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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]

In high-income countries that were first to roll out coronavirus disease 2019 (COVID-19) vaccines, older adults have thus far usually been prioritized for these vaccines over younger adults. Age-based priority primarily resulted from interpreting evidence available at the time, which indicated that vaccinating the elderly first would minimize COVID-19 deaths and hospitalizations. The World Health Organization counsels a similar approach for all countries. This paper argues that some low- and middle-income countries that are short of COVID-19 vaccine doses might be justified in revising this approach and instead prioritizing certain younger persons when allocating current vaccines or future variant-specific vaccines. [ABSTRACT FROM AUTHOR]

Motivated by the varying effectiveness of government intervention policies to contain the COVID-19 pandemic, and the potential positive relationship between ethnolinguistic diversity and social distance, this paper aims to provide empirical evidence on the relationship between ethnolinguistic diversity and the spread of COVID-19. In particular, using global data from 113 developed and developing countries during the early stages of the pandemic (from 31 December 2019 to 8 July 2020), we have found a significant negative effect of ethnolinguistic diversity on the spread of the virus. The result is robust to alternative measures of ethnolinguistic diversity and estimator that addresses endogeneity. Moreover, we also show that the impact of ethnolinguistic diversity on the spread of COVID-19 differs in economies characterized by different levels of democracy, policy stringency on addressing COVID-19 and health expenditure. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has resulted in the diversion of health resources away from routine primary care delivery. This disruption of health services has necessitated new approaches to providing care to ensure continuity.Objectives: To summarize changes to the provision of routine primary care services during the pandemic.Methods: Rapid literature review using PubMed/MEDLINE, SCOPUS, and Cochrane. Eligible studies were based in primary care and described practice-level changes in the provision of routine care in response to COVID-19. Relevant data addressing changes to routine primary care delivery, impact on primary care functions and challenges experienced in adjusting to new approaches to providing care, were obtained from included studies. A narrative summary was guided by Burns et al.'s framework for primary care provision in disasters.Results: Seventeen of 1,699 identified papers were included. Studies reported on telehealth use and public health measures to maintain safe access to routine primary care, including providing COVID-19 screening, and establishing dedicated care pathways for non-COVID and COVID-related issues. Acute and urgent care were prioritized, causing disruptions to chronic disease management and preventive care. Challenges included telehealth use including disparities in access and practical difficulties in assessing patients, personal protective equipment shortages, and financial solvency of medical practices.Conclusions: Substantial disruptions to routine primary care occurred due to the COVID-19 pandemic. Primary care practices' rapid adaptation, often with limited resources and support, demonstrates agility and innovative capacity. Findings underscore the need for timely guidance and support from authorities to optimize the provision of comprehensive routine care during pandemics. [ABSTRACT FROM AUTHOR]

For all health conditions, reliable age-disaggregated data are vital for both epidemiological analysis and monitoring the relative prioritization of different age groups in policy responses. This is especially essential in the case of Coronavirus Disease-2019 (COVID-19), given the strong association between age and case fatality. This paper assesses the availability and quality of age-based data on reported COVID-19 cases and deaths for low- and middle-income countries. It finds that the availability of reliable data which permit specific analyses of older people is largely absent. The paper explores the potential of excess mortality estimates as an alternative metric of the pandemic's effects on older populations. Notwithstanding some technical challenges, this may offer a better approach, especially in countries where cause of death data are unreliable. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic, caused by the coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created an unprecedented threat to public health. The pandemic has been sweeping the globe, impacting more than 200 countries, with more outbreaks still lurking on the horizon. At the time of the writing, no approved drugs or vaccines are available to treat COVID-19 patients, prompting an urgent need to decipher mechanisms underlying the pathogenesis and develop curative treatments. To fight COVID-19, researchers around the world have provided specific tools and molecular information for SARS-CoV-2. These pieces of information can be integrated to aid computational investigations and facilitate clinical research. This paper reviews current knowledge, the current status of drug development and various resources for key steps toward effective treatment of COVID-19, including the phylogenetic characteristics, genomic conservation and interaction data. The final goal of this paper is to provide information that may be utilized in bioinformatics approaches and aid target prioritization and drug repurposing. Several SARS-CoV-2-related tools/databases were reviewed, and a web-portal named OverCOVID (http://bis.zju.edu.cn/overcovid/) is constructed to provide a detailed interpretation of SARS-CoV-2 basics and share a collection of resources that may contribute to therapeutic advances. These information could improve researchers' understanding of SARS-CoV-2 and help to accelerate the development of new antiviral treatments. [ABSTRACT FROM AUTHOR]

More than 50 000 papers have been published about COVID-19 since the beginning of 2020 and several hundred new papers continue to be published every day. This incredible rate of scientific productivity leads to information overload, making it difficult for researchers, clinicians and public health officials to keep up with the latest findings. Automated text mining techniques for searching, reading and summarizing papers are helpful for addressing information overload. In this review, we describe the many resources that have been introduced to support text mining applications over the COVID-19 literature; specifically, we discuss the corpora, modeling resources, systems and shared tasks that have been introduced for COVID-19. We compile a list of 39 systems that provide functionality such as search, discovery, visualization and summarization over the COVID-19 literature. For each system, we provide a qualitative description and assessment of the system's performance, unique data or user interface features and modeling decisions. Many systems focus on search and discovery, though several systems provide novel features, such as the ability to summarize findings over multiple documents or linking between scientific articles and clinical trials. We also describe the public corpora, models and shared tasks that have been introduced to help reduce repeated effort among community members; some of these resources (especially shared tasks) can provide a basis for comparing the performance of different systems. Finally, we summarize promising results and open challenges for text mining the COVID-19 literature. [ABSTRACT FROM AUTHOR]

Introduction The coronavirus pandemic (COVID-19) has affected the functioning and capacity of healthcare systems worldwide. COVID-19 has also disproportionately affected older adults. In the context of COVID-19, decision-making surrounding place of care (PoC) and place of death (PoD) in older adults involves significant new challenges. Aims To explore key factors that influence PoC and PoD decisions in older adults. A secondary aim was to investigate key factors that influence the process and outcome of these decisions in older adults. To apply findings from current evidence to the context of COVID-19. Methods Rapid review of reviews, undertaken using WHO guidance for rapid reviews for the production of actionable evidence. Data extracted was synthesised using narrative synthesis, with thematic analysis and tabulation. Results 10 papers were included for full data extraction. These papers were published between 2005 and 2020. Papers included discussed actual PoD, as well as preferred. Results were divided into papers that explored the process of decision-making, and those that explored decision-making outcomes. Conclusions The process and outcomes of decision-making for older people are affected by many factors—all of which have the potential to influence both patients and caregivers experience of illness and dying. Within the context of COVID-19, such decisions may have to be made rapidly and be reflexive to changing needs of systems and of families and patients. [ABSTRACT FROM AUTHOR]

As coronavirus disease 2019 (COVID-19) spread through the United States in 2020, states began to set up alert systems to inform policy decisions and serve as risk communication tools for the general public. Many of these systems included indicators based on an assessment of trends in numbers of reported cases. However, when cases are indexed by date of disease onset, reporting delays complicate the interpretation of trends. Despite a foundation of statistical literature with which to address this problem, these methods have not been widely applied in practice. In this paper, we develop a Bayesian spatiotemporal nowcasting model for assessing trends in county-level COVID-19 cases in Ohio. We compare the performance of our model with the approach used in Ohio and the approach included in decision support materials from the Centers for Disease Control and Prevention. We demonstrate gains in performance while still retaining interpretability using our model. In addition, we are able to fully account for uncertainty in both the time series of cases and the reporting process. While we cannot eliminate all of the uncertainty in public health surveillance and subsequent decision-making, we must use approaches that embrace these challenges and deliver more accurate and honest assessments to policy-makers. [ABSTRACT FROM AUTHOR]

Global evaluations of response to the COVID-19 pandemic, the Global Clinical Practice (a network of 12,942 clinicians from 151 countries), and the Global Response to Infections Disease have consistently rated the United Arab Emirates (UAE) as one of the most effective medical responses to the COVID-19 pandemic. In parallel, according to the 2020 Edelman Trust Barometer, public trust in the UAE government is 81%—a leading score in the Middle East. While widespread miscommunication rumours, and lack of coordination was observed in the early phases of COVID-19 globally, the UAE case demonstrates a comprehensive positive approach and experience. The research reported in this paper aimed to understand the role of media in the police response in relation to COVID-19 risk management in the UAE. Content analysis of documentary and data sources was conducted from public COVID-19-related meta-data sources. The findings suggest pre-defined conducive legislative and institutional structure, professionalism of media and police, and collaborative approaches among implementing agencies contributed to the success of the early phase COVID-19 risk management in the UAE. This research contributes to the body of knowledge in pandemic and infodemic risk management through analysis of the UAE experience. [ABSTRACT FROM AUTHOR]

Over the last 25 years, marijuana laws have been changing throughout the USA. California started legalizing medicinal marijuana in 1996 and has since continued to relax laws. Compared to Washington and Colorado, there are little data on how the changing laws have affected the cannabinoid detection rate in California. This paper looks at the prevalence of five cannabinoids (Δ9-tetrahydrocannabinol (THC), 11-hydroxy-tetrahydrocannabinol (hydroxy-THC), 11-nor-9-carboxy-tetrahydrocannabinol (carboxy-THC), cannabinol and cannabidiol) in Orange County, CA, from 2016 to 2019. From 2016 to 2017, after legalizing recreational marijuana, there was an increase in the presence of THC, carboxy-THC and hydroxy-THC in postmortem and major crime cases, consisting mostly of sexual assaults. However, driving under the influence of drugs (DUID) saw a slight decrease. In 2018, when shops could be licensed to sell marijuana to anyone over 21 years old, there was an increase seen in all five cannabinoids for DUID and postmortem cases. The age group from 21 to 30 years showed the most prevalent cannabinoid use in all case types for all years except in major crime cases in 2019, where <21 year-old age group was the most prevalent. Surprisingly, the >50-year-old group in death investigation cases was a close second in prevalence in all years, which differs from DUID and major crime cases. [ABSTRACT FROM AUTHOR]

Predicting protein properties from amino acid sequences is an important problem in biology and pharmacology. Protein–protein interactions among SARS-CoV-2 spike protein, human receptors and antibodies are key determinants of the potency of this virus and its ability to evade the human immune response. As a rapidly evolving virus, SARS-CoV-2 has already developed into many variants with considerable variation in virulence among these variants. Utilizing the proteomic data of SARS-CoV-2 to predict its viral characteristics will, therefore, greatly aid in disease control and prevention. In this paper, we review and compare recent successful prediction methods based on long short-term memory (LSTM), transformer, convolutional neural network (CNN) and a similarity-based topological regression (TR) model and offer recommendations about appropriate predictive methodology depending on the similarity between training and test datasets. We compare the effectiveness of these models in predicting the binding affinity and expression of SARS-CoV-2 spike protein sequences. We also explore how effective these predictive methods are when trained on laboratory-created data and are tasked with predicting the binding affinity of the in-the-wild SARS-CoV-2 spike protein sequences obtained from the GISAID datasets. We observe that TR is a better method when the sample size is small and test protein sequences are sufficiently similar to the training sequence. However, when the training sample size is sufficiently large and prediction requires extrapolation, LSTM embedding and CNN-based predictive model show superior performance. [ABSTRACT FROM AUTHOR]

Background The dissemination of scientific data on coronavirus disease 2019 (COVID-19) continually builds but, in April 2020, could not keep up with the spread of the disease. Through technology, surgeons in Italy and the UK, representing both peak and pre-peak infective time zones, were able to communicate so that the urgent lessons on the huge expected demands of care learned in Italy could be brought to the UK in advance. This paper specifically discusses the issues related to paediatric surgery, currently under-reported in the literature. Methods The aim of this paper is to conjoin experience from the field to provide a framework for a safe assessment and treatment of paediatric patients by adopting a systemic approach aimed at reducing the risk of contamination. We reviewed the processes and good practices that were undertaken in contexts of emergency such as in Italy and the UK and then adapted them within the Systems Engineering Initiative for Patient Safety (SEIPS) framework to provide an assessment of how to reorganize the services in order to cope with an unexpected situation. The SEIPS model is the adopted theoretical framework, which allows to analyse the system in its main components with a human factors and ergonomics (HFE) perspective. Results The results introduce some of the good practices and recommendations developed during the emergency in the surgical scenario with a focus on the paediatric patients. They represent the lessons learned from the combination of the little existing evidence of literature and the experience from surgical teams who responded in an impromptu and unrehearsed way. Conclusions Lessons learned from the frontline 'on the fly' during COVID-19 emergency should be consolidated and taken into the future. In order to prepare proactively for the next phases and get ahead of the curve of these hospital accesses, there is a need for a risk assessment of the new clinical pathways with a multidisciplinary approach centred on HFE with the adoption of the SEIPS model and an involvement of all the surgical teams. [ABSTRACT FROM AUTHOR]

Background: In the context of the COVID-19 emergency, the concern has been raised that people may compensate the reduction in risk ensured by mask use with an increase in risk induced by lower adherence to physical distancing rules.Purpose: The paper investigates if people compensate risk in this manner when their interaction partner wears a face mask, examining if risk compensation further depends on gender, signaled social status and perceived race.Methods: An experiment was conducted in two waves (June, n = 1396 and September 2020, n = 1326) in front of the traffic lights of four busy roads in Paris. A confederate asked a randomly selected pedestrian for directions following a script and keeping the recommended distance. Confederates were locally recognizable as Blacks or Whites and alternatively presented themselves with a costume indicative of high or low social status. An observer recorded whether the pedestrian kept the recommended distance.Results: Both in June and September, men are less likely to comply with the distancing rule when the confederate wears the face mask, and particularly so when the confederate signals high status. When the confederate wears the mask, female pedestrians observe less the one-meter rule in September than in June.Conclusions: Men's risk compensatory behavior is constant over time. In contrast, women's depends on the time period. [ABSTRACT FROM AUTHOR]

The current COVID-19 pandemic confines people to their homes, disrupting the fragile social fabric of deprived neighbourhoods and citizen's participation options. In deprived neighbourhoods, community engagement is central in building community resilience, an important resource for health and a prerequisite for effective health promotion programmes. It provides access to vulnerable groups and helps understand experiences, assets, needs and problems of citizens. Most importantly, community activities, including social support, primary care or improving urban space, enhance health through empowerment, strengthened social networks, mutual respect and providing a sense of purpose and meaning. In the context of inequalities associated with COVID-19, these aspects are crucial for citizens of deprived neighbourhoods who often feel their needs and priorities are ignored. In this perspectives paper, illustrated by a varied overview of community actions in the UK and The Netherlands, we demonstrate how citizens, communities and organizations may build resilience and community power. Based on in-depth discussion among the authors we distilled six features of community actions: increase in mutual aid and neighbourhood ties, the central role of community-based organizations (CBOs), changing patterns of volunteering, use of digital media and health promotion opportunities. We argue that in order to enable and sustain resilient and confident, 'disaster-proof', communities, areas which merit investment include supporting active citizens, new (digital) ways of community engagement, transforming formal organizations, alignment with the (local) context and applying knowledge in the field of health promotion in new ways, focussing on learning and co-creation with citizen initiatives. [ABSTRACT FROM AUTHOR]

In this paper, we propose and analyse a compartmental model of COVID-19 to predict and control the outbreak. We first formulate a comprehensive mathematical model for the dynamical transmission of COVID-19 in the context of sub-Saharan Africa. We provide the basic properties of the model and compute the basic reproduction number |$\mathcal {R}_0$| when the parameter values are constant. After, assuming continuous measurement of the weekly number of newly COVID-19 detected cases, newly deceased individuals and newly recovered individuals, the Ensemble of Kalman filter (EnKf) approach is used to estimate the unmeasured variables and unknown parameters, which are assumed to be time-dependent using real data of COVID-19. We calibrated the proposed model to fit the weekly data in Cameroon and Gabon before, during and after the lockdown. We present the forecasts of the current pandemic in these countries using the estimated parameter values and the estimated variables as initial conditions. During the estimation period, our findings suggest that |$\mathcal {R}_0 \approx 1.8377 $| in Cameroon, while |$\mathcal {R}_0 \approx 1.0379$| in Gabon meaning that the disease will not die out without any control measures in theses countries. Also, the number of undetected cases remains high in both countries, which could be the source of the new wave of COVID-19 pandemic. Short-term predictions firstly show that one can use the EnKf to predict the COVID-19 in Sub-Saharan Africa and that the second vague of the COVID-19 pandemic will still increase in the future in Gabon and in Cameroon. A comparison between the basic reproduction number from human individuals |$\mathcal {R}_{0h}$| and from the SARS-CoV-2 in the environment |$\mathcal {R}_{0v}$| has been done in Cameroon and Gabon. A comparative study during the estimation period shows that the transmissions from the free SARS-CoV-2 in the environment is greater than that from the infected individuals in Cameroon with |$\mathcal {R}_{0h}$| = 0.05721 and |$\mathcal {R}_{0v}$| = 1.78051. This imply that Cameroonian apply distancing measures between individual more than with the free SARS-CoV-2 in the environment. But, the opposite is observed in Gabon with |$\mathcal {R}_{0h}$| = 0.63899 and |$\mathcal {R}_{0v}$| = 0.39894. So, it is important to increase the awareness campaigns to reduce contacts from individual to individual in Gabon. However, long-term predictions reveal that the COVID-19 detected cases will play an important role in the spread of the disease. Further, we found that there is a necessity to increase timely the surveillance by using an awareness program and a detection process, and the eradication of the pandemic is highly dependent on the control measures taken by each government. [ABSTRACT FROM AUTHOR]

In this paper, three stochastic mathematical models are developed for the spread of the coronavirus disease (COVID-19). These models take into account the known special characteristics of this disease such as the existence of infectious undetected cases and the different social and infectiousness conditions of infected people. In particular, they include a novel approach that considers the social structure, the fraction of detected cases over the real total infected cases, the influx of undetected infected people from outside the borders, as well as contact-tracing and quarantine period for travellers. Two of these models are discrete time–discrete state space models (one is simplified and the other is complete) while the third one is a continuous time–continuous state space stochastic integro-differential model obtained by a formal passing to the limit from the proposed simplified discrete model. From a numerical point of view, the particular case of Lebanon has been studied and its reported data have been used to estimate the complete discrete model parameters, which can be of interest in estimating the spread of COVID-19 in other countries. The obtained simulation results have shown a good agreement with the reported data. Moreover, a parameters' analysis is presented in order to better understand the role of some of the parameters. This may help policy makers in deciding on different social distancing measures. [ABSTRACT FROM AUTHOR]

Understanding the T-cell response to SARS-CoV-2 is key in patients who lack antibody production. We demonstrate the applicability of a functional assay to measure the T-cell response in a cohort of patients with immunodeficiency. T-cell responses to COVID are now linked to improved outcomes. This paper demonstrates a method to robustly test responses for routine diagnostic use in healthy controls and those unable to make a detectable antibody response due to underlying immune deficiency (primary or acquired). [ABSTRACT FROM AUTHOR]

Objective Although telehealth has become a central component of medical care in response to the coronavirus disease 2019 (COVID-19) pandemic, comprehensive pediatric neuropsychological assessment over virtual platforms lacks empirical efficacy. This paper presents: a) the results of a quality improvement project examining the feasibility of in-person evaluation in the context of safety measures that alter test standardization, b) the impact such changes had upon neuropsychological test scores, and c) how using a hybrid model of clinical service delivery affected access to care. Method We compared demographic and outcome variables between patients seen during the pandemic (N  = 87) to a group of patients seen in our service immediately prior to COVID-19 (N  = 87). A subset of those patients were case-matched for age and diagnosis (N  = 39 per group). Children seen for neuropsychological re-evaluation during the pandemic (N  = 10) were examined using pairwise comparison. Results Groups did not differ on age, sex, or FSIQ. Despite changes to standardized administration, no group differences were found for any selected neuropsychological test variables in the larger sample or subsamples. In fact, all variables were moderately to highly correlated in the re-evaluation subgroup. The hybrid model expedited feedback sessions and increased face-to-face (telehealth) feedbacks. Conclusions A hybrid model incorporating modified in-person testing and intake and feedback encounters via telehealth may be a feasible and effective way to provide pediatric neuropsychological services. These preliminary findings suggest such novel aspects of neuropsychological evaluation could represent an improvement over pre-COVID models, especially in rural settings. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) has been a global disaster, with over 746,312 confirmed cases and still counting in Indonesia, especially Jakarta, which has about 50 per cent asymptomatic confirmed cases. This paper aims to investigate the persistent factors of COVID-19 diagnosis using four scenarios of asymptomatic inclusion. We use Bayesian Logistic Regression to identify the factors of COVID-19 positivity, which can address issues in the traditional approach such as overfitting and uncertainty. This study discovers three main findings: (1) COVID-19 can infect people regardless of age; (2) Among twelve symptoms of coronavirus (COVID-19), five symptoms increase the COVID-19 likelihood, and two symptoms decrease the possibility of COVID-19 infection; and (3) From an epidemiological perspective, the contact history rises the probability of COVID-19, while healthcare workers and people who did travel are less likely to become infected from COVID-19. Therefore given this study, it is essential to be attentive to the people who have the symptoms and contact history. Surprisingly, health care workers and travelers who apply health protocols strictly according to the rules have a low risk of COVID19 infection. [ABSTRACT FROM AUTHOR]

Background the COVID-19 pandemic disproportionately affected care home residents' and staffs' access to health care and advice. Health and social care professionals adapted rapidly to using video consultation (videoconferencing) technology without guidance. We sought to identify enablers and barriers to their use in supporting care home residents and staff. Methods a scoping review of the evidence on remote consultations between healthcare services and care homes. Interviews with English health and social care professionals about their experiences during the pandemic. Findings were synthesised using the non-adoption, abandonment, scale-up, spread, sustainability framework. Results 18 papers were included in the review. Twelve interviews were completed. Documented enablers and barriers affecting the uptake and use of technology (e.g. reliable internet; reduced travelling) resonated with participants. Interviews demonstrated rapid, widespread technology adoption overcame barriers anticipated from the literature, often strengthening working relationships with care homes. Novel implementation issues included using multiple platforms and how resident data were managed. Healthcare professionals had access to more bespoke digital platforms than their social care counterparts. Participants alternated between platforms depending on individual context or what their organisation supported. All participants supported ongoing use of technologies to supplement in-person consultations. Conclusions the evidence on what needs to be in place for video consultations to work with care homes was partly confirmed. The pandemic context demolished many documented barriers to engagement and provided reassurance that residents' assessments were possible. It exposed the need to study further differing resident requirements and investment in digital infrastructure for adequate information management between organisations. [ABSTRACT FROM AUTHOR]

We read with interest the paper by Lee I et al i .[1] in which they describe widespread microvascular damage marked by endothelial cell damage/activation, microthrombi, complement activation, and disruption of the blood-brain barrier (BBB). Endothelial cell damage is the central part of COVID-19 and a mouse model induced by injection of the S1 subunit of the spike protein. [Extracted from the article]

Introduction the COVID-19 pandemic poses a high risk to older people. The aim of this article is to provide a rapid overview of the COVID-19 literature, with a specific focus on older adults. We frame our findings within an overview of the disease and have also evaluated the inclusion of older people within forthcoming clinical trials. Methods we searched PubMed and bioRxiv/medRxiv to identify English language papers describing the testing, treatment and prognosis of COVID-19. PubMed and bioRxiv/medRxiv searches took place on 20 and 24 March 2020, respectively. Results screening of over 1,100 peer-reviewed and pre-print papers yielded n  = 22 on COVID-19 testing, n  = 15 on treatment and n  = 13 on prognosis. Viral polymerase chain reaction (PCR) and serology are the mainstays of testing, but a positive diagnosis may be increasingly supported by radiological findings. The current evidence for the effectiveness of antiviral, corticosteroid and immunotherapies is inconclusive, although trial data are largely based on younger people. In addition to age, male gender and comorbidities, specific laboratory and radiology findings are important prognostic factors. Evidence suggests that social distancing policies could have important negative consequences, particularly if in place for an extended period. Conclusion given the established association between increasing age and poor prognosis in COVID-19, we anticipate that this rapid review of the current and emergent evidence might form a basis on which future work can be established. Exclusion of older people, particularly those with comorbidities, from clinical trials is well recognised and is potentially being perpetuated in the field of current COVID-19 research. [ABSTRACT FROM AUTHOR]

During the WHO-GloPID COVID-19 Global Research and Innovation Forum meeting held in Geneva on the 11th and 12th of February 2020 a number of different ethical concepts were used. This paper briefly states what a number of these concepts mean and how they might be applied to discussions about research during the COVID-19 pandemic and related outbreaks. This paper does not seek to be exhaustive and other ethical concepts are, of course, relevant and important. [ABSTRACT FROM AUTHOR]

The technological innovation of wind power is crucial to energy security and energy structure transformation. The Chinese government has been committed to improving the innovation of the wind power industry for decades. Although academic researchers and wind power policymakers have been widely concerned about the absolute score of innovation output, concentrating on innovation output in isolation is ultimately insufficient. This article goes beyond bean counting and evaluates the innovation of the Chinese wind power industry from the perspective of relative efficiency, and then assesses the efforts of the government to improve innovation efficiency (IE). The study uses the data of 105 wind power listed enterprises in China over the period 2008–2019. According to the recommendation made by the existing papers, IE is defined as the capability to generate innovation outputs per unit of R&D investment. Regression analysis is applied to test the policy effect. During 2008–2019, the average value of IE of Chinese wind power industry is 0.196. The IE of wind power enterprises in eastern China (0.265) is higher than that in central and western China (0.169). Besides, the regression results indicate that all categories of wind power innovation policies contribute to the IE of wind power industry in China. Furthermore, the innovation policies issued by the departments of the State Council significantly improve the IE of wind power industry, but the innovation policies from the National People's Congress and the State Council have no significant impacts on IE. [ABSTRACT FROM AUTHOR]

Pneumonia, especially corona virus disease 2019 (COVID-19), can lead to serious acute lung injury, acute respiratory distress syndrome, multiple organ failure and even death. Thus it is an urgent task for developing high-efficiency, low-toxicity and targeted drugs according to pathogenesis of coronavirus. In this paper, a novel disease-related compound identification model–based capsule network (CapsNet) is proposed. According to pneumonia-related keywords, the prescriptions and active components related to the pharmacological mechanism of disease are collected and extracted in order to construct training set. The features of each component are extracted as the input layer of capsule network. CapsNet is trained and utilized to identify the pneumonia-related compounds in Qingre Jiedu injection. The experiment results show that CapsNet can identify disease-related compounds more accurately than SVM, RF, gcForest and forgeNet. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Chemosensory scientists have been skeptical that reports of COVID-19 taste loss are genuine, in part because before COVID-19 taste loss was rare and often confused with smell loss. Therefore, to establish the predicted prevalence rate of taste loss in COVID-19 patients, we conducted a systematic review and meta-analysis of 376 papers published in 2020–2021, with 241 meeting all inclusion criteria. Drawing on previous studies and guided by early meta-analyses, we explored how methodological differences (direct vs. self-report measures) may affect these estimates. We hypothesized that direct measures of taste are at least as sensitive as those obtained by self-report and that the preponderance of evidence confirms taste loss is a symptom of COVID-19. The meta-analysis showed that, among 138,897 COVID-19-positive patients, 39.2% reported taste dysfunction (95% confidence interval: 35.34%–43.12%), and the prevalence estimates were slightly but not significantly higher from studies using direct (n = 18) versus self-report (n = 223) methodologies (Q = 0.57, df = 1, P = 0.45). Generally, males reported lower rates of taste loss than did females, and taste loss was highest among middle-aged adults. Thus, taste loss is likely a bona fide symptom of COVID-19, meriting further research into the most appropriate direct methods to measure it and its underlying mechanisms. [ABSTRACT FROM AUTHOR]

Background vaccination uptake in the UK and increased care home testing are likely affecting care home visitation. With scant scientific evidence to date, the aim of this longitudinal qualitative study was to explore the impact of both (vaccination and testing) on the conduct and experiences of care home visits. Methods family carers of care home residents with dementia and care home staff from across the UK took part in baseline (October/November 2020) and follow-up interviews (March 2021). Public advisers were involved in all elements of the research. Data were analysed using thematic analysis. Results across 62 baseline and follow-up interviews with family carers (n  = 26; 11) and care home staff (n  = 16; 9), five core themes were developed: delayed and inconsistent offers of face-to-face visits; procedures and facilitation of visits; variable uptake of the COVID-19 vaccine; misinformation, education and free choice; frustration and anger among family carers. The variable uptake in staff, compared to family carers, was a key factor seemingly influencing visitation, with a lack of clear guidance leading care homes to implement infection control measures and visitation rights differently. Conclusions we make five recommendations in this paper to enable improved care home visitation in the ongoing, and in future, pandemics. Visits need to be enabled and any changes to visiting rights must be used as a last resort, reviewed regularly in consultation with residents and carers and restored as soon as possible as a top priority, whilst more education needs to be provided surrounding vaccination for care home staff. [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]

Community engagement is crucial for controlling disease outbreak and mitigating natural and industrial disasters. The COVID-19 pandemic has reconfirmed the need to elevate community engagement to build equity, trust and sustained action in future health promotion preparedness strategies. Using the health promotion strategy of strengthening community action enhances the opportunity for better outcomes. There is, therefore, a need to improve our understanding of community engagement practices during crises, scale-up good community engagement initiatives, and improve and sustain people-centered approaches to emergency responses. This paper presents five case studies from the United States, Singapore, Sierra Leone, Kenya and South Africa that demonstrate the potential strengths that can be nurtured to build resilience in local communities to help mitigate the impact of disasters and emergencies. The case studies highlight the importance of co-developing relevant education and communication strategies, amplifying the role of community leaders, empowering community members to achieve shared goals, assessing and adapting to changing contexts, pre-planning and readiness for future emergencies and acknowledgement of historic context. [ABSTRACT FROM AUTHOR]

Background We aimed to review the evidence from studies relating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) culture with the results of reverse-transcription polymerase chain reaction (RT-PCR) and other variables that may influence the interpretation of the test, such as time from symptom onset. Methods We searched LitCovid, medRxiv, Google Scholar, and the World Health Organization coronavirus disease 2019 (COVID-19) database for COVID-19 up to 10 September 2020. We included studies attempting to culture or observe SARS-CoV-2 in specimens with RT-PCR positivity. Studies were dual-extracted and the data summarized narratively by specimen type. Where necessary, we contacted corresponding authors of included papers for additional information. We assessed quality using a modified Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) risk-of-bias tool. Results We included 29 studies reporting attempts at culturing, or observing tissue infection by, SARS-CoV-2 in sputum, nasopharyngeal or oropharyngeal, urine, stool, blood, and environmental specimens. The quality of the studies was moderate with lack of standardized reporting. The data suggest a relationship between the time from onset of symptom to the timing of the specimen test, cycle threshold (Ct), and symptom severity. Twelve studies reported that Ct values were significantly lower and log copies higher in specimens producing live virus culture. Two studies reported that the odds of live virus culture were reduced by approximately 33% for every 1-unit increase in Ct. Six of 8 studies reported detectable RNA for >14 days, but infectious potential declined after day 8 even among cases with ongoing high viral loads. Four studies reported viral culture from stool specimens. Conclusions Complete live viruses are necessary for transmission, not the fragments identified by PCR. Prospective routine testing of reference and culture specimens and their relationship to symptoms, signs, and patient co-factors should be used to define the reliability of PCR for assessing infectious potential. Those with high Ct are unlikely to have infectious potential. [ABSTRACT FROM AUTHOR]

Policy responses to coronavirus disease 2019 (COVID-19), particularly those related to nonpharmaceutical interventions, are unprecedented in scale and scope. However, evaluations of policy impacts require a complex combination of circumstance, study design, data, statistics, and analysis. Beyond the issues that are faced for any policy, evaluation of COVID-19 policies is complicated by additional challenges related to infectious disease dynamics and a multiplicity of interventions. The methods needed for policy-level impact evaluation are not often used or taught in epidemiology, and they differ in important ways that may not be obvious. Methodological complications of policy evaluations can make it difficult for decision-makers and researchers to synthesize and evaluate the strength of the evidence in COVID-19 health policy papers. Here we 1) introduce the basic suite of policy-impact evaluation designs for observational data, including cross-sectional analyses, pre-/post- analyses, interrupted time-series analysis, and difference-in-differences analysis; 2) demonstrate key ways in which the requirements and assumptions underlying these designs are often violated in the context of COVID-19; and 3) provide decision-makers and reviewers with a conceptual and graphical guide to identifying these key violations. Our overall goal is to help epidemiologists, policy-makers, journal editors, journalists, researchers, and other research consumers understand and weigh the strengths and limitations of evidence. [ABSTRACT FROM AUTHOR]

The psychological and sexual health of different populations are negatively affected during the coronavirus disease 2019 (COVID-19) pandemic. However, little is known about psychological distress and erectile function of male recovered patients with COVID-19 in the long term. We aimed to evaluate psychological distress and erectile function of male recovered patients with COVID-19 in the mid-to-long terms. We recruited 67 eligible male recovered patients with COVID-19 and followed them up twice within approximately 6 months of recovery time. The psychological distress and erectile function were assessed by validated Chinese version of paper questionnaires. The primary outcomes were Symptom Checklist 90 questionnaire for psychological distress and International Index of Erectile Function-5 for erectile function. In the first visit, COVID-19 patients with a median recovery time of 80 days mainly presented the following positive symptoms: Obsessive-Compulsive, additional items (ADD), Hostility, Interpersonal Sensitivity, Depression, and Somatization; while the dimension scores in Somatization, Anxiety, ADD, and Phobia were higher than Chinese male norms. Besides, the prevalence of erectile dysfunction (ED) in the first-visit patients was significantly higher than Chinese controls. In the second visit, the primary psychological symptoms of COVID-19 patients with a median recovery time of 174 days were Obsessive-Compulsive, ADD, Interpersonal Sensitivity, and Hostility, while all dimensions scores of Symptom Checklist 90 were lower than Chinese male norms. Moreover, second-visit patients had no significant difference with Chinese controls in ED prevalence. In addition, it suggested that GSI was the independent risk factor for ED in the regression analysis for the first-visit patients. The study showed the changes of psychological symptoms and erectile function in COVID-19 recovered patients, and provided reference on whether psychological and sexual supports are needed after a period of recovery. To our knowledge, it is the first study to comprehensively evaluate the psychological distress and erectile function of COVID-19 recovered patients in the mid-to-long terms. The main limitations were the low number of analyzed participants, and the psychological distress and erectile function of healthy Chinese men over the same period were not evaluated, and the psychological and sexual related data of participants prior to COVID-19 were not available. Additionally, there was a selection bias in comparing COVID-19 patients with healthy controls. With less impact of COVID-19 event, the impaired erectile function and psychological distress improved in COVID-19 recovered patients with a recovery time of nearly half a year. Hu B, Ruan Y, Liu K, et al. A Mid-to-Long Term Comprehensive Evaluation of Psychological Distress and Erectile Function in COVID-19 Recovered Patients. J Sex Med 2021;18:1863–1871. [ABSTRACT FROM AUTHOR]

Single-cell RNA sequencing has enabled to capture the gene activities at single-cell resolution, thus allowing reconstruction of cell-type-specific gene regulatory networks (GRNs). The available algorithms for reconstructing GRNs are commonly designed for bulk RNA-seq data, and few of them are applicable to analyze scRNA-seq data by dealing with the dropout events and cellular heterogeneity. In this paper, we represent the joint gene expression distribution of a gene pair as an image and propose a novel supervised deep neural network called DeepDRIM which utilizes the image of the target TF-gene pair and the ones of the potential neighbors to reconstruct GRN from scRNA-seq data. Due to the consideration of TF-gene pair's neighborhood context, DeepDRIM can effectively eliminate the false positives caused by transitive gene–gene interactions. We compared DeepDRIM with nine GRN reconstruction algorithms designed for either bulk or single-cell RNA-seq data. It achieves evidently better performance for the scRNA-seq data collected from eight cell lines. The simulated data show that DeepDRIM is robust to the dropout rate, the cell number and the size of the training data. We further applied DeepDRIM to the scRNA-seq gene expression of B cells from the bronchoalveolar lavage fluid of the patients with mild and severe coronavirus disease 2019. We focused on the cell-type-specific GRN alteration and observed targets of TFs that were differentially expressed between the two statuses to be enriched in lysosome, apoptosis, response to decreased oxygen level and microtubule, which had been proved to be associated with coronavirus infection. [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]

Two thousand nineteen novel coronavirus SARS-CoV-2, the pathogen of COVID-19, has caused a catastrophic pandemic, which has a profound and widespread impact on human lives and social economy globally. However, the molecular perturbations induced by the SARS-CoV-2 infection remain unknown. In this paper, from the perspective of omnigenic, we analyze the properties of the neighborhood perturbed by SARS-CoV-2 in the human interactome and disclose the peripheral and core regions of virus-host network (VHN). We find that the virus-host proteins (VHPs) form a significantly connected VHN, among which highly perturbed proteins aggregate into an observable core region. The non-core region of VHN forms a large scale but relatively low perturbed periphery. We further validate that the periphery is non-negligible and conducive to identifying comorbidities and detecting drug repurposing candidates for COVID-19. We particularly put forward a flower model for COVID-19, SARS and H1N1 based on their peripheral regions, and the flower model shows more correlations between COVID-19 and other two similar diseases in common functional pathways and candidate drugs. Overall, our periphery-core pattern can not only offer insights into interconnectivity of SARS-CoV-2 VHPs but also facilitate the research on therapeutic drugs. [ABSTRACT FROM AUTHOR]

Background The COVID-19 outbreak is increasing and spreading rapidly globally, with over 20 million cases and 800, 000 thousand deaths reported in 216 countries as of 28th August 2020. Since the report of the index case in Nigeria in February 2020 by the Nigeria Center for Disease Control (NCDC), daily records of confirmed cases have been reported in all states in the country. On 3rd April 2020, an outbreak of Coronavirus disease-2019 (COVID-19) was confirmed in Ondo State, Southwest Nigeria. Field investigations were conducted by the State Ministry of Health (MoH) to identify and confirm additional cases. This paper provides the outcome of the epidemiological investigation of the outbreak to further guide outbreak response activities. Methods Outbreak settings Ondo State is in the South-West Zone of Nigeria with her capital at Akure. The State is situated between longitudes 40 151E and 60 001E of the Greenwich median and latitudes 50 451N and 70 451 N, which are to the North of the equator in the Southwestern geopolitical zones of the country. Field Investigation The investigation was conducted as part of outbreak control and response measures hence permission to conduct the study was obtained from the Ondo State Ministry of Health (OSMoH). Following an alert from clinicians at a government-owned Hospital, Akure, Ondo State on 30 March 2020, the index case of COVID-19, a 34-year-old male with recent travel history to India was investigated. He arrived at Ondo State on 21st March 2020 and presented at the hospital with cough, sore throat and running nose with the onset of symptoms on 23rd March 2020. The State public health emergency Rapid Response Team (RRT) comprising of Commissioner for Health, State Epidemiologist, State and LGA surveillance officers, and health development partners in the state visited the hospital to investigate and implement public health response. Nasopharygeal and oropharyngeal samples were collected and tested for COVID-19, and returned positive from the national reference laboratory on the 3rd of April 2020. Operational definitions During the onset of the outbreak, three categories of case definitions for COVID-19 were used to guide the outbreak investigations according to the Nigeria Center for Diseases Control (NCDC) guidelines. Suspect case: (1) This is a patient with acute respiratory illness (fever and at least one sign/ symptom of respiratory disease (e.g. cough, shortness of breath) and a history of travel to or residence in a country/area or territory reporting local transmission of COVID-19 disease during the 14 days prior to symptom onset; (2) or a patient/health care worker with any acute respiratory illness and has been in contact with a confirmed COVID-19 case in the last 14 days prior to the onset of symptoms; (3) or a patient with a severe acute respiratory infection (fever and at least one sign/symptom of respiratory disease (e.g. cough, shortness of breath) and requiring hospitalization and with no other aetiology that fully explains the clinical presentation; (4) or a case for whom testing for COVID-19 is inconclusive. Confirmed case: A person with laboratory confirmation of COVID-19 infection, irrespective of clinical signs and symptoms. Probable case: Any suspected case for whom testing for COVID-19 is indeterminate test result or for whom testing was positive on a pan-coronavirus assay Data analysis The State COVID-19 line-list and case investigation forms of all COVID-19 cases from 19th March to 9th August 2020 were retrieved from the state disease surveillance unit, information on key variables were extracted and exported into SPSS version 20 and analyzed. Descriptive statistics such as frequency table, mean (standard deviation) and charts were used to describe key variables including LGA, age, sex, occupation and education and clinical conditions of cases. The week of report of cases and outcomes were used to generate the epidemic curve. The Chi-square test was used to compare categorical variables including the socio-demographic characteristics, clinical condition and outcome of cases. Two-sided P-values <0.05 were considered statistically significant. Results Socio-demographic characteristics of cases A total of 4353 suspected cases were reported and tested for COVID-19, of which 1316 COVID-19 cases were confirmed, with a case fatality rate of 2.2% recorded in 7 of the 17 Local Government Areas that reported at least a confirmed case (Figure 1). Most of the confirmed cases (1169; 88.8%), resides in urban areas (LGAs) (Table 1). Majority [1110 (84.3%)] were within the age group 20 to 59 years, with a mean age of 37.8 ±14.8 years. Males (713; 54.2%) were more affected compare to females (603; 45.8). More than three quarters (1009; 76.7%) of the cases had a tertiary level of education. Health care workers (404; 30.7%) were most affected compared to other professionals as shown in Table 1. 1170 Figure 1: Open in new tab Download slide Distribution of suspected and confirmed COVID-19 cases in Ondo state, March to August 2020 1170 Figure 1: Open in new tab Download slide Distribution of suspected and confirmed COVID-19 cases in Ondo state, March to August 2020 1170 Table 1: Socio-demographic characteristics of respondents N = 1316 Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Open in new tab 1170 Table 1: Socio-demographic characteristics of respondents N = 1316 Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Open in new tab Admission and clinical conditions of confirmed cases From Table 2 , 88 (6.7%) of the confirmed cases were admitted as inpatient during investigation, while 325 (24.7%) were symptomatic. The first symptom reported by cases were as follows; cough (98; 30.2%), fever (74; 22.8%), headache (30; 9.2%), runny nose (39; 12.0%), sore throat (24; 7.4%) and difficulty in breathing (15; 4.6%). 1170 Table 2: Admission and clinical conditions of confirmed cases.  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2 .  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2  Others= abdominal pain; chills/sweats; joint pain; inability to walk; Nausea Open in new tab 1170 Table 2: Admission and clinical conditions of confirmed cases.  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2 .  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2  Others= abdominal pain; chills/sweats; joint pain; inability to walk; Nausea Open in new tab Figure 2 described the epidemic curve of the outbreak from March to August 2020. The index case was confirmed on April 4, 2020. Thereafter, there was a surge in the number of confirmed COVID-19 cases with the outbreak reaching its peak on July 2, 2020. Afterwards, fluctuations in the number of cases were observed before a steady decline was recorded between August 3, 2020 and August 9, 2020. 1170 Figure 2 Open in new tab Download slide Epi-Curve of confirmed cases of COVID-19 in Ondo State, March to August 2020 1170 Figure 2 Open in new tab Download slide Epi-Curve of confirmed cases of COVID-19 in Ondo State, March to August 2020 Association between socio-demographic characteristics, clinical conditions and outcomes of cases In Table 3 , significant proportion of death occurred among cases within the age group 60 years and above (14; 13.5%) compared to other age groups (p < 0.001). Death occurred more among males (26; 3.6%) compared to the females (3; 0.5%) (p < 0.001). Furthermore, symptomatic cases had higher proportion (27; 8.3%) of deaths compared to asymptomatic cases (2; 0.2%) (P < 0.001). Among the symptomatic cases, a high proportion of death was found among those with difficulty in breathing (3; 20%), fever (11; 14.9%), new loss of taste (1; 11.1%), cough (9; 9.2%) and sore throat (2; 8.3%) (P < 0.001) 1170 Table 3: Association between socio-demographic characteristics and outcomes of cases Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Others = chest pain, diarrhea, fatigue, joint pain, malaise, nausea, vomiting Open in new tab 1170 Table 3: Association between socio-demographic characteristics and outcomes of cases Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Others = chest pain, diarrhea, fatigue, joint pain, malaise, nausea, vomiting Open in new tab Conclusions The outcome of this investigation indicating high transmission among urban residence and health care workers are key public health concerns in the response to the COVID-19 outbreak in Ondo State, Nigeria. Furthermore, high case mortality among the older age groups requires public health intervention. Thus, we recommend intensified risk communication, enhanced surveillance activities, and use of community structures such as community and religious leaders, market and commercial vehicles associations, Ward Development Committee (WDC) and Village Development Committee (VDC) to ensure compliance with public health COVID-19 preventive measures particularly in the urban areas and among those facing a high risk of death. Furthermore, there is a need to prioritize public health interventions including training and vaccination among the vulnerable groups including health care workers who serve as front liners during case investigation, testing and case management. Key messages Enforcement of public health preventive measures particularly in urban settings, and supporting government to strengthen and monitor Infection Prevention and Control practices in hospital settings. [ABSTRACT FROM AUTHOR]

Objectives Isatis indigotica Fort. (I. indigotica) is an herbaceous plant belonging to Cruciferae family. Its leaf (IIL) and root (IIR) are commonly used in traditional Chinese medicines (TCMs) with good clinical efficacies such as clearing away heat and detoxification, cooling blood and reducing swelling. This review aimed to provide a systematic summary on the phytochemistry, pharmacology and clinical applications of I. indigotica. Key findings This plant contains alkaloids, organic acids, flavonoids, lignans, nucleosides, amino acids, and steroids. Previous pharmacological researches indicated that I. indigotica possesses promising antivirus, antibacterial, immunoregulatory, anti-inflammation, and cholagogic effects. Importantly, it can inhibit various viruses, such as influenza, hepatitis B, mumps, herpes simplex, cytomegalovirus, and coxsachievirus. Clinically, it is frequently used to treat various viral diseases like viral influenza, parotitis and viral hepatitis. Consequently, I. indigotica may be beneficial for the prevention and treatment of coronavirus disease 2019 (COVID-19). Summary This paper reviewed the chemical constituents, pharmacological effects and clinical applications of I. indigotica which may guide further research and application of this plant. [ABSTRACT FROM AUTHOR]

Acupuncture is an important part of Chinese medicine that has been widely used in the treatment of inflammatory diseases. During the coronavirus disease 2019 (COVID-19) epidemic, acupuncture has been used as a complementary treatment for COVID-19 in China. However, the underlying mechanism of acupuncture treatment of COVID-19 remains unclear. Based on bioinformatics/topology, this paper systematically revealed the multi-target mechanisms of acupuncture therapy for COVID-19 through text mining, bioinformatics, network topology, etc. Two active compounds produced after acupuncture and 180 protein targets were identified. A total of 522 Gene Ontology terms related to acupuncture for COVID-19 were identified, and 61 pathways were screened based on the Kyoto Encyclopedia of Genes and Genomes. Our findings suggested that acupuncture treatment of COVID-19 was associated with suppression of inflammatory stress, improving immunity and regulating nervous system function, including activation of neuroactive ligand–receptor interaction, calcium signaling pathway, cancer pathway, viral carcinogenesis, Staphylococcus aureus infection, etc. The study also found that acupuncture may have additional benefits for COVID-19 patients with cancer, cardiovascular disease and obesity. Our study revealed for the first time the multiple synergistic mechanisms of acupuncture on COVID-19. Acupuncture may play an active role in the treatment of COVID-19 and deserves further promotion and application. These results may help to solve this pressing problem currently facing the world. [ABSTRACT FROM AUTHOR]

Discovering drug–target (protein) interactions (DTIs) is of great significance for researching and developing novel drugs, having a tremendous advantage to pharmaceutical industries and patients. However, the prediction of DTIs using wet-lab experimental methods is generally expensive and time-consuming. Therefore, different machine learning-based methods have been developed for this purpose, but there are still substantial unknown interactions needed to discover. Furthermore, data imbalance and feature dimensionality problems are a critical challenge in drug-target datasets, which can decrease the classifier performances that have not been significantly addressed yet. This paper proposed a novel drug–target interaction prediction method called PreDTIs. First, the feature vectors of the protein sequence are extracted by the pseudo-position-specific scoring matrix (PsePSSM), dipeptide composition (DC) and pseudo amino acid composition (PseAAC); and the drug is encoded with MACCS substructure fingerings. Besides, we propose a FastUS algorithm to handle the class imbalance problem and also develop a MoIFS algorithm to remove the irrelevant and redundant features for getting the best optimal features. Finally, balanced and optimal features are provided to the LightGBM Classifier to identify DTIs, and the 5-fold CV validation test method was applied to evaluate the prediction ability of the proposed method. Prediction results indicate that the proposed model PreDTIs is significantly superior to other existing methods in predicting DTIs, and our model could be used to discover new drugs for unknown disorders or infections, such as for the coronavirus disease 2019 using existing drugs compounds and severe acute respiratory syndrome coronavirus 2 protein sequences. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) has spread rapidly throughout the globe. The spectrum of disease is broad but among hospitalized patients with COVID-19, respiratory failure from acute respiratory distress syndrome is the leading cause of mortality. There is an urgent need for an effective treatment. The current focus has been developing novel therapeutics, including antivirals, protease inhibitors, vaccines and targeting the overactive cytokine response with anti-cytokine therapy. The overproduction of early response proinflammatory cytokines results in what has been described as a "cytokine storm" is leading eventually to death when the cells fail to terminate the inflammatory response. Accumulating evidence shows that inflammatory cytokines induce selectin ligands that play a crucial role in the pathogenesis of inflammatory diseases by mediating leukocyte migration from the blood into the tissue. Thus, the selectins and selectin ligands represent a promising therapeutic target for the treatment of COVID-19. In this paper, potential pan-selectin inhibitors were identified employing a virtual screening using a docking procedure. For this purpose, the Asinex and ZINC databases of ligands, including approved drugs, biogenic compounds and glycomimetics, altogether 923,602 compounds, were screened against the P-, L- and E-selectin. At first, the experimentally confirmed inhibitors were docked into all three selectins' carbohydrate recognition domains to assess the suitability of the screening procedure. Finally, based on the evaluation of ligands binding, we propose 10 purchasable pan-selectin inhibitors to develop COVID-19 therapeutics. [ABSTRACT FROM AUTHOR]

This paper presents findings of a nation-wide study examining the impact of COVID-19 on researchers. Findings indicate that more than half of researchers experienced personal or family mental strain due to COVID-19 pandemic effects. COVID-19 pandemic is being treated as an opportunity by six out of ten researchers in terms of more time for study and planning future research activities (78 per cent). The majority of researchers (73 per cent) believe that Science and Technology will emerge enhanced from the pandemic in the public sphere. Relating our findings with research outcomes of existed surveys, it appears that COVID-19 had a significant impact on researchers' and workers' psychosocial life. Researchers' and scientists' standpoint suggest that Science and Technology will be upgraded in the public dialogue. Finally, researchers viewed the pandemic as an opportunity for more time for study and planning of future research activities while working time, with respect to other countries, decreased the most. [ABSTRACT FROM AUTHOR]

Background This paper presents a descriptive analysis of the perceptions of Kenyan midwifery educators regarding the early impact of coronavirus disease 2019 (COVID-19) on the continuity of midwifery education. Methods A cross-sectional online survey was conducted among 51 midwifery/clinical medicine educators from 35 diploma training colleges from all eight regions of Kenya. Educators' concerns and satisfaction regarding the delivery of training during the early phases of the pandemic were expressed as proportions on a three-point Likert scale. Results Of the educators, 76% were extremely concerned about face-to-face teaching during the pandemic; 96% of educators had started delivering virtual teaching (VT), with only 41% being extremely confident in facilitating VT; and 97% were unsatisfied with the measures in place in their institutions to continue face-to-face teaching. Conclusion To minimise the impact of COVID-19 on midwifery education in Kenya, capacity building for VT and mitigation measures for safe in-person training are urgently needed. [ABSTRACT FROM AUTHOR]

During the coronavirus pandemic, second-year students on the B.Sc. molecular biology and genetics degree at Istanbul Technical University sat an open-ended online exam for a microbiology course in which one of the compulsory questions asked how the course had helped them during the first phase of the pandemic (April–July 2020). Fifty of 69 students gave consent for their (anonymous) responses to be analysed in order to discern any key ways in which their knowledge had been applied. The aim of the study was to investigate whether taking an advanced microbiology course increases understanding of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic and has a positive impact on student behaviours with respect to public health practices. Findings were divided into four major themes: course content (information), application of course content to behavioural change (practice), professionalism and their 'audience' whilst at home in lockdown (family and friends). Social distancing, wearing face masks, and hand and surface hygiene were described as important behaviours, with this practice informed by their basic microbiology knowledge. This paper describes a scenario where rote assessment can be used to assess wider scientific literacy with respect to application in society, providing students with an opportunity to incorporate and apply their learning into real-life situations, whilst tutors can assess constructivist learning, conceptual understanding and impact on student behaviour. [ABSTRACT FROM AUTHOR]

Summary: The factors responsible for the spectrum of coronavirus 19 (COVID‐19) disease severity and the genesis and nature of protective immunity against COVID‐19 remain elusive. Multiple studies have investigated the immune responses to COVID‐19 in various populations, including those without evidence of COVID‐19 infection. Information regarding innate and adaptive immune responses to the novel severe respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has evolved rapidly. Data are accumulating defining disease phenotypes that aid in rational and informed development of new therapeutic approaches for the treatment of patients infected with SARS‐CoV‐2 and the development of novel vaccines. In this paper, data on important innate immune responses are summarized, including cytokines, specifically interleukin (IL)‐6 and complement, and potential treatments are explored. Adaptive immune responses and derivative therapeutics such as monoclonal antibodies directed at spike proteins are also examined. Finally, data on real‐time assessments of adaptive immune responses are explored, which include CD4+/CD8+ T cells, natural killer (NK) T cells, memory B cells and T follicular cells with specificities for COVID‐19 peptides in infected and normal individuals. Data of two novel vaccines have been released, both showing > 95% efficacy in preventing SARS‐CoV‐2 infection. Analysis of humoral and cellular responses to the vaccines will determine the robustness and durability of protection. In addition, long‐term assessment of SARS‐CoV‐2 memory B and T cell‐mediated immune responses in patients recovering from an infection or those with cross‐reactive immunological memory will help to define risk for future SARS‐CoV infections. Finally, patients recovering from SARS‐CoV‐2 infection may experience prolonged immune activation probably due to T cell exhaustion. This will be an important new frontier for study. This review summarizes published data on the relevant innate and adaptive immune responses to SARS‐CoV‐2. Data characterizing innate and adaptive immune responses have rapidly led to informed therapeutic interventions, including vaccine development and recognition of dysfunctional immune responses that are likely responsible for post‐COVID‐19 autoimmunity. [ABSTRACT FROM AUTHOR]

Background The bacille Calmette-Guérin (BCG) tuberculosis vaccine has immunity benefits against respiratory infections. Accordingly, it has been hypothesized to have a protective effect against coronavirus disease 2019 (COVID-19). Recent research found that countries with universal BCG childhood vaccination policies tend to be less affected by the COVID-19 pandemic. However, such ecological studies are biased by numerous confounders. Instead, this paper reports on a rare nationwide natural experiment that occurred in Sweden in 1975, where discontinuation of newborns' BCG vaccination led to a dramatic decrease in BCG coverage rate, thus allowing us to estimate BCG's effect without the biases associated with cross-country comparisons. Methods Numbers of COVID-19 cases and hospitalizations were recorded for birth cohorts born just before and just after 1975, representing 1 026 304 and 1 018 544 individuals, respectively. We used regression discontinuity to assess the effect of BCG vaccination on COVID-19–related outcomes. On such a large population, this method allows for a precision that would be hard to achieve using a randomized controlled trial. Results The odds ratios (95% CI) for COVID-19 cases and COVID-19–related hospitalizations were 1.0005 (.8130–1.1881) and 1.2046 (.7532–1.6560), allowing us to reject fairly modest effects of universal BCG vaccination. We can reject with 95% confidence that universal BCG vaccination reduces the number of cases by 19% and the number of hospitalizations by 25%. Conclusions While the effect of a recent vaccination must be evaluated, we provide strong evidence that receiving the BCG vaccine at birth does not have a protective effect against COVID-19 among middle-aged individuals. [ABSTRACT FROM AUTHOR]

Background The COVID-19 pandemic has led to large proportions of the labour market moving to remote work, while others have become unemployed. Those still at their physical workplace likely face increased risk of infection, compared to other workers. The objective of this paper is to understand the relationship between working arrangements, infection control programs (ICP), and symptoms of anxiety and depression among Canadian workers, not specifically working in healthcare. Methods A convenience-based internet survey of Canadian non-healthcare workers was facilitated through various labour organizations between April 26 and June 6, 2020. A total of 5180 respondents started the survey, of which 3779 were assessed as employed in a full-time or part-time capacity on 2 March 2020 (prior to large-scale COVID-19 pandemic responses in Canada). Of this sample, 3305 (87.5%) had complete information on main exposures and outcomes. Anxiety symptoms were measured using the Generalised Anxiety Disorder screener (GAD-2), and depressive symptoms using the Patient Health Questionnaire screener (PHQ-2). For workers at their physical workplace (site-based workers) we asked questions about the adequacy and implementation of 11 different types of ICP, and the adequacy and supply of eight different types of personal protective equipment (PPE). Respondents were classified as either: working remotely; site-based workers with 100% of their ICP/PPE needs met; site-based workers with 50–99% of ICP/PPE needs met; site-based workers with 1–49% of ICP/PPE needs met; site-based workers with none of ICP/PPE needs met; or no longer employed. Regression analyses examined the association between working arrangements and ICP/PPE adequacy and having GAD-2 and PHQ-2 scores of three and higher (a common screening point in both scales). Models were adjusted for a range of demographic, occupation, workplace, and COVID-19-specific factors. Results A total of 42.3% (95% CI: 40.6–44.0%) of the sample had GAD-2 scores of 3 and higher, and 34.6% (95% CI: 32.–36.2%) had PHQ-2 scores of 3 and higher. In initial analyses, symptoms of anxiety and depression were lowest among those working remotely (35.4 and 27.5%), compared to site-based workers (43.5 and 34.7%) and those who had lost their jobs (44.1 and 35.9%). When adequacy of ICP and PPE was taken into account, the lowest prevalence of anxiety and depressive symptoms was observed among site-based workers with all of their ICP needs being met (29.8% prevalence for GAD-2 scores of 3 and higher, and 23.0% prevalence for PHQ-2 scores of 3 and higher), while the highest prevalence was observed among site-based workers with none of their ICP needs being met (52.3% for GAD-2 scores of 3 and higher, and 45.8% for PHQ-2 scores of 3 and higher). Conclusion Our results suggest that the adequate design and implementation of employer-based ICP have implications for the mental health of site-based workers. As economies re-open the ongoing assessment of ICP and associated mental health outcomes among the workforce is warranted. [ABSTRACT FROM AUTHOR]

Objectives The high demand of filtering facepiece respirators (FFRs) worldwide during the period of the COVID-19 pandemic has led to a critical situation for decision-makers regarding their supply. After authorizing the use of FFRs certified by other regions of the world, decision-makers in many countries have published alerts, particularly concerning the 'KN95' type. Methods This paper investigated the filtration performance of different FFRs using an experimental setup already employed during several studies on FFRs filtration performance. Its high-resolution measuring devices permit to determine filtration performance according to the normative criteria: the pressure drop and the filtration efficiency. Eight different FFRs have been used: four NIOSH-approved FFRs and four not NIOSH-approved with a 'KN95' shape available during the beginning of the COVID-19 pandemic. Results The data show a high disparity between different FFRs purchased by healthcare establishments, and between those that are NIOSH-approved and those that are not NIOSH-approved. The results confirm that the NIOSH certification offers good protection according to the normative criteria. The 'KN95' types present pressure drops which correspond to the normative value, however their efficiencies are lower than the efficiencies of FFRs certified by NIOSH and lower than 95% at the most penetrate particle size. Conclusions FFRs marking is not sufficient to conclude on the FFRs' efficiency. Visual inspection can not determine which samples are counterfeit or have manufacturing defects. [ABSTRACT FROM AUTHOR]