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According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.

At least since March 2020, the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic and the multi-organ coronavirus disease 2019 (COVID-19) are keeping a firm grip on the world. Although most cases are mild, older patients and those with co-morbidities are at increased risk of developing a cytokine storm, characterized by a systemic inflammatory response leading to acute respiratory distress syndrome and organ failure. The present paper focuses on the small molecule MP1032, describes its mode of action, and gives rationale why it is a promising option for the prevention/treatment of the SARS-CoV-2-induced cytokine storm. MP1032 is a phase-pure anhydrous polymorph of 5-amino-2,3-dihydro-1,4-phthalazinedione sodium salt that exhibits good stability and bioavailability. The physiological action of MP1032 is based on a multi-target mechanism including localized, self-limiting reactive oxygen species (ROS) scavenging activities that were demonstrated in a model of lipopolysaccharide (LPS)-induced joint inflammation. Furthermore, its immune-regulatory and PARP-1-modulating properties, coupled with antiviral effects against SARS-CoV-2, have been demonstrated in various cell models. Preclinical efficacy was elucidated in LPS-induced endotoxemia, a model with heightened innate immune responses that shares many similarities to COVID-19. So far, during oral clinical development with three-month daily administrations, no serious adverse drug reactions occurred, highlighting the outstanding safety profile of MP1032.

The coronavirus disease 2019 (COVID-19) pandemic is considered a public health emergency of international concern. The 2019 novel coronavirus (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused this pandemic has spread rapidly to over 200 countries, and has drastically affected public health and the economies of states at unprecedented levels. In this context, efforts around the world are focusing on solving this problem in several directions of research, by: (i) exploring the origin and evolution of the phylogeny of the SARS-CoV-2 viral genome; (ii) developing nanobiosensors that could be highly effective in detecting the new coronavirus; (iii) finding effective treatments for COVID-19; and (iv) working on vaccine development. In this paper, an overview of the progress made in the development of nanobiosensors for the detection of human coronaviruses (SARS-CoV, SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV) is presented, along with specific techniques for modifying the surface of nanobiosensors. The newest detection methods of the influenza virus responsible for acute respiratory syndrome were compared with conventional methods, highlighting the newest trends in diagnostics, applications, and challenges of SARS-CoV-2 (COVID-19 causative virus) nanobiosensors.

This study aimed to descript the Belgian COVID-19 responses process according to the WHO's (World Health Organization) Health Emergency and Disaster Risk Management Framework (Health EDRM Framework) and to present the measures taken and epidemic impact in the different phases of COVID-19 in Belgium. The WHO's EDRM Framework was used for reviewing the Belgian Public health emergency preparedness and responses in the context of COVID-19. Information on the measures taken was collected through the literature review including all government's communication, reports, and scientific papers. All epidemic data were extracted from a national open database managed and published by the Sciensano. Additionally, two authors closely followed the Belgian situation since the beginning of the pandemic and updated the data every day. During the COVID-19 pandemic, the anti-epidemic strategy was mainly to avoid medical resources exceeding the upper limit. Belgium issued a series of emergency decrees to limit the spread of the virus. An existing structure of "federal-region-municipal" as the framework of public health emergency preparedness and response was adapted. The emergency response process in Belgium was divided into four phases: information-evaluation-coordination-decision-making at the region level and the final decision-making at the federal level. Belgium also implemented a phased plan in the process of setting up and lifting the lockdown. However, it was vulnerable in early response, due to the shortage of medical equipment supplies in general, and more particularly for the long term care facilities (LTCFs). Belgium has achieved an intensive cooperation between stakeholders based on an existing multisectoral emergency organization framework. Legislation, medical insurance, and good communication also played a role in limiting the spread of viruses. However, the authorities underestimated the risk of an epidemic and did not take quarantine measures among people suspected affected by SARS-COV-2 in the early stages, resulting in insufficient medical equipment supply and a large number of deaths in the LTCF. The implementation of the lockdown measure in Belgium also encountered obstacles. The lockdown and its exit strategy were both closely related to the pandemic situation and social and economic life. The authorities should strengthen information management, improve the public awareness of the measures, and find out the balance points between the social and economic life and infection control measures.

The outbreak of Corona Virus Disease 2019 (COVID-19) has affected the lives of people all over the world. It is particularly urgent and important to analyze the epidemic spreading law and support the implementation of epidemic prevention measures. It is found that there is a moderate to high correlations between the number of newly diagnosed cases per day and temperature and relative humidity in countries with more than 10,000 confirmed cases worldwide. In this paper, the correlation between temperature/relative humidity and the number of newly diagnosed cases is obvious. Governments can adjust the epidemic prevention measures according to climate change, which will more effectively control the spread of COVID-19.

An overwhelming flood of misinformation is accompanying the pandemic of COVID-19. Fake news and conspiracy theories are so prevalent that the World Health Organization started as early as February 2020 to use the term "infodemic". This paper is focused on the assessment of the prevalence of beliefs in conspiracy theories related to COVID-19 in Polish society. The association of support for conspiracy theories with sociodemographic variables, health literacy (HL) and eHealth literacy (eHL) was studied. The analysis reported here was based on the data from an online survey of a representative sample ( n = 1002) of the adult population of Polish Internet users. The multivariate linear regression for the COVID-19-related conspiracy belief score (CCBS) and logistic regression models for the support of individual conspiracy theories was developed. The percentage of supporters of particular conspiracy theories in the study sample ranged from 43% to 56%. The CCBS was significantly associated with age, education level, vocational status and both HL and eHL. However, it was lower for persons with higher HL (regression coefficient (B) = -0.04, p < 0.001) but higher for those with higher eHL (B = 0.04, p = 0.038). The most influential predictors of CCBS were age (standardised regression coefficient (β) = -0.21) and education level (β from 0.08 to 0.16 for respondents with lower education levels and those with master's degrees). In conclusion, younger persons rather than older, those with a lower rather than with a higher level of education, employees rather than students and persons with lower rather than higher HL were more likely to believe the conspiracy theories. Surprisingly, contrary to expectations, higher eHL was significantly associated with greater belief in such theories.

A novel series of some hydrazones bearing thiazole moiety were generated via solvent-drop grinding of thiazole carbohydrazide 2 with various carbonyl compounds. Also, dehydrative-cyclocondensation of 2 with active methylene compounds or anhydrides gave the respective pyarzole or pyrazine derivatives. The structures of the newly synthesized compounds were established based on spectroscopic evidences and their alternative syntheses. Additionally, the anti-viral activity of all the products was tested against SARS-CoV-2 main protease (M pro ) using molecular docking combined with molecular dynamics simulation (MDS). The average binding affinities of the compounds 3a , 3b , and 3c (-8.1 ± 0.33 kcal/mol, -8.0 ± 0.35 kcal/mol, and -8.2 ± 0.21 kcal/mol, respectively) are better than that of the positive control Nelfinavir (-6.9 ± 0.51 kcal/mol). This shows the possibility of these three compounds to effectively bind to SARS-CoV-2 Mpro and hence, contradict the virus lifecycle., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper.

The problem of treating viral infections is extremely relevant due to both the emergence of new viral diseases and to the low effectiveness of existing approaches to the treatment of known viral infections. This review focuses on the application of porphyrin, chlorin, and phthalocyanine series for combating viral infections by chemical and photochemical inactivation methods. The purpose of this review paper is to summarize the main approaches developed to date in the chemical and photodynamic inactivation of human and animal viruses using porphyrins and their analogues and to analyze and discuss the information on viral targets and antiviral activity of porphyrins, chlorins, of their conjugates with organic/inorganic compounds obtained in the last 10-15 years in order to identify the most promising areas.

The current COVID-19 pandemic is having a major impact on our daily lives. Social distancing is one of the measures that has been implemented with the aim of slowing the spread of the disease, but it is difficult for blind people to comply with this. In this paper, we present a system that helps blind people to maintain physical distance to other persons using a combination of RGB and depth cameras. We use a real-time semantic segmentation algorithm on the RGB camera to detect where persons are and use the depth camera to assess the distance to them; then, we provide audio feedback through bone-conducting headphones if a person is closer than 1.5 m. Our system warns the user only if persons are nearby but does not react to non-person objects such as walls, trees or doors; thus, it is not intrusive, and it is possible to use it in combination with other assistive devices. We have tested our prototype system on one blind and four blindfolded persons, and found that the system is precise, easy to use, and amounts to low cognitive load.

Background: To prioritize the development of antiviral compounds, it is necessary to compare their relative preclinical activity and clinical efficacy., Methods: We reviewed in vitro, animal model, and clinical studies of candidate anti-coronavirus compounds and placed extracted data in an online relational database., Results: As of August 2020, the Coronavirus Antiviral Research Database (CoV-RDB; covdb.stanford.edu) contained over 2800 cell culture, entry assay, and biochemical experiments, 259 animal model studies, and 73 clinical studies from over 400 published papers. SARS-CoV-2, SARS-CoV, and MERS-CoV account for 85% of the data. Approximately 75% of experiments involved compounds with known or likely mechanisms of action, including monoclonal antibodies and receptor binding inhibitors (21%), viral protease inhibitors (17%), miscellaneous host-acting inhibitors (10%), polymerase inhibitors (9%), interferons (7%), fusion inhibitors (5%), and host protease inhibitors (5%). Of 975 compounds with known or likely mechanism, 135 (14%) are licensed in the U.S. for other indications, 197 (20%) are licensed outside the U.S. or are in human trials, and 595 (61%) are pre-clinical investigational compounds., Conclusion: CoV-RDB facilitates comparisons between different candidate antiviral compounds, thereby helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development.

Social distancing and contact/exposure tracing are accepted to be critical strategies in the fight against the COVID-19 epidemic. They are both closely connected to the ability to reliably establish the degree of proximity between people in real-world environments. We proposed, implemented, and evaluated a wearable proximity sensing system based on an oscillating magnetic field that overcomes many of the weaknesses of the current state of the art Bluetooth based proximity detection. In this paper, we first described the underlying physical principle, proposed a protocol for the identification and coordination of the transmitter (which is compatible with the current smartphone-based exposure tracing protocols). Subsequently, the system architecture and implementation were described, finally an elaborate characterization and evaluation of the performance (both in systematic lab experiments and in real-world settings) were performed. Our work demonstrated that the proposed system is much more reliable than the widely-used Bluetooth-based approach, particularly when it comes to distinguishing between distances above and below the 2.0 m threshold due to the magnetic field's physical properties.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus was discovered in China in late 2019 and subsequently triggered a global pandemic. Dentists, like many other health professionals, are at an increased risk of contracting the virus as they work in close proximity to patients, especially when performing aerosol-generating procedures. Thus, in order for dentists to protect themselves and their patients, it is recommended that practitioners wear filtering facepiece 2 (FFP2) respirators. The prolonged use of these FFP2 respirators has been linked to several side effects. The aim of this paper is to assess the perceived experience associated with N95/FFP2 respirators based on the available literature and data collected through an online survey completed by Italian dental professionals. Articles were included up to May 2020 and literature searches were conducted through The National Library of Medicine, Cochrane Central Register of Controlled Trials, and Embase databases. The search terms included COVID-19, respirators, masks, and discomfort. An online survey was administered to 256 Italian dentists. The results from this survey were in agreement with the available literature. The findings concurred that the prolonged use of respirators was associated with headaches (47.5%), severe exertion and discomfort (50.8%), moderate concentration problems (54.3%), moderate breathing difficulties (63.5%), and consequently, an impaired work ability (85.5%). These findings were not influenced by the number of hours spent wearing the respirator. Despite several side effects, FFP2 respirators are fundamental in protecting dentists and their importance was acknowledged.

This study examines how confinement measures established during the COVID-19 pandemic crisis affected the emotions of the population. For this purpose, public sentiment on social media and digital ecosystems in Spain is analyzed. We identified affective tones towards media and citizens published on social media focusing on six basic emotions: anger, fear, joy, sadness, disgust and uncertainty. The main contribution of this work is the evidence of contagious sentiments and, consequently, the possibility of using this new dimension of social media as a form of a "collective therapy". This paper contributes to understanding the impact of confinement measures in a pandemic from the point of view of emotional health. This analysis provides a set of practical implications that can guide conceptual and empirical work in health crisis management with an alternative approach, especially useful for decision-making processes facing emergency responses and health crises, even in an unprecedented global health crisis such as the traumatic events caused by the COVID-19 disease.

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a severe global health crisis. In this paper, we used docking and simulation methods to identify potential targets and the mechanism of action of chloroquine (CQ) and hydroxychloroquine (HCQ) against SARS-CoV-2. Our results showed that both CQ and HCQ influenced the functionality of the envelope (E) protein, necessary in the maturation processes of the virus, due to interactions that modify the flexibility of the protein structure. Furthermore, CQ and HCQ also influenced the proofreading and capping of viral RNA in SARS-CoV-2, performed by nsp10/nsp14 and nsp10/nsp16. In particular, HCQ demonstrated a better energy binding with the examined targets compared to CQ, probably due to the hydrogen bonding of the hydroxyl group of HCQ with polar amino acid residues.

This paper makes the case for immediate planning for a COVID-19 vaccination uptake strategy in advance of vaccine availability for two reasons: first, the need to build a consensus about the order in which groups of the population will get access to the vaccine; second, to reduce any fear and concerns that exist in relation to vaccination and to create demand for vaccines. A key part of this strategy is to counter the anti-vaccination movement that is already promoting hesitancy and resistance. Since the beginning of the COVID-19 pandemic there has been a tsunami of misinformation and conspiracy theories that have the potential to reduce vaccine uptake. To make matters worse, sections of populations in many countries display low trust in governments and official information about the pandemic and how the officials are tackling it. This paper aims to set out in short form critical guidelines that governments and regional bodies should take to enhance the impact of a COVID-19 vaccination strategy. We base our recommendations on a review of existing best practice guidance. This paper aims to assist those responsible for promoting COVID-19 vaccine uptake to digest the mass of guidance that exists and formulate an effective locally relevant strategy. A summary of key guidelines is presented based on best practice guidance.

Background and Objective : COVID-19 has engulfed the entire world, with many countries struggling to contain the pandemic. In order to understand how each country is impacted by the virus compared with what would have been expected prior to the pandemic and the mortality risk on a global scale, a multi-factor weighted spatial analysis is presented. Method : A number of key developmental indicators across three main categories of demographics, economy, and health infrastructure were used, supplemented with a range of dynamic indicators associated with COVID-19 as independent variables. Using normalised COVID-19 mortality on 13 May 2020 as a dependent variable, a linear regression (N = 153 countries) was performed to assess the predictive power of the various indicators. Results : The results of the assessment show that when in combination, dynamic and static indicators have higher predictive power to explain risk variation in COVID-19 mortality compared with static indicators alone. Furthermore, as of 13 May 2020 most countries were at a similar or lower risk level than what would have been expected pre-COVID, with only 44/153 countries experiencing a more than 20% increase in mortality risk. The ratio of elderly emerges as a strong predictor but it would be worthwhile to consider it in light of the family makeup of individual countries. Conclusion : In conclusion, future avenues of data acquisition related to COVID-19 are suggested. The paper concludes by discussing the ability of various factors to explain COVID-19 mortality risk. The ratio of elderly in combination with the dynamic variables associated with COVID-19 emerge as more significant risk predictors in comparison to socio-economic and demographic indicators.

People with existing non-communicable diseases (NCDs) are particularly vulnerable to health risks brought upon by emergencies and disasters, yet limited research has been conducted on disease management and the implications of Health-EDRM policies that address health vulnerabilities of people with NCDs during the COVID-19 pandemic. This paper reports the baseline findings of an anonymous, random, population-based, 6-month cohort study that aimed to examine the experiences of people with NCDs and their relevant self-care patterns during the COVID-19 pandemic. A total of 765 telephone interviews were completed from 22nd March to 1st April 2020 in Hong Kong, China. The dataset was representative of the population, with 18.4% of subjects reporting at least one NCD. Results showed that low household income and residence in government-subsidized housing were significant predictors for the subjects who experienced difficulty in managing during first 2 months of the pandemic (11% of the NCD patients). Of those on long-term NCD medication, 10% reported having less than one week's supply of medication. Targeted services for vulnerable groups during a pandemic should be explored to support NCD self-care.

Increasing evidence suggests that Severe Acute Respiratory Syndrome-coronavirus-2 (SARS-CoV-2) can also invade the central nervous system (CNS). However, findings available on its neurological manifestations and their pathogenic mechanisms have not yet been systematically addressed. A literature search on neurological complications reported in patients with COVID-19 until June 2020 produced a total of 23 studies. Overall, these papers report that patients may exhibit a wide range of neurological manifestations, including encephalopathy, encephalitis, seizures, cerebrovascular events, acute polyneuropathy, headache, hypogeusia, and hyposmia, as well as some non-specific symptoms. Whether these features can be an indirect and unspecific consequence of the pulmonary disease or a generalized inflammatory state on the CNS remains to be determined; also, they may rather reflect direct SARS-CoV-2-related neuronal damage. Hematogenous versus transsynaptic propagation, the role of the angiotensin II converting enzyme receptor-2, the spread across the blood-brain barrier, the impact of the hyperimmune response (the so-called "cytokine storm"), and the possibility of virus persistence within some CNS resident cells are still debated. The different levels and severity of neurotropism and neurovirulence in patients with COVID-19 might be explained by a combination of viral and host factors and by their interaction.

The present paper intends to address the impact of COVID-19 crisis upon the consumer buying behavior of fresh vegetables directly from local producers as observed 30 days later, after enforcing the state of emergency in Romania within a well-defined area, namely, the quarantined area of Suceava. The study relies on the interpretation of answers received from the quarantined area (N = 257) to a questionnaire applied online nationwide. The starting point of this paper is the analysis of the sociodemographic factors on the purchasing decision of fresh vegetables directly from local producers before declaring the state of emergency in Romania (16 March 2020). Further research has been conducted by interpreting the changes triggered by the COVID-19 crisis on the purchasing intention of such products before and after the end of the respective crisis. The aim of this scientific investigation relies on identifying the methods by which these behavioral changes can influence the digital transformation of short food supply chains.

This paper provides a rapid assessment method of potentially infectious waste flow related to the coronavirus disease (COVID-19) pandemic in Romania focusing on the emergency state (from 16 March to 14 May 2020) where a national lockdown was in force with restrictive and social distancing measures concerning population mobility and economic activities. Medical and municipal waste management systems are critical services in combating the virus spread in the community. This assessment is useful due to poor available data of medical waste flow in environmental reports and it covers COVID-19 patients, quarantined, and self-isolated persons as the main potential infectious waste sources. The proposed model estimates that COVID-19 related waste flow is 4312 t at the national level from 25 February to 15 June of which 2633 t in the emergency state period. This assessment is correlated with deficiencies of medical and municipal waste management systems in Romania before the COVID-19 pandemic as stress factors of public health and environment. This study points out the main challenges of waste operators and reveals some best practices during this pandemic crisis. Based on the results and discussion section, several recommendations are proposed to COVID-19 waste-related issues and points out the crucial role of the reliable medical and municipal waste database in managing such biologic hazards at national and EU levels. Monitoring of COVID-19 waste flow through such models are important for decision-makers, particularly in low and middle-income countries which are facing waste management deficiencies and gaps in waste statistics, to reduce other contamination risks or related environmental threats.

Background: Pacific Small Island Developing States (SIDS) have health care systems with a limited capacity to deal with pandemics, making them especially vulnerable to the economic and social impacts of the coronavirus (COVID-19). This paper examines the introduction, transmission, and incidence of COVID-19 into Pacific SIDS., Methods: Calculate the rate of transmission (the average number of new cases per day between the first recorded case and the most recent day) and connectivity (daily direct flights to the leading airport in each selected island group) using flight history and COVID-19 transmission data., Results: Correlational analyses show that connectivity is positively related with (a) first-case dates and (b) spread rate in Pacific SIDS., Conclusion: Connectivity plays a central role in the spread of COVID-19 in Pacific SIDS. The continued entry of people was a significant factor for spread within countries. Efforts to prevent transmission by closing borders reduced transmission but also created significant economic hardship because many Pacific SIDS rely heavily on tourism and international exchange. The findings highlight the importance of exploring the possibility that the COVID-19 spread rate may be higher than official figures indicate, and present pathways to mitigate socio-economic impacts. The practical implications of the findings reveal the vulnerability of Pacific SIDS to pandemics and the key role of connectivity in the spread of COVID-19 in the Pacific region.

While COVID-19 is becoming one of the most severe public health crises in the twenty-first century, media coverage about this pandemic is getting more important than ever to make people informed. Drawing on data scraped from Twitter, this study aims to analyze and compare the news updates of two main Spanish newspapers El País and El Mundo during the pandemic. Throughout an automatic process of topic modeling and network analysis methods, this study identifies eight news frames for each newspaper's Twitter account. Furthermore, the whole pandemic development process is split into three periods-the pre-crisis period, the lockdown period and the recovery period. The networks of the computed frames are visualized by these three segments. This paper contributes to the understanding of how Spanish news media cover public health crises on social media platforms.

In this paper, a formula for estimating the prevalence ratio of a disease in a population that is tested with imperfect tests is given. The formula is in terms of the fraction of positive test results and test parameters, i.e., probability of true positives (sensitivity) and the probability of true negatives (specificity). The motivation of this work arises in the context of the COVID-19 pandemic in which estimating the number of infected individuals depends on the sensitivity and specificity of the tests. In this context, it is shown that approximating the prevalence ratio by the ratio between the number of positive tests and the total number of tested individuals leads to dramatically high estimation errors, and thus, unadapted public health policies. The relevance of estimating the prevalence ratio using the formula presented in this work is that precision increases with the number of tests. Two conclusions are drawn from this work. First, in order to ensure that a reliable estimation is achieved with a finite number of tests, testing campaigns must be implemented with tests for which the sum of the sensitivity and the specificity is sufficiently different than one. Second, the key parameter for reducing the estimation error is the number of tests. For a large number of tests, as long as the sum of the sensitivity and specificity is different than one, the exact values of these parameters have very little impact on the estimation error.

As SARS-CoV-2 is spreading rapidly around the globe, adopting proper actions for confronting and protecting against this virus is an essential and unmet task. Reactive oxygen species (ROS) promoting molecules such as peroxides are detrimental to many viruses, including coronaviruses. In this paper, metal decorated single-wall carbon nanotubes (SWCNTs) were evaluated for hydrogen peroxide (H 2 O 2 ) adsorption for potential use for designing viral inactivation surfaces. We employed first-principles methods based on the density functional theory (DFT) to investigate the capture of an individual H 2 O 2 molecule on pristine and metal (Pt, Pd, Ni, Cu, Rh, or Ru) decorated SWCNTs. Although the single H 2 O 2 molecule is weakly physisorbed on pristine SWCNT, a significant improvement on its adsorption energy was found by utilizing metal functionalized SWCNT as the adsorbent. It was revealed that Rh-SWCNT and Ru-SWCNT systems demonstrate outstanding performance for H 2 O 2 adsorption. Furthermore, we discovered through calculations that Pt- and Cu-decorated SWNCT-H 2 O 2 systems show high potential for filters for virus removal and inactivation with a very long shelf-life (2.2 × 10 12 and 1.9 × 10 8 years, respectively). The strong adsorption of metal decorated SWCNTs and the long shelf-life of these nanomaterials suggest they are exceptional candidates for designing personal protection equipment against viruses.

Objectives: The COVID-19 (SARS-CoV-2) pandemic is an ongoing public health challenge, also for the dentistry community. The main objective of this paper was to determine the economic and health-care impact of COVID-19 on dentists in the Autonomous Region of Galicia (Spain)., Methods: This was a descriptive observational study in which the data was collected by means of a self-administered survey (from 1 April 2020 to 30 April 2020)., Results: A total of 400 dentists from Galicia responded to the survey. Only 12.3% of the participants could obtain personal protective equipment (PPE) including FFP2 masks. Of the male respondents, 33.1% suffered losses >€15,000 compared to 19.4% of female respondents (OR = 3.121, p < 0.001). Economic losses seem to have contributed to the applications for economic help as 29.5% of the respondents who applied for this measure recorded losses in excess of €15,000 ( p = 0.03). Patients complained more about the fact that only emergency care was available during the State of Alarm, in dental surgeries that do not work with insurance companies or franchises. Only 4 professionals tested positive, 50% of whom worked exclusively in private practice and the other 50% who practised in both private and public surgeries. Dentists who practise in the public sector saw more urgent patients per week than those practising in private surgeries ( p = 0.013)., Conclusions: The COVID-19 pandemic has had economic repercussions in dentistry as only urgent treatment was available during the State of Alarm. These repercussions seem to be higher in male participants, as the majority of the participants have revealed higher economic losses than females. The level of assistance has also been affected, reducing the number of treated patients, although this quantity has been different in private and public surgeries. By presenting these findings we look to highlight the role that dentists play in society in treating dental emergencies in our surgeries, and this must be recognised and addressed by the relevant authorities, who must provide PPEs as a priority to this group as well as providing special economic aid in accordance with the losses incurred by the sector.

The contribution of this paper is twofold. First, a new data driven approach for predicting the Covid-19 pandemic dynamics is introduced. The second contribution consists in reporting and discussing the results that were obtained with this approach for the Brazilian states, with predictions starting as of 4 May 2020. As a preliminary study, we first used an Long Short Term Memory for Data Training-SAE (LSTM-SAE) network model. Although this first approach led to somewhat disappointing results, it served as a good baseline for testing other ANN types. Subsequently, in order to identify relevant countries and regions to be used for training ANN models, we conduct a clustering of the world's regions where the pandemic is at an advanced stage. This clustering is based on manually engineered features representing a country's response to the early spread of the pandemic, and the different clusters obtained are used to select the relevant countries for training the models. The final models retained are Modified Auto-Encoder networks, that are trained on these clusters and learn to predict future data for Brazilian states. These predictions are used to estimate important statistics about the disease, such as peaks and number of confirmed cases. Finally, curve fitting is carried out to find the distribution that best fits the outputs of the MAE, and to refine the estimates of the peaks of the pandemic. Predicted numbers reach a total of more than one million infected Brazilians, distributed among the different states, with São Paulo leading with about 150 thousand confirmed cases predicted. The results indicate that the pandemic is still growing in Brazil, with most states peaks of infection estimated in the second half of May 2020. The estimated end of the pandemics (97% of cases reaching an outcome) spread between June and the end of August 2020, depending on the states.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2. The disease was first detected in Wuhan, the capital of China's Hubei province, in December 2019 and has since spread globally, especially to Europe and North America, resulting in the ongoing global coronavirus pandemic disaster of 2019-2020. Although most cases have mild symptoms, there is some progression to viral pneumonia and multi-organ failure and death. More than 4.6 million cases have been registered across 216 countries and territories as of 19 April 2020, resulting in more than 311,000 deaths. Risk to communities with continued widespread disease transmission depends on characteristics of the virus, including how well it spreads between people; the severity of resulting illness; and the medical or other measures available to control the impact of the virus (for example, vaccines or medications that can treat the illness) and the relative success of these. In the absence of vaccines or medications, non-pharmaceutical interventions were the most important response strategy based on community interventions such as person-to-person distancing, mask-wearing, isolation and good personal hygiene (hand-washing)-all of which have been demonstrated can reduce the impact of this seemingly unstoppable globally spreading natural disaster. This paper presents the results of quantitative research regarding the level of citizen preparedness for disasters caused by coronavirus disease (COVID-19) in Serbia. The survey was conducted using a questionnaire that was requested and then collected online among 975 respondents during disaster in April 2020. The questionnaire examined citizens' basic socio-economic and demographic characteristics, their knowledge, preparedness, risk perception and preventive measures taken individually and as a community to prevent the death and widespread transmission of novel coronavirus disease 2019 in the Republic of Serbia. Based on the findings that there are major differences in the public's perception of risks posed by communicable disease threats such as presented by COVID-19, emergency management agencies should use these differences to develop targeted strategies to enhance community and national preparedness by promoting behavioral change and improving risk management decision-making.

"Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)", the novel coronavirus, is responsible for the ongoing worldwide pandemic. "World Health Organization (WHO)" assigned an "International Classification of Diseases (ICD)" code-"COVID-19"-as the name of the new disease. Coronaviruses are generally transferred by people and many diverse species of animals, including birds and mammals such as cattle, camels, cats, and bats. Infrequently, the coronavirus can be transferred from animals to humans, and then propagate among people, such as with "Middle East Respiratory Syndrome (MERS-CoV)", "Severe Acute Respiratory Syndrome (SARS-CoV)", and now with this new virus, namely "SARS-CoV-2", or human coronavirus. Its rapid spreading has sent billions of people into lockdown as health services struggle to cope up. The COVID-19 outbreak comes along with an exponential growth of new infections, as well as a growing death count. A major goal to limit the further exponential spreading is to slow down the transmission rate, which is denoted by a "spread factor (f)", and we proposed an algorithm in this study for analyzing the same. This paper addresses the potential of data science to assess the risk factors correlated with COVID-19, after analyzing existing datasets available in "ourworldindata.org (Oxford University database)", and newly simulated datasets, following the analysis of different univariate "Long Short Term Memory (LSTM)" models for forecasting new cases and resulting deaths. The result shows that vanilla, stacked, and bidirectional LSTM models outperformed multilayer LSTM models. Besides, we discuss the findings related to the statistical analysis on simulated datasets. For correlation analysis, we included features, such as external temperature, rainfall, sunshine, population, infected cases, death, country, population, area, and population density of the past three months - January, February, and March in 2020. For univariate timeseries forecasting using LSTM, we used datasets from 1 January 2020, to 22 April 2020.

Nowadays, an infectious disease outbreak is considered one of the most destructive effects in the sustainable development process. The outbreak of new coronavirus (COVID-19) as an infectious disease showed that it has undesirable social, environmental, and economic impacts, and leads to serious challenges and threats. Additionally, investigating the prioritization parameters is of vital importance to reducing the negative impacts of this global crisis. Hence, the main aim of this study is to prioritize and analyze the role of certain environmental parameters. For this purpose, four cities in Italy were selected as a case study and some notable climate parameters-such as daily average temperature, relative humidity, wind speed-and an urban parameter, population density, were considered as input data set, with confirmed cases of COVID-19 being the output dataset. In this paper, two artificial intelligence techniques, including an artificial neural network (ANN) based on particle swarm optimization (PSO) algorithm and differential evolution (DE) algorithm, were used for prioritizing climate and urban parameters. The analysis is based on the feature selection process and then the obtained results from the proposed models compared to select the best one. Finally, the difference in cost function was about 0.0001 between the performances of the two models, hence, the two methods were not different in cost function, however, ANN-PSO was found to be better, because it reached to the desired precision level in lesser iterations than ANN-DE. In addition, the priority of two variables, urban parameter, and relative humidity, were the highest to predict the confirmed cases of COVID-19.

After the outbreak of COVID-19 (especially in the stage of tourism recovery), the bed and breakfast (B&B) tourism industry faced big challenges in improving its health strategies. B&Bs are very important for the tourism industry in China and many other countries. However, few studies have studied the impact of B&Bs, under COVID-19, on tourism in China. Our paper is among one of the first studies to investigate the impact of COVID-19 on tourist satisfaction with B&Bs in China. The work/travel restrictions started from 20 January 2020, and work/after travel resumed from 20 February 2020 in Zhejiang, China. Data were collected from 588 tourists (who experienced B&Bs in Zhejiang, China) from a WeChat online survey, from 1 March to 15 March 2020. The current study attempted to fill the gap by studying the changing tourist satisfaction levels with B&Bs before/after COVID-19. Moreover, some suggestions are given to the B&B industry for tourism resumption after COVID-19 by an importance-performance analysis (IPA)., Competing Interests: The authors declare no conflict of interest.

: The coronavirus disease (COVID-19) outbreak is rapidly progressing globally, and Italy, as one of the main pandemic hotspots, may provide some hard lessons for other countries. In this paper, we summarize the current organizational capacity and provide a pragmatic and narrative account of strategies and activities implemented by the Department of Prevention (Dipartimento di Prevenzione)-the regional entity of the Local Health Authority of the Italian National Health Service in charge of public health-since the beginning of the outbreak. We conduct a preliminary analysis of general strengths, weaknesses, opportunities, and threats (SWOT) of the response strategies from a local perspective. Furthermore, we provide firsthand insights on future directions and priorities to manage this unprecedented pandemic. Our case report gives a qualitative view of the healthcare response, based on the experience of frontline professionals, with the aim to generate hypotheses about factors which may promote or hinder the prevention and management of a pandemic locally. We highlight the importance of a public health approach for responding to COVID-19 and reshaping healthcare systems., Competing Interests: The authors declare no conflicts of interest.

Coronavirus disease 2019 (COVID-19) has spread rapidly across the globe, becoming a major public health challenge not for China only, but also for countries around the world. Despite worldwide efforts to contain viral spread, the outbreak has not been stopped yet. Among healthcare personnel, dentists seem to be at elevated risk of exposure to COVID-19. This risk is even more serious in pediatric dentistry, since affected children, frequently, present an asymptomatic, mild or moderate clinical viral infection and, therefore, they may play a major role in community-based COVID-19 transmission. To date, despite no universal guidelines are available for dental procedures in pediatric dentistry during COVID-19 outbreak, routine dental practice should be postponed and only severe dental emergencies must be treated. In the case of a dental emergency, involving a pediatric patient, dentists should be aware of which recommended management protocol can be adopted during the practice to protect patient health, to safeguard their-self and to prevent viral transmission. The aim of this paper is to provide clinical recommendations, presenting a needed tool for dentists to allow a valid and safe how-to-do protocol. Pediatric dentists should keep a high level of awareness to help patients, minimize risk and prevent viral spread.

With both cost and safety taken into account in the context of the life-threatening COVID-19 pandemic globally, rural tourism is expected to be the top choice for Chinese residents for relaxation and enhancing parent-child relationships. In this paper, a structural equation (SEM) model was proposed to compare risk knowledge, risk perception, risk aversion attitudes and behavioral intentions towards rural tourism. According to the empirical results, there was a large proportion of tourists showing preference for rural tourism recently. Potential participants in rural tourism paid most attention to the performance realization and time cost of scenic spots, while the psycho-social risk posed by COVID-19 had little impact. The inherent risk nature of risk aversion attitudes made knowledge of the pneumonia risk less effective in reducing tourists' intentions, while knowledge of the pneumonia risk was more effective in alleviating the risk perception that potential tourists have towards rural tourism. With regard to travel intention and recommendation intention of rural tourism, the negative impacts of risk aversion attitude were more considerable compared to risk perception. Meanwhile, the parallel mediating effect of risk perception and risk aversion attitude in rural tourism needed to be taken into consideration together.

In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the movement of patients, thence reducing the risk of infection. Leveraging the recent Cloud computing and Internet of Things (IoT) technologies, this paper aims at proposing a tele-medical laboratory service where clinical exams are performed on patients directly in a hospital by technicians through IoT medical devices and results are automatically sent via the hospital Cloud to doctors of federated hospitals for validation and/or consultation. In particular, we discuss a distributed scenario where nurses, technicians and medical doctors belonging to different hospitals cooperate through their federated hospital Clouds to form a virtual health team able to carry out a healthcare workflow in secure fashion leveraging the intrinsic security features of the Blockchain technology. In particular, both public and hybrid Blockchain scenarios are discussed and assessed using the Ethereum platform.

The expanding number of chronic respiratory diseases and the new Covid-19 outbreak create an increasing demand for mechanical ventilation (MV). As MV is no longer limited to intensive care units (ICU) and operating rooms (OR), more clinicians should acquaint themselves with the principles of mechanical ventilation. To fully acknowledge contemporary concepts of MV, it is crucial to understand the elemental physiology and respiratory machine nuances. This paper addresses the latter issues and provides insight into ventilation modes and essential monitoring of MV.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel betacoronavirus, is the causative agent of COVID-19, which has caused economic and social disruption worldwide. To date, many drugs and vaccines have been developed for the treatment and prevention of COVID-19 and have effectively controlled the global epidemic of SARS-CoV-2. However, SARS-CoV-2 is highly mutable, leading to the emergence of new variants that may counteract current therapeutic measures. Electron microscopy (EM) is a valuable technique for obtaining ultrastructural information about the intracellular process of virus replication. In particular, EM allows us to visualize the morphological and subcellular changes during virion formation, which would provide a promising avenue for the development of antiviral agents effective against new SARS-CoV-2 variants. In this review, we present our recent findings using transmission electron microscopy (TEM) combined with electron tomography (ET) to reveal the morphologically distinct types of SARS-CoV-2 particles, demonstrating that TEM and ET are valuable tools for visually understanding the maturation status of SARS-CoV-2 in infected cells. This review also discusses the application of EM analysis to the evaluation of genetically engineered RNA viruses. [ABSTRACT FROM AUTHOR]

Cross-species spillover to humans of coronaviruses (CoVs) from wildlife animal reservoirs poses marked and global threats to human and animal health. Recently, sporadic infection of canine coronavirus–human pneumonia-2018 (CCoV-HuPn-2018) in hospitalized patients with pneumonia genetically related to canine and feline coronavirus were identified. In addition, swine acute diarrhea syndrome coronavirus (SADS-CoV) had the capability of broad tropism to cultured cells including from humans. Together, the transmission of Alphacoronaviruses that originated in wildlife to humans via intermediate hosts was responsible for the high-impact emerging zoonosis. Entry of CoV is mainly mediated by Spike and formation of a typical six helix bundle (6-HB) structure in the postfusion state of Spike is pivotal. Here, we present the complete fusion core structures of CCoV-HuPn-2018 and SADS-CoV from Alphacoronavirus at 2.10 and 2.59 Å, respectively. The overall structure of the CCoV-HuPn-2018 fusion core is similar to Alphacoronavirus like HCoV-229E, while SADS-CoV is analogous to Betacoronavirus like SARS-CoV-2. Collectively, we provide a structural basis for the development of pan-CoV small molecules and polypeptides based on the HR1-HR2 complex, concerning CCoV-HuPn-2018 and SADS-CoV. [ABSTRACT FROM AUTHOR]

Murine hepatitis virus (MHV) is a non-human pathogen betacoronavirus that is evolutionarily and structurally related to the human pathogenic viruses SARS-CoV, MERS-CoV, and SARS-CoV-2. However, unlike the human SARS and MERS viruses, MHV requires a biosafety level 2 laboratory for propagating and safe handling, making it a potentially suitable surrogate virus. Despite this utility, few papers discussed the propagation and quantification of MHV using cell lines readily available in biorepositories making their implementations not easily reproducible. This article provides protocols for propagating and quantifying MHV-A59 using the recommended NCTC clone 1469 and clone 929 cell lines from American Type Culture Collection (ATCC). More specifically, the methods detail reviving cells, routine cell passaging, preparing freeze stocks, infection of NCTC clone 1469 with MHV and subsequent harvesting, and plaque assay quantification of MHV using NCTC clone 929 cells. Using these protocols, a BSL-2 laboratory equipped for cell culture work would generate at least 6.0 log plaque-forming units (PFU) per mL of MHV lysate and provide an optimized overlay assay using either methylcellulose or agarose as overlays for the titration of infectious virus particles. The protocols described here are intended to be utilized for persistence and inactivation studies of coronaviruses. [ABSTRACT FROM AUTHOR]

The novel coronavirus SARS-CoV-2 is the seventh identified human coronavirus. Understanding the extent of pre-existing immunity induced by seropositivity to endemic seasonal coronaviruses and the impact of cross-reactivity on COVID-19 disease progression remains a key research question in immunity to SARS-CoV-2 and the immunopathology of COVID-2019 disease. This paper describes a panel of lentiviral pseudotypes bearing the spike (S) proteins for each of the seven human coronaviruses (HCoVs), generated under similar conditions optimized for high titre production allowing a high-throughput investigation of antibody neutralization breadth. Optimal production conditions and most readily available permissive target cell lines were determined for spike-mediated entry by each HCoV pseudotype: SARS-CoV-1, SARS-CoV-2 and HCoV-NL63 best transduced HEK293T/17 cells transfected with ACE2 and TMPRSS2, HCoV-229E and MERS-CoV preferentially entered HUH7 cells, and CHO cells were most permissive for the seasonal betacoronavirus HCoV-HKU1. Entry of ACE2 using pseudotypes was enhanced by ACE2 and TMPRSS2 expression in target cells, whilst TMPRSS2 transfection rendered HEK293T/17 cells permissive for HCoV-HKU1 and HCoV-OC43 entry. Additionally, pseudotype viruses were produced bearing additional coronavirus surface proteins, including the SARS-CoV-2 Envelope (E) and Membrane (M) proteins and HCoV-OC43/HCoV-HKU1 Haemagglutinin-Esterase (HE) proteins. This panel of lentiviral pseudotypes provides a safe, rapidly quantifiable and high-throughput tool for serological comparison of pan-coronavirus neutralizing responses; this can be used to elucidate antibody dynamics against individual coronaviruses and the effects of antibody cross-reactivity on clinical outcome following natural infection or vaccination. [ABSTRACT FROM AUTHOR]

Bats are a major global reservoir of alphacoronaviruses (alphaCoVs) and betaCoVs. Attempts to discover the causative agents of COVID-19 and SARS have revealed horseshoe bats (Rhinolophidae) to be the most probable source of the virus. We report the first detection of bat coronaviruses (BtCoVs) in insectivorous bats in Poland and highlight SARS-related coronaviruses found in Rhinolophidae bats. The study included 503 (397 oral swabs and 106 fecal) samples collected from 20 bat species. Genetically diverse BtCoVs (n = 20) of the Alpha- and Betacoronavirus genera were found in fecal samples of two bat species. SARS-related CoVs were in 18 out of 58 lesser horseshoe bat (Rhinolophus hipposideros) samples (31%, 95% CI 20.6–43.8), and alphaCoVs were in 2 out of 55 Daubenton's bat (Myotis daubentonii) samples (3.6%, 95% CI 0.6–12.3). The overall BtCoV prevalence was 4.0% (95% CI 2.6–6.1). High identity was determined for BtCoVs isolated from European M. daubentonii and R. hipposideros bats. The detection of SARS-related and alphaCoVs in Polish bats with high phylogenetic relatedness to reference BtCoVs isolated in different European countries but from the same species confirms their high host restriction. Our data elucidate the molecular epidemiology, prevalence, and geographic distribution of coronaviruses and particularly SARS-related types in the bat population. [ABSTRACT FROM AUTHOR]