS-CoV-2 infection was 94.8% (95% CI: 94.4, 95.1) for documented infection, 94.1% (95% CI: 91.9, 95.7) for hospitalization, and 96.4% (95% CI: 92.5, 98.3) for severe illness. Our results should be considered by policy-makers when deciding whether or not to prioritize vaccination of previously infected adults. [ABSTRACT FROM AUTHOR]

Background The coronavirus disease (COVID) pandemic has resulted in a major disruption in healthcare that has affected several medical and surgical specialties. European and American Vascular Societies have proposed deferring the creation of an elective vascular access (VA) [autologous or prosthetic arteriovenous fistula (AVF) or arteriovenous graft (AVG)] in incident patients on haemodialysis (HD) in the era of the COVID pandemic. The aim of this study is to examine the impact of the COVID pandemic on VA creation and the central venous catheter (CVC)-related hospitalizations and complications in HD patients dialyzed in 16 Spanish HD units of three different regions. Methods We compared retrospectively two periods of time: the pre-COVID (1 January 2019–11 March 2020) and the COVID era (12 March 2020–30 June 2021) in all HD patients (prevalent and incident) dialyzed in our 16 HD centres. The variables analysed were type of VA (CVC, AVF and AVG) created, percentage of CVC in incident and prevalent HD patients, CVC-related hospitalizations and complications (infection, extrusion, disfunction, catheter removal) and percentage of CVC HD sessions that did not reach the goal of Kt (>45) as a marker of HD adequacy. Results A total of 1791 VAs for HD were created and 905 patients started HD during the study period. Patients who underwent vascular access surgery during the COVID period compared with pre-COVID period were significantly younger, with a significant decrease in surgical activity to create AVFs and AVGs in older HD patients (>75 and >85 years of age). There was a significant increase in CVC placement (from 59.7% to 69.5%; P < 0.001) from the pre-COVID to the COVID period. During the COVID pandemic, a significantly higher number of patients started HD through a CVC (80.3% versus 69.1%; P < 0.001). The percentage of CVC in prevalent HD patients has not decreased in the 19 months since the start of the pandemic [414 CVC/1058 prevalent patients (39.4%)]. No significant changes were detected in CVC-related hospitalizations between the pre-COVID and COVID periods. In the COVID period, a significant increase in catheter replacement and the percentage of HD session that did not reach the HD dose objective (Kt > 45) was observed. Conclusions COVID has presented a public health system crisis that has influenced VA for HD, with an increase in CVCs relative to AVFs. A decrease in HD sessions that did not reach the HD dose objective was observed in the COVID period compared with a pre-COVID period. [ABSTRACT FROM AUTHOR]

The mitochondrial membrane potential (ΔΨm) is a parameter often used to determine mitochondrial function; therefore, it can be used to determine the integrity and functionality of cells. A decrement of ΔΨm is implicated in several inflammatory‐related pathologies, such phenomena can be related to COVID‐19 infection. The present work aimed to compare the ΔΨm in leucocytes (human PBMCs; HPBMC) isolated from healthy control (HC) subjects, patients with COVID‐19 (C‐19), recovered subjects at 40 ± 13 (R1) and 335 ± 20 (R2) days after infection (dai). Obtained data showed that ΔΨm decreased in HPBMC of subjects with C‐19, R1, and R2 compared with HC. When analyzing the ΔΨm data by sex, in females, a significant decrease was observed in R1 and R2 groups versus HC. Regarding men, a significant decrease of ΔΨm was observed in R1, with respect to HC, contrary to R2 group, who reestablished this parameter. Obtained results suggest that the loss of ΔΨm could be related to the long‐COVID. [ABSTRACT FROM AUTHOR]

Aims Since its emergence in early 2020, the novel severe acute respiratory syndrome coronavirus 2 causing coronavirus disease 2019 (COVID-19) has reached pandemic levels, and there have been repeated outbreaks across the globe. The aim of this two part series is to provide practical knowledge and guidance to aid clinicians in the diagnosis and management of cardiovascular (CV) disease in association with COVID-19. Methods and results A narrative literature review of the available evidence has been performed, and the resulting information has been organized into two parts. The first, which was reported previously, focused on the epidemiology, pathophysiology, and diagnosis of CV conditions that may be manifest in patients with COVID-19. This second part addresses the topics of: care pathways and triage systems and management and treatment pathways, both of the most commonly encountered CV conditions and of COVID-19; and information that may be considered useful to help patients with CV disease (CVD) to avoid exposure to COVID-19. Conclusion This comprehensive review is not a formal guideline but rather a document that provides a summary of current knowledge and guidance to practicing clinicians managing patients with CVD and COVID-19. The recommendations are mainly the result of observations and personal experience from healthcare providers. Therefore, the information provided here may be subject to change with increasing knowledge, evidence from prospective studies, and changes in the pandemic. Likewise, the guidance provided in the document should not interfere with recommendations provided by local and national healthcare authorities. [ABSTRACT FROM AUTHOR]

We conducted 3 successive seroprevalence surveys, 3 months apart, using multistage cluster sampling to measure the extent and dynamics of the severe acute respiratory syndrome coronavirus 2 epidemic in Conakry, the capital city of Guinea. Seroprevalence increased from 17.3% (95% CI, 12.4%–23.8%) in December 2020 during the first survey (S1) to 28.9% (95% CI, 25.6%–32.4%) in March/April 2021 (S2), then to 42.4% (95% CI, 39.5%–45.3%) in June 2021 (S3). This significant overall trend of increasing seroprevalence (P  < .0001) was also significant in every age class, illustrating a sustained transmission within the whole community. These data may contribute to defining cost-effective response strategies. [ABSTRACT FROM AUTHOR]

Nonpharmaceutical interventions, such as social distancing and lockdowns, have been essential to control of the coronavirus disease 2019 (COVID-19) pandemic. In particular, localized lockdowns in small geographic areas have become an important policy intervention for preventing viral spread in cases of resurgence. These localized lockdowns can result in lower social and economic costs compared with larger-scale suppression strategies. Using an integrated data set from Chile (March 3–June 15, 2020) and a novel synthetic control approach, we estimated the effect of localized lockdowns, disentangling its direct and indirect causal effects on transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our results showed that the effects of localized lockdowns are strongly modulated by their duration and are influenced by indirect effects from neighboring geographic areas. Our estimates suggest that extending localized lockdowns can slow down SARS-CoV-2 transmission; however, localized lockdowns on their own are insufficient to control pandemic growth in the presence of indirect effects from contiguous neighboring areas that do not have lockdowns. These results provide critical empirical evidence about the effectiveness of localized lockdowns in interconnected geographic areas. [ABSTRACT FROM AUTHOR]

Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context. [ABSTRACT FROM AUTHOR]

Background Vaccination programs are essential for the containment of the coronavirus disease 2019 pandemic, which has hit haemodialysis populations especially hard. Early reports suggest a reduced immunologic response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in dialysis patients, in spite of a high degree of seroconversion. We aimed to identify risk factors for a reduced efficacy of an mRNA vaccine in a cohort of haemodialysis patients. Method In a multicentre study, including 294 Portuguese haemodialysis patients who had received two doses of BNT162b2 with a 3-week interval, immunoglobulin G-class antibodies against the SARS-CoV-2 spike protein were determined 3 weeks after the first dose (M1) and 6 weeks after the second dose (M2). The threshold for seroconversion was 10 UR/mL. Demographic and clinical data were retrieved from a quality registry. Adverse events were registered using a questionnaire. Results At M2, seroconversion was 93.1% with a median antibody level of 197.5 U/mL (1.2–3237.0) and a median increase of 180.0 U/mL (−82.9 to 2244.6) from M1. Age [beta −8.9; 95% confidence interval (95% CI) −12.88 to −4.91; P < 0.0001], ferritin >600 ng/mL (beta 183.93; 95% CI 74.75–293.10; P = 0.001) and physical activity (beta 265.79; 95% CI 30.7–500.88; P = 0.03) were independent predictors of SARS-CoV-2 antibody levels after two vaccine doses. Plasma albumin >3.5 g/dL independently predicted the increase of antibody levels between both doses (odds ratio 14.72; 95% CI 1.38 to 157.45; P = 0.03). Only mild adverse reactions were observed in 10.9% of patients. Conclusions The SARS-CoV-2 vaccine BNT162b2 is safe and effective in haemodialysis patients. Besides age, iron status and nutrition are possible modifiable modulators of the immunologic response to SARS-CoV-2 mRNA vaccines. These data suggest the need for an early identification of populations at higher risk for diminished antibody production and the potential advantage of the implementation of oriented strategies to maximize the immune response to vaccination in these patients. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate overall and sex-specific excess all-cause mortality since the inception of the COVID-19 pandemic until August 2020 among 22 countries.Methods: Countries reported weekly or monthly all-cause mortality from January 2015 until the end of June or August 2020. Weekly or monthly COVID-19 deaths were reported for 2020. Excess mortality for 2020 was calculated by comparing weekly or monthly 2020 mortality (observed deaths) against a baseline mortality obtained from 2015-2019 data for the same week or month using two methods: (i) difference in observed mortality rates between 2020 and the 2015-2019 average and (ii) difference between observed and expected 2020 deaths.Results: Brazil, France, Italy, Spain, Sweden, the UK (England, Wales, Northern Ireland and Scotland) and the USA demonstrated excess all-cause mortality, whereas Australia, Denmark and Georgia experienced a decrease in all-cause mortality. Israel, Ukraine and Ireland demonstrated sex-specific changes in all-cause mortality.Conclusions: All-cause mortality up to August 2020 was higher than in previous years in some, but not all, participating countries. Geographical location and seasonality of each country, as well as the prompt application of high-stringency control measures, may explain the observed variability in mortality changes. [ABSTRACT FROM AUTHOR]

Background First severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections on Danish mink farms were reported in June 2020 and thereupon spread geographically. We provide population-level evidence on excess human incidence rates in Danish municipalities affected by disease outbreaks on mink farms and evaluate the effectiveness of two non-pharmaceutical interventions, i.e. culling of infected mink and local lockdowns. Methods We use information on SARS-CoV-2 outbreaks on mink farms in 94 Danish municipalities together with data on human SARS-CoV-2 cases and tested persons in Weeks 24–51 of 2020. Difference-in-difference estimation and panel event studies for weekly human incidence rates are applied to (i) identify epidemiological trends of human SARS-CoV-2 infections associated with disease outbreaks on mink farms, and (ii) quantify the mitigating effects from the two non-pharmaceutical interventions. Results SARS-CoV-2 outbreaks on mink farms in a municipality associate with an increase in weekly human incidence rates by about 75%; spatial spillover effects to neighbouring municipalities are also observed. Local lockdowns reduce human incidence rates, while culling of mink appears to be more effective in combination with a lockdown. The temporal lag between an outbreak on a mink farm and a significant increase in human incidence rates is estimated to be 1–3 weeks; lockdowns and culling of mink neutralize this effect 4–8 weeks after the initial outbreak. Conclusions SARS-CoV-2 infections among farmed mink in Denmark significantly link to local human infection trends. Strict animal and human disease surveillance in regions with mink farming should be pursued internationally to mitigate future epidemic developments. [ABSTRACT FROM AUTHOR]

Aims Coronavirus disease 2019 (COVID-19) can lead to multiorgan damage. MicroRNAs (miRNAs) in blood reflect cell activation and tissue injury. We aimed to determine the association of circulating miRNAs with COVID-19 severity and 28 day intensive care unit (ICU) mortality. Methods and results We performed RNA-Seq in plasma of healthy controls (n  =   11), non-severe (n  =   18), and severe (n  =   18) COVID-19 patients and selected 14 miRNAs according to cell- and tissue origin for measurement by reverse transcription quantitative polymerase chain reaction (RT–qPCR) in a separate cohort of mild (n  =   6), moderate (n  =   39), and severe (n  =   16) patients. Candidates were then measured by RT–qPCR in longitudinal samples of ICU COVID-19 patients (n  =   240 samples from n  =   65 patients). A total of 60 miRNAs, including platelet-, endothelial-, hepatocyte-, and cardiomyocyte-derived miRNAs, were differentially expressed depending on severity, with increased miR-133a and reduced miR-122 also being associated with 28 day mortality. We leveraged mass spectrometry-based proteomics data for corresponding protein trajectories. Myocyte-derived (myomiR) miR-133a was inversely associated with neutrophil counts and positively with proteins related to neutrophil degranulation, such as myeloperoxidase. In contrast, levels of hepatocyte-derived miR-122 correlated to liver parameters and to liver-derived positive (inverse association) and negative acute phase proteins (positive association). Finally, we compared miRNAs to established markers of COVID-19 severity and outcome, i.e. SARS-CoV-2 RNAemia, age, BMI, D-dimer, and troponin. Whilst RNAemia, age and troponin were better predictors of mortality, miR-133a and miR-122 showed superior classification performance for severity. In binary and triplet combinations, miRNAs improved classification performance of established markers for severity and mortality. Conclusion Circulating miRNAs of different tissue origin, including several known cardiometabolic biomarkers, rise with COVID-19 severity. MyomiR miR-133a and liver-derived miR-122 also relate to 28 day mortality. MiR-133a reflects inflammation-induced myocyte damage, whilst miR-122 reflects the hepatic acute phase response. [ABSTRACT FROM AUTHOR]

The confirmed number of SARS-CoV-2 infections up to 18 October 2022 is 626 million worldwide, but information about factors affecting the probability of infection or a severe course of COVID-19 remains insufficient and often speculative. Only a small number of factors have been rigorously examined, mostly by retrospective or cross-sectional studies.   We ran a preregistered study on 5164 Internet users who shared information with us about their exposure to 105 risk factors and reported being COVID-19 negative before the beginning of the fourth wave of COVID-19 in the Czech Republic. After the fourth wave, in which 709 (13.7%) of participants were infected, we used a partial Kendall test controlled for sex, age, and urbanization to compare the risk of infection and a severe course of the disease in subjects who initially did and did not report exposure to particular risk factors.   After the correction for multiple tests, we identified 13 factors – including male sex, lower age, blood group B, and larger household size – that increased the risk of infection and 16 factors – including mask-wearing, borreliosis in the past, use of vitamin D supplements, or rooibos drinking – that decreased it. We also identified 23 factors that increased the risk of a severe course of COVID-19 and 12 factors that decreased the risk.   This preregistered longitudinal study is of explorative nature. Therefore, although the observed effects were strong and remained highly significant even after correction for multiple tests, it will be necessary to confirm their existence in future independent studies. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has highlighted the need to come out with quick interventional solutions that can now be obtained through the application of different bioinformatics software to actively improve the success rate. Technological advances in fields such as computer modeling and simulation are enriching the discovery, development, assessment and monitoring for better prevention, diagnosis, treatment and scientific evidence generation of specific therapeutic strategies. The combined use of both molecular prediction tools and computer simulation in the development or regulatory evaluation of a medical intervention, are making the difference to better predict the efficacy and safety of new vaccines. An integrated bioinformatics pipeline that merges the prediction power of different software that act at different scales for evaluating the elicited response of human immune system against every pathogen is proposed. As a working example, we applied this problem solving protocol to predict the cross-reactivity of pre-existing vaccination interventions against SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Introduction Care homes have been severely affected by the SARS-CoV-2 pandemic. Rapid antigen testing could identify most SARS-CoV-2 infected staff and visitors before they enter homes. We explored implementation of staff and visitor testing protocols using lateral flow devices (LFDs). Methods An evaluation of a SARS-CoV-2 LFD-based testing protocol in 11 care homes in Liverpool, UK, including staff and visitor testing, plus a qualitative exploratory study in nine of these homes. The proportion of pilot homes with outbreaks, and outbreak size, were compared to non-pilot homes in Liverpool. Adherence to testing protocols was evaluated. Fifteen staff were interviewed, and transcript data were thematically coded using an iterative analysis to identify and categorize factors influencing testing implementation. Results In total, 1,638 LFD rapid tests were performed on 407 staff. Protocol adherence was poor with 8.6% of staff achieving >75% protocol adherence, and 25.3% achieving |$\ge$| 50%. Six care homes had outbreaks during the study. Compared to non-pilot care homes, there was no evidence of significant difference in the proportion of homes with outbreaks, or the size of outbreaks. Qualitative data showed difficulty implementing testing strategies due to excessive work burden. Factors influencing adherence related to test integration and procedural factors, socio-economic factors, cognitive overload and the emotional value of testing. Conclusion Implementation of staff and visitor care home LFD testing protocols was poorly adhered to and consequently did not reduce the number or scale of COVID-19 outbreaks. More focus is needed on the contextual and behavioural factors that influence protocol adherence. [ABSTRACT FROM AUTHOR]

Epidemiologists sometimes use external sources of variation to explore highly confounded exposure-outcome relationships or exposures that cannot be randomized. These exogenous sources of variation, or natural experiments, are sometimes proposed as instrumental variables to examine the effects of given exposures on given outcomes. Previous epidemiologic studies have applied this technique using famines, earthquakes, weather events, and previous pandemics as exogenous sources of variation for other exposures; interest in applying this technique using the current severe acute respiratory system coronavirus 2 (SARS-CoV-2) pandemic is already documented. Yet large-scale events like these likely have broad and complicated impacts on human health, which almost certainly violates the exclusion restriction assumption of instrumental variable analyses. We review the assumptions of instrumental variable analyses, highlight previous applications of this method with respect to natural experiments with broad impacts or "shocks," and discuss how these relate to our current observations of the SARS-CoV-2 pandemic. While we encourage thorough investigation of the broad impacts of the SARS-CoV-2 pandemic on human health, we caution against its widespread use as an instrumental variable to study other exposures of interest. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the main reason for the increasing number of deaths worldwide. Although strict quarantine measures were followed in many countries, the disease situation is still intractable. Thus, it is needed to utilize all possible means to confront this pandemic. Therefore, researchers are in a race against the time to produce potential treatments to cure or reduce the increasing infections of COVID-19. Computational methods are widely proving rapid successes in biological related problems, including diagnosis and treatment of diseases. Many efforts in recent months utilized Artificial Intelligence (AI) techniques in the context of fighting the spread of COVID-19. Providing periodic reviews and discussions of recent efforts saves the time of researchers and helps to link their endeavors for a faster and efficient confrontation of the pandemic. In this review, we discuss the recent promising studies that used Omics-based data and utilized AI algorithms and other computational tools to achieve this goal. We review the established datasets and the developed methods that were basically directed to new or repurposed drugs, vaccinations and diagnosis. The tools and methods varied depending on the level of details in the available information such as structures, sequences or metabolic data. [ABSTRACT FROM AUTHOR]

The rapid spread and huge impact of the COVID-19 pandemic caused by the emerging SARS-CoV-2 have driven large efforts for sequencing and analyzing the viral genomes. Mutation analyses have revealed that the virus keeps mutating and shows a certain degree of genetic diversity, which could result in the alteration of its infectivity and pathogenicity. Therefore, appropriate delineation of SARS-CoV-2 genetic variants enables us to understand its evolution and transmission patterns. By focusing on the nucleotides that co-substituted, we first identified 42 co-mutation modules that consist of at least two co-substituted nucleotides during the SARS-CoV-2 evolution. Then based on these co-mutation modules, we classified the SARS-CoV-2 population into 43 groups and further identified the phylogenetic relationships among groups based on the number of inconsistent co-mutation modules, which were validated with phylogenetic trees. Intuitively, we tracked tempo-spatial patterns of the 43 groups, of which 11 groups were geographic-specific. Different epidemic periods showed specific co-circulating groups, where the dominant groups existed and had multiple sub-groups of parallel evolution. Our work enables us to capture the evolution and transmission patterns of SARS-CoV-2, which can contribute to guiding the prevention and control of the COVID-19 pandemic. An interactive website for grouping SARS-CoV-2 genomes and visualizing the spatio-temporal distribution of groups is available at https://www.jianglab.tech/cmm-grouping/. [ABSTRACT FROM AUTHOR]

To attain promising pharmacotherapies, researchers have applied drug repurposing (DR) techniques to discover the candidate medicines to combat the coronavirus disease 2019 (COVID-19) outbreak. Although many DR approaches have been introduced for treating different diseases, only structure-based DR (SBDR) methods can be employed as the first therapeutic option against the COVID-19 pandemic because they rely on the rudimentary information about the diseases such as the sequence of the severe acute respiratory syndrome coronavirus 2 genome. Hence, to try out new treatments for the disease, the first attempts have been made based on the SBDR methods which seem to be among the proper choices for discovering the potential medications against the emerging and re-emerging infectious diseases. Given the importance of SBDR approaches, in the present review, well-known SBDR methods are summarized, and their merits are investigated. Then, the databases and software applications, utilized for repurposing the drugs against COVID-19, are introduced. Besides, the identified drugs are categorized based on their targets. Finally, a comparison is made between the SBDR approaches and other DR methods, and some possible future directions are proposed. [ABSTRACT FROM AUTHOR]

Background The Robert-Koch-Institute reports that during the summer holiday period a foreign country is stated as the most likely place of infection for an average of 27 and a maximum of 49% of new SARS-CoV-2 infections in Germany. Methods Cross-sectional study on observational data. In Germany, summer school holidays are coordinated between states and spread out over 13 weeks. Employing a dynamic model with district fixed effects, we analyze the association between these holidays and weekly incidence rates across 401 German districts. Results We find effects of the holiday period of around 45% of the average district incidence rates in Germany during their respective final week of holidays and the 2 weeks after holidays end. Western states tend to experience stronger effects than Eastern states. We also find statistically significant interaction effects of school holidays with per capita taxable income and the share of foreign residents in a district's population. Conclusions Our results suggest that changed behavior during the holiday season accelerated the pandemic and made it considerably more difficult for public health authorities to contain the spread of the virus by means of contact tracing. Germany's public health authorities did not prepare adequately for this acceleration. [ABSTRACT FROM AUTHOR]

Background understanding care-home outbreaks of COVID-19 is a key public health priority in the ongoing pandemic to help protect vulnerable residents. Objective to describe all outbreaks of COVID-19 infection in Scottish care-homes for older people between 01/03/2020 and 31/03/2020, with follow-up to 30/06/2020. Design and setting National linked data cohort analysis of Scottish care-homes for older people. Methods data linkage was used to identify outbreaks of COVID-19 in care-homes. Care-home characteristics associated with the presence of an outbreak were examined using logistic regression. Size of outbreaks was modelled using negative binomial regression. Results 334 (41%) Scottish care-homes for older people experienced an outbreak, with heterogeneity in outbreak size (1–63 cases; median = 6) and duration (1–94 days, median = 31.5 days). Four distinct patterns of outbreak were identified: 'typical' (38% of outbreaks, mean 11.2 cases and 48 days duration), severe (11%, mean 29.7 cases and 60 days), contained (37%, mean 3.5 cases and 13 days) and late-onset (14%, mean 5.4 cases and 17 days). Risk of a COVID-19 outbreak increased with increasing care-home size (for ≥90 beds vs <20, adjusted OR = 55.4, 95% CI 15.0–251.7) and rising community prevalence (OR = 1.2 [1.0–1.4] per 100 cases/100,000 population increase). No routinely available care-home characteristic was associated with outbreak size. Conclusions reducing community prevalence of COVID-19 infection is essential to protect those living in care-homes. More systematic national data collection to understand care-home residents and the homes in which they live is a priority in ensuring we can respond more effectively in future. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), better known as COVID-19, has become a current threat to humanity. The second wave of the SARS-CoV-2 virus has hit many countries, and the confirmed COVID-19 cases are quickly spreading. Therefore, the epidemic is still passing the terrible stage. Having idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) are the risk factors of the COVID-19, but the molecular mechanisms that underlie IPF, COPD, and CVOID-19 are not well understood. Therefore, we implemented transcriptomic analysis to detect common pathways and molecular biomarkers in IPF, COPD, and COVID-19 that help understand the linkage of SARS-CoV-2 to the IPF and COPD patients. Here, three RNA-seq datasets (GSE147507, GSE52463, and GSE57148) from Gene Expression Omnibus (GEO) is employed to detect mutual differentially expressed genes (DEGs) for IPF, and COPD patients with the COVID-19 infection for finding shared pathways and candidate drugs. A total of 65 common DEGs among these three datasets were identified. Various combinatorial statistical methods and bioinformatics tools were used to build the protein–protein interaction (PPI) and then identified Hub genes and essential modules from this PPI network. Moreover, we performed functional analysis under ontologies terms and pathway analysis and found that IPF and COPD have some shared links to the progression of COVID-19 infection. Transcription factors–genes interaction, protein–drug interactions, and DEGs-miRNAs coregulatory network with common DEGs also identified on the datasets. We think that the candidate drugs obtained by this study might be helpful for effective therapeutic in COVID-19. [ABSTRACT FROM AUTHOR]

Aims We investigated the incidence, risk factors, clinical characteristics, and outcomes of pulmonary embolism (PE) in patients with COVID-19 attending emergency departments (EDs), before hospitalization. Methods and Results We retrospectively reviewed all COVID-19 patients diagnosed with PE in 62 Spanish EDs (20% of Spanish EDs, case group) during the first COVID-19 outbreak. COVID-19 patients without PE and non-COVID-19 patients with PE were included as control groups. Adjusted comparisons for baseline characteristics, acute episode characteristics, and outcomes were made between cases and randomly selected controls (1:1 ratio). We identified 368 PE in 74 814 patients with COVID-19 attending EDs (4.92‰). The standardized incidence of PE in the COVID-19 population resulted in 310 per 100 000 person-years, significantly higher than that observed in the non-COVID-19 population [35 per 100 000 person-years; odds ratio (OR) 8.95 for PE in the COVID-19 population, 95% confidence interval (CI) 8.51–9.41]. Several characteristics in COVID-19 patients were independently associated with PE, the strongest being D-dimer >1000 ng/mL, and chest pain (direct association) and chronic heart failure (inverse association). COVID-19 patients with PE differed from non-COVID-19 patients with PE in 16 characteristics, most directly related to COVID-19 infection; remarkably, D-dimer >1000 ng/mL, leg swelling/pain, and PE risk factors were significantly less present. PE in COVID-19 patients affected smaller pulmonary arteries than in non-COVID-19 patients, although right ventricular dysfunction was similar in both groups. In-hospital mortality in cases (16.0%) was similar to COVID-19 patients without PE (16.6%; OR 0.96, 95% CI 0.65–1.42; and 11.4% in a subgroup of COVID-19 patients with PE ruled out by scanner, OR 1.48, 95% CI 0.97–2.27), but higher than in non-COVID-19 patients with PE (6.5%; OR 2.74, 95% CI 1.66–4.51). Adjustment for differences in baseline and acute episode characteristics and sensitivity analysis reported very similar associations. Conclusions PE in COVID-19 patients at ED presentation is unusual (about 0.5%), but incidence is approximately ninefold higher than in the general (non-COVID-19) population. Moreover, risk factors and leg symptoms are less frequent, D-dimer increase is lower and emboli involve smaller pulmonary arteries. While PE probably does not increase the mortality of COVID-19 patients, mortality is higher in COVID-19 than in non-COVID-19 patients with PE. [ABSTRACT FROM AUTHOR]

Background: Early detection of SARS-CoV-2 circulation is imperative to inform local public health response. However, it has been hindered by limited access to SARS-CoV-2 diagnostic tests and testing infrastructure. In regions with limited testing capacity, routinely collected health data might be leveraged to identify geographical locales experiencing higher than expected rates of COVID-19-associated symptoms for more specific testing activities.Methods: We developed syndromic surveillance tools to analyse aggregated health facility data on COVID-19-related indicators in seven low- and middle-income countries (LMICs), including Liberia. We used time series models to estimate the expected monthly counts and 95% prediction intervals based on 4 years of previous data. Here, we detail and provide resources for our data preparation procedures, modelling approach and data visualisation tools with application to Liberia.Results: To demonstrate the utility of these methods, we present syndromic surveillance results for acute respiratory infections (ARI) at health facilities in Liberia during the initial months of the COVID-19 pandemic (January through August 2020). For each month, we estimated the deviation between the expected and observed number of ARI cases for 325 health facilities and 15 counties to identify potential areas of SARS-CoV-2 circulation.Conclusions: Syndromic surveillance can be used to monitor health facility catchment areas for spikes in specific symptoms which may indicate SARS-CoV-2 circulation. The developed methods coupled with the existing infrastructure for routine health data systems can be leveraged to monitor a variety of indicators and other infectious diseases with epidemic potential. [ABSTRACT FROM AUTHOR]

The global coronavirus disease 2019 pandemic has raised significant concerns of developing rapid, broad strategies to protect the vulnerable population and prevent morbidity and mortality. However, even with an aggressive approach, controlling the pandemic has been challenging, with concerns of emerging variants that likely escape vaccines, nonadherence of social distancing/preventive measures by the public, and challenges in rapid implementation of a global vaccination program that involves mass production, distribution, and execution. In this review, we revisit the utilization of attenuated vaccinations, such as the oral polio vaccine, which are safe, easy to administer, and likely provide cross-protection against respiratory pathogens. We discuss the rationale and data supporting its use and detail description of available vaccines that could be repurposed for curtailing the pandemic. [ABSTRACT FROM AUTHOR]