COVID-19 Cases Worldwide Research Articles

The Saudi Critical Care Society extracorporeal life support chapter guidance on utilization of veno-venous extracorporeal membrane oxygenation in adults with acute respiratory distress syndrome and special considerations in the era of coronavirus disease 2019.

Extracorporeal membrane oxygenation (ECMO) is considered as a supportive treatment that provides circulatory and ventilatory support and can be thought off as a bridge to organ recovery. Since 2009, it has been applied as a rescue treatment for patients with severe adult respiratory distress syndrome (ARDS) mainly due to viral causes. In December 2019, several patients presented with a constellation of symptoms of viral pneumonia in China. A new strain of the corona virus family, called COVID-19, has been discovered to be the cause of this severe mysterious illness that was named severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). This new virus continued to spread across the globe leading to the World Health Organization announcing it as a pandemic in the early 2020. By the end of March 2021, the number of COVID-19 cases worldwide exceeded 126 million cases. In Saudi Arabia, the first confirmed case of COVID-19 was reported in the 2nd March 2020. By the end of March 2021, the total number of confirmed COVID-19 cases in Saudi Arabia is just above 360,000. In anticipation of the need of ECMO for the treatment of patients with SARS‑CoV‑2 based on the previous Middle East respiratory syndrome coronavirus pandemic experience, the Saudi Extra-Corporeal Life Support (ECLS) chapter that is under the umbrella of the Saudi Critical Care Society (SCCS) convened a working group of ECMO experts. The mission of this group was to formulate a guidance for the use of ECMO as a last resort for patients with severe ARDS, especially with COVID-19 based on available evidence. The ECLS-SCCS chapter wanted to generate a document that can be used to simple guide, with a focus on safety, to provide ECMO service for patients with severe ARDS with a special focus on SARS‑CoV‑2.

Challenges and Adaptation in Otorhinolaryngology Practice During Pandemic Lockdown: Experience from a Malaysian COVID-19 Hospital.

COVID-19 has taken the world by storm: since the first few cases appeared in Wuhan, China in December 2019 and by June 2020 there were more than 10 million cases of COVID-19 cases worldwide. Malaysia had its first case in January 2020 and acted promptly by implementing several drastic measures to contain the disease. Subsequently, the Ministry of Health Malaysia has implemented guidelines and recommendations on the management of COVID-19. The Department of Otorhinolaryngology-Head and Neck Surgery (ORL-HNS) provides services for patients with ear, nose, throat, head and neck diseases and provides audiology, speech and language therapy, as well as undergraduate and postgraduate training. As the department’s staff is heavily involved in examinations and interventions of upper aerodigestive tract problems, the challenges are distinctly different from other specialties. This article discusses how COVID-19 affected ORL-HNS services and what measures were taken in Hospital Melaka, Malaysia.

Bots and Misinformation Spread on Social Media: Implications for COVID-19.

As of March 2021, the SARS-CoV-2 virus has been responsible for over 115 million cases of COVID-19 worldwide, resulting in over 2.5 million deaths. As the virus spread exponentially, so did its media coverage, resulting in a proliferation of conflicting information on social media platformsa so-called infodemic. In this viewpoint, we survey past literature investigating the role of automated accounts, or bots, in spreading such misinformation, drawing connections to the COVID-19 pandemic. We also review strategies used by bots to spread (mis)information and examine the potential origins of bots. We conclude by conducting and presenting a secondary analysis of data sets of known bots in which we find that up to 66% of bots are discussing COVID-19. The proliferation of COVID-19 (mis)information by bots, coupled with human susceptibility to believing and sharing misinformation, may well impact the course of the pandemic.

Blockchain-Federated-Learning and Deep Learning Models for COVID-19 Detection Using CT Imaging.

With the increase of COVID-19 cases worldwide, an effective way is required to diagnose COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage and reliability of testing kits, due to the quick spread of the virus, medical practitioners are facing difficulty in identifying the positive cases. The second real-world problem is to share the data among the hospitals globally while keeping in view the privacy concerns of the organizations. Building a collaborative model and preserving privacy are the major concerns for training a global deep learning model. This paper proposes a framework that collects a small amount of data from different sources (various hospitals) and trains a global deep learning model using blockchain-based federated learning. Blockchain technology authenticates the data and federated learning trains the model globally while preserving the privacy of the organization. First, we propose a data normalization technique that deals with the heterogeneity of data as the data is gathered from different hospitals having different kinds of Computed Tomography (CT) scanners. Secondly, we use Capsule Network-based segmentation and classification to detect COVID-19 patients. Thirdly, we design a method that can collaboratively train a global model using blockchain technology with federated learning while preserving privacy. Additionally, we collected real-life COVID-19 patients’ data open to the research community. The proposed framework can utilize up-to-date data which improves the recognition of CT images. Finally, we conducted comprehensive experiments to validate the proposed method. Our results demonstrate better performance for detecting COVID-19 patients.

SARS-CoV-2 genomic surveillance in Costa Rica: Evidence of a divergent population and an increased detection of a spike T1117I mutation.

Genome sequencing is a key strategy in the surveillance of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Latin America is the hardest-hit region of the world, accumulating almost 20% of COVID-19 cases worldwide. In Costa Rica, from the first detected case on March 6th to December 31st almost 170,000 cases have been reported. We analyzed the genomic variability during the SARS-CoV-2 pandemic in Costa Rica using 185 sequences, 52 from the first months of the pandemic, and 133 from the current wave.Three GISAID clades (G, GH, and GR) and three PANGOLIN lineages (B.1, B.1.1, and B.1.291) were predominant, suggesting multiple re-introductions from other regions. The whole-genome variant calling analysis identified a total of 283 distinct nucleotide variants, following a power-law distribution with 190 single nucleotide mutations in a single sequence, and only 16 mutations were found in >5% sequences. These mutations were distributed through the whole genome. The prevalence of worldwide-found variant D614G in the Spike (98.9% in Costa Rica), ORF8 L84S (1.1%) is similar to what is found elsewhere. Interestingly, the frequency of mutation T1117I in the Spike has increased during the current pandemic wave beginning in May 2020 in Costa Rica, reaching 29.2% detection in the full genome analyses in November 2020. This variant has been observed in less than 1% of the GISAID reported sequences worldwide in 2020. Structural modeling of the Spike protein with the T1117I mutation suggests a potential effect on the viral oligomerization needed for cell infection, but no differences with other genomes on transmissibility, severity nor vaccine effectiveness are predicted.In conclusion, genome analyses of the SARS-CoV-2 sequences over the course of the COVID-19 pandemic in Costa Rica suggest the introduction of lineages from other countries and the detection of mutations in line with other studies, but pointing out the local increase in the detection of Spike-T1117I variant. The genomic features of this virus need to be monitored and studied in further analyses as part of the surveillance program during the pandemic.

Genetic variability in COVID-19-related genes in the Brazilian population

SARS-CoV-2 utilizes the angiotensin-converting enzyme 2 (ACE2) receptor and transmembrane serine protease (TMPRSS2) to infect human lung cells. Previous studies have suggested that different host ACE2 and TMPRSS2 genetic backgrounds might contribute to differences in the rate of SARS-CoV-2 infection or COVID-19 severity. Recent studies have also shown that variants in 15 genes related to type I interferon immunity to influenza virus might predispose patients toward life-threatening COVID-19 pneumonia. Other genes (SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, IL6, CTSL, ABO, and FURIN) and HLA alleles have also been implicated in the response to infection with SARS-CoV-2. Currently, Brazil has recorded the third-highest number of COVID-19 cases worldwide. We aimed to investigate the genetic variation present in COVID-19-related genes in the Brazilian population. We analyzed 27 candidate genes and HLA alleles in 954 admixed Brazilian exomes. We used the information available in two public databases (http://www.bipmed.org and http://abraom.ib.usp.br/) and additional exomes from individuals born in southeast Brazil, the region of the country with the highest number of COVID-19 patients. Variant allele frequencies were compared with the 1000 Genomes Project phase 3 (1KGP) and gnomAD databases. We detected 395 nonsynonymous variants; of these, 325 were also found in the 1KGP and/or gnomAD. Six of these variants were previously reported to influence the rate of infection or clinical prognosis of COVID-19. The remaining 70 variants were identified exclusively in the Brazilian sample, with a mean allele frequency of 0.0025. In silico analysis revealed that seven of these variants are predicted to affect protein function. Furthermore, we identified HLA alleles previously associated with the COVID-19 response at loci DQB1 and DRB1. Our results showed genetic variability common to other populations and rare and ultrarare variants exclusively found in the Brazilian population. These findings might lead to differences in the rate of infection or response to infection by SARS-CoV-2 and should be further investigated in patients with this disease.

Analyzing Cross-country Pandemic Connectedness During COVID-19 Using a Spatial-Temporal Database: Network Analysis.

Communicable diseases including COVID-19 pose a major threat to public health worldwide. To curb the spread of communicable diseases effectively, timely surveillance and prediction of the risk of pandemics are essential. The aim of this study is to analyze free and publicly available data to construct useful travel data records for network statistics other than common descriptive statistics. This study describes analytical findings of time-series plots and spatial-temporal maps to illustrate or visualize pandemic connectedness. We analyzed data retrieved from the web-based Collaborative Arrangement for the Prevention and Management of Public Health Events in Civil Aviation dashboard, which contains up-to-date and comprehensive meta-information on civil flights from 193 national governments in accordance with the airport, country, city, latitude, and the longitude of flight origin and the destination. We used the database to visualize pandemic connectedness through the workflow of travel data collection, network construction, data aggregation, travel statistics calculation, and visualization with time-series plots and spatial-temporal maps. We observed similar patterns in the time-series plots of worldwide daily flights from January to early-March of 2019 and 2020. A sharp reduction in the number of daily flights recorded in mid-March 2020 was likely related to large-scale air travel restrictions owing to the COVID-19 pandemic. The levels of connectedness between places are strong indicators of the risk of a pandemic. Since the initial reports of COVID-19 cases worldwide, a high network density and reciprocity in early-March 2020 served as early signals of the COVID-19 pandemic and were associated with the rapid increase in COVID-19 cases in mid-March 2020. The spatial-temporal map of connectedness in Europe on March 13, 2020, shows the highest level of connectedness among European countries, which reflected severe outbreaks of COVID-19 in late March and early April of 2020. As a quality control measure, we used the aggregated numbers of international flights from April to October 2020 to compare the number of international flights officially reported by the International Civil Aviation Organization with the data collected from the Collaborative Arrangement for the Prevention and Management of Public Health Events in Civil Aviation dashboard, and we observed high consistency between the 2 data sets. The flexible design of the database provides users access to network connectedness at different periods, places, and spatial levels through various network statistics calculation methods in accordance with their needs. The analysis can facilitate early recognition of the risk of a current communicable disease pandemic and newly emerging communicable diseases in the future.

SARS-CoV-2 Infection in Ivory Coast: A Serosurveillance Survey among Gold Mine Workers.

ABSTRACTOf the 107 million COVID-19 cases worldwide, less than 2 million have been reported in African countries. The aim of this study was to evaluate the seroprevalence of SARS-CoV-2 infection in Ivory Coast mine workers. From July 15 to October 13, 2020, a voluntary serological test campaign was conducted in 3 sites: two gold mines, and the headquarters in Abidjan. Rapid tests to detect IgG and IgM on capillary blood were performed. To identify independent sociodemographic characteristics associated with a higher SARS-CoV-2 seroprevalence rate, a multivariate logistic regression analysis was performed. A total of 1,687 subjects were tested; 91% were male (n = 1,536), and the mean age was 37 years. The overall seroprevalence was 25.1% (n = 422), ranging between 13.6% (11.2–16.1%), 34.4% (31.1–37.7%), and 34.7% (26.2–43.2%) in mine A, in mine B, and in Abidjan, respectively. Among the 422 seropositive subjects, 74 reported mild symptoms in the three previous months and one was hospitalized for severe COVID-19 infection. SARS-CoV-2 seroprevalence is high in both gold miners and administrative staff working in Ivory Coast. The burden of infection in West Africa has probably been underestimated till now.

1,2,3,4,6-Pentagalloyl Glucose, a RBD-ACE2 Binding Inhibitor to Prevent SARS-CoV-2 Infection.

The outbreak of SARS-CoV-2 virus caused more than 80,155,187 confirmed COVID-19 cases worldwide, which has posed a serious threat to global public health and the economy. The development of vaccines and discovery of novel drugs for COVID-19 are urgently needed. Although the FDA-approved SARS-CoV-2 vaccines has been launched in many countries recently, the strength of safety, stringent storage condition and the possibly short-term immunized efficacy remain as the major challenges in the popularity and recognition of using vaccines against SARS-CoV-2. With the spike-receptor binding domain (RBD) of SARS-CoV-2 being responsible for binding to human angiotensin-converting enzyme 2 receptor (hACE2), ACE2 is identified as the receptor for the entry and viral infection of SARS-CoV-2. In this study, molecular docking and biolayer interferometry (BLI) binding assay were adopted to determine the direct molecular interactions between natural small-molecule, 1,2,3,4,6-Pentagalloyl glucose (PGG) and the spike-RBD of the SARS-CoV-2. Our results showed that PGG preferentially binds to a pocket that contains residues Glu 340 to Lys 356 of spike-RBD with a relatively low binding energy of -8 kcal/mol. BLI assay further confirmed that PGG exhibits a relatively strong binding affinity to SARS-CoV-2-RBD protein in comparison to hACE2. In addition, both ELISA and immunocytochemistry assay proved that PGG blocks SARS-CoV-2-RBD binding to hACE2 dose dependently in cellular level. Notably, PGG was confirmed to abolish the infectious property of RBD-pseudotyped lentivirus in hACE2 overexpressing HEK293 cells, which mimicked the entry of wild type SARS-CoV-2 virus in human host cells. Finally, maximal tolerated dose (MTD) studies revealed that up to 200 mg/kg/day of PGG was confirmed orally safe in mice. Our findings suggest that PGG may be a safe and potential antiviral agent against the COVID-19 by blockade the fusion of SARS-CoV-2 spike-RBD to hACE2 receptors. Therefore, PGG may be considered as a safe and natural antiviral agent for its possible preventive application in daily anti-virus hygienic products such as a disinfectant spray or face mask.

CoVNet-19: A Deep Learning model for the detection and analysis of COVID-19 patients

Background:The ongoing fight with Novel Corona Virus, getting quick treatment, and rapid diagnosis reports have become an act of high priority. With millions getting infected daily and a fatality rate of 2%, we made it our motive to contribute a little to solve this real-world problem by accomplishing a significant and substantial method for diagnosing COVID-19 patients. Aim:The Exponential growth of COVID-19 cases worldwide has severely affected the health care system of highly populated countries due to proportionally a smaller number of medical practitioners, testing kits, and other resources, thus becoming essential to identify the infected people. Catering to the above problems, the purpose of this paper is to formulate an accurate, efficient, and time-saving method for detecting positive corona patients. Method:In this paper, an Ensemble Deep Convolution Neural Network model “CoVNet-19” is being proposed that can unveil important diagnostic characteristics to find COVID-19 infected patients using X-ray images chest and help radiologists and medical experts to fight this pandemic. Results:The experimental results clearly show that the overall classification accuracy obtained with the proposed approach for three-class classification among COVID-19, Pneumonia, and Normal is 98.28%, along with an average precision and Recall of 98.33% and 98.33%, respectively. Besides this, for binary classification between Non-COVID and COVID Chest X-ray images, an overall accuracy of 99.71% was obtained. Conclusion:Having a high diagnostic accuracy, our proposed ensemble Deep Learning classification model can be a productive and substantial contribution to detecting COVID-19 infected patients.

A COVID-19 Obituary.

I read obituaries. I read obituaries every day. I have read obituaries every day since I was 11 years old. I wake up in the morning, and before I start my day I go to the front door, open it, and retrieve the New York Times that has been delivered to my home. I retreat to the bathroom and I open the paper to read the obituaries. Before I dress. Before my coffee. Before breakfast. I read obituaries. I check the ages of those who have died. 98, 102, and 89, perhaps there is hope. 62, 49, and 34, looks like it will be a bad day. I read the causes and circumstances of death. Died in his sleep of natural causes — a sigh of relief. I notice so many more musicians and artists and drummers for obscure rock groups of the 60s seem to die and get featured obituaries than doctors, psychiatrists, psychologists, and palliative care clinicians. Perhaps it’s a biased sample — those people who get that special obituary for noteworthy deaths with that special picture when they were younger in their prime. Why do I read obituaries so compulsively? Well, the answer is of course multi-layered. On the most accessible level, I am fascinated by the stories of peoples lives. The narratives of lives lived in all their variety, length, scope, and focus. They are dramas that have the potential to aid us all in the search for who we want to become and examples to measure ourselves against. As the Talmud taught us, “What is truer than the truth? The story.” However, on a perhaps deeper level, reading obituaries, for me, is an inquiry in how to create an attitude and a perspective to death. It is a re-confirmation, each day, that death is real, an inevitable part of life, and that, in fact, we live with death every moment. In creating the story of our life, we create a story of a life lived and a death that is ever present and can occur at any moment. It is a reminder that death is at the essence of life, reconfirms life, and that death punctuates life. Reading obituaries allows me to maintain a sense of mortality salience as I live each moment of life. Death is always present in our lives. It is a constant. But now, in the Age of the COVID-19 pandemic, death is even more constantly present. In fact, there are more deaths each day, and more deaths this past year, that at any time in our recent history. It is January 22, 2021, 1 year since the start of this global pandemic. The COVID-19 pandemic “Numbers” are unfathomable: 100 million COVID-19 cases worldwide and 2.1 million deaths globally. In the United States alone, we have almost 24 million COVID-19 cases and more than 420,000 deaths. This excess mortality due to COVID-19 has resulted in more obituaries being printed in our newspapers than at any time in the recent past. And so I am reading more obituaries; more COVID-19 obituaries.

Meteorological parameters and air pollutants affect the transmission of COVID-19: a review

In less than a year, experimental body explaining the relationship of meteorological indicators, air pollutants concentration, and COVID-19 disease rapidly increases. Among studies, inconclusive findings are conflicting and therefore need to be gathered in a systematically review methods. Therefore, systematic literature review is conducted to present available studies concerning the effect of climatic parameters and air pollutants and their association with COVID-19 pandemic. Search strategy was conducted using Science Direct with terms of “COVID-19”, “environment”, “meteorology”, and “pollutants”. After critically assessed with inclusion criteria, 23 studies met to be included in the database. Results indicate that temperature and humidity are not directly correlated with the growth of COVID-19 cases worldwide. Although multi-regional studies mostly revealed significant correlation with individual parameter of meteorological factors, dynamics data of COVID-19 transmission may be a factor causing the different results. On the other hand, irrespective with lockdown scheme, air pollutants are likely affecting the spread of the pathogens through several mode of actions which most of available explanation is that the SAR-Cov-2 virus can create a cluster with particular matter on the air. Thus, lower air quality index in association with wind speed, in particular condition, can potentially increase the transmission of COVID-19. This study emphasizes that there are many other factors that more logically transmitting the SAR-CoV-2 virus such as human mobility and interaction.

Auditing in the Era of the COVID-19 Pandemic: A Discussion of Challenges and Key Matters

As of the beginning of November 2020, the number of COVID-19 cases worldwide has approached 47 million cases. In the United States, there have been over nine million COVID-19 cases, and the death toll is approaching 232,000 deaths. The pandemic has negatively affected the economy, unemployment rates, and the performance of many industry sectors. Despite the adversities of COVID-19, stakeholders need external auditors to continue providing high-quality assurance work. We discuss the challenges and key matters that external auditors face due to the pandemic. We provide thoughts and suggestions for auditors to consider. Additionally, we propose some research ideas for academic researchers to advance in the future. The topics that we emphasize include remote auditing, scope limitations, auditing inventory, disclosures on risks and uncertainties, subsequent events, going concern opinions, internal controls, and fraud risk. This article should be informative to audit practitioners, corporate stakeholders, and academic researchers. External auditing will continue to play a crucial role in the functioning of the capital markets. It is essential to gather and disseminate knowledge about how auditors can remain effective and resilient during even the most strenuous times.

On Cloud Analytical Database Management Systems Suitable for Data Intensive Biomedical Related Research

Per to Worldometer [1], as of mid-December 2020, there are more than 77 million Covid-19 cases worldwide with more than 1.7 million deaths worldwide. Unfortunately, with the second wave hitting many countries, positive cases are increasing rapidly at astonishing rates. Along with that, a large amount of data, both directly and indirectly related to Covid-19, is generated ready to be minded supporting decision makers, scientists, corporations, drug makers, etc. [2]. Two immediate questions naturally would be (2) where we should store the data and (2) what Database Management Systems (DBMS) we should use to analyze the data? To benefit from easy access and to accommodate sharp growth in data volume, it is hard to dispute that the data should be stored in the cloud. In this position paper, we will present our recommendations based on our more than five years of using different Analytical DBMS (ADBMS, also called data warehouses in many articles), which we will discuss briefly next.

Clinical Skills Updated During the Pandemic

At the time of writing this article, we are at 23 Million COVID19 cases worldwide, with just over 800,000 dead (Coronavirus Update (Live): WorldoMeter, 2020). The word Pandemic is becoming an idiom synonymous with a crisis that is shaping global healthcare systems. It shouldn’t be a word to describe solely the current epoch rather, how it will shape the societies of the future. Similarly, to when the term once had a different meaning “pandemos’’, meaning “all the people’’. The Greek physician Hippocrates became the first to give this term a medical association. Society as we know it is slowly morphing and adapting to a state of existence never anticipated before. This showcases the strength of mankind that is, adapting to changing environments. If we are good at one thing, this is it: our resilience and primordial genes assist us to adapt around situations and scenarios to continue to build ourselves and others, for mutual merit or for crafty degeneration. Ever since the efforts in Wuhan to combat the virus circulated across the internet, healthcare professionals have been applying their knowledge and skillsets in a new environment and at pace which has never been programmed into a clinical skills training session. A new dimension to the practice of medicine was emerging in the harshest conditions known to healthcare professionals. Extremely long hours and the inadequacies of personal protective equipment’s, not only tested the tangible manufacturer’s capacity of producing protective materials under huge demand, but also the true grit of each and every individual who worked in a hospital and especially the ones that were at the bedside of a deteriorating Covid-19 patient.

Tackling COVID-19 in Resource-Constrained Settings: Experiences from India and Vietnam

SARS-CoV-2 is a novel strain of the large family of respiratory coronaviruses. It gives rise to a highly contagious disease (COVID-19) transmitted via droplets and close contact. First discovered in Wuhan, China, it rapidly spread across continents and was soon declared a global pandemic. Though majority of people do not develop critical symptoms, many have experienced severe diseases that resulted in hospitalization and death. The millions of COVID-19 cases worldwide means that even a small percentage of critical patients still makes for a large number, potentially placing healthcare systems on the brink of collapse. Consequently, countries began implementing various preventive strategies, prior to the availability of vaccines, to reduce transmission rates. These are categorized into three stages: testing, containment, and mitigation. Testing allows for identification of infections, containment aims to effectively trace and isolate those infected, and mitigation is to slow wider spread of the virus. This paper will discuss the initial COVID-19 responses of India and Vietnam based on these stages as well as how their domestic contexts may have influenced their outcomes. Both are low-resource Asian countries predicted to be amongst the hardest-hit. Nonetheless, despite having similar interventions, while Vietnam became one of the most successful at controlling the pandemic, India’s efforts fell short, resulting in substantial shortages and massive human tragedies. This highlights how pandemic response is a multi-faceted and context-specific process. Hence, examining public health responses in the context of India and Vietnam will contribute to and improve global knowledge of infection control in diverse settings.

Analysis of Promising Approaches to COVID-19 Vaccine Development

The number of confirmed COVID-19 cases worldwide amounted to 50 million at the beginning of November 2020. This is clearly not enough for the formation of herd immunity, which will prevent repeated outbreaks of the disease. Quarantine measures can only curb the spread of the disease to some extent, therefore specific preventive measures are needed to create collective immunity to COVID-19.The underlying principle of collective immunity is indirect protection of the whole of the population by immunising a certain part of it. Vaccination is the most effective approach to prevention of epidemic outbreaks. The aim of the study was to analyse promising approaches to the development of vaccines against novel coronavirus COVID-19 infection. The paper summarises data on development studies and clinical trials of COVID-19 vaccines conducted in different countries. It analyses the pros and cons of different platforms for vaccine development (attenuated vaccines, inactivated vaccines, subunit vaccines, DNA and RNA vaccines, recombinant vector vaccines). The paper presents a potential design of novel vaccines. It was concluded that COVID-19 vaccines might be developed both for immunising high-risk groups and for mass immunisation. An optimal solution for the second task would be to develop human or monkey adenovirus vector-based vaccines whose mass production has already been unveiled.

Catheter directed pulmonary artery thrombolysis in a Covid-19 positive patient with massive pulmonary embolism

Thromboembolic complications are common complications amongst cases of COVID-19 worldwide. This occurrence has seen a key role of endovascular treatment in managing this potentially fatal complication. Endovascular thrombectomy or catheter directed thrombolysis is a fast and effective method for treatment of pulmonary embolisms, especially in the setting of a pandemic. However, good workflow and safety measures should be strictly adhered to ensure a favorable outcome of patients and ensure safety of treating personnel.

The COVID-19 Pandemic and Bankruptcies of Retail Companies: An Initial Look

As of mid-October 2020, the number of COVID-19 cases worldwide has approached 38 million cases. In the United States (U.S.) alone, as of mid-October 2020, there have been over 7.8 million COVID-19 cases and over 215,000 deaths1. The negative economic consequences of the COVID-19 pandemic have been considerable. The Bureau of Economic Analysis (BEA) informs that U.S. real gross domestic product (GDP) decreased five percent in the first quarter of 2020 (BEA 2020) [1]. GDP decreased even further at an annual rate of 31.7 percent in the second quarter of 2020, based on the second estimate given by the BEA. Numerous news outlets reported that the 31.7 percent decline represents the worst quarterly contraction in the U.S. economy ever recorded.

Animals and SARS-CoV-2: Species susceptibility and viral transmission in experimental and natural conditions, and the potential implications for community transmission.

The current COVID‐19 global pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) of probable bat origin, has highlighted the ongoing need for a One Health response to emerging zoonotic disease events. Understanding the human–animal interface and its relevance to disease transmission remains a critical control point for many emerging zoonoses. Determination of the susceptibility of various animal species to infection with SARS‐CoV‐2 and the role of animals in the epidemiology of the disease will be critical to informing appropriate human and veterinary public health responses to this pandemic. A scoping literature review was conducted to collect, evaluate and present the available research evidence regarding SARS‐CoV‐2 infections in animals. Experimental studies have successfully demonstrated SARS‐CoV‐2 infection and transmission in cats, ferrets, hamsters, bats and non‐human primates under experimental settings. Dogs appear to have limited susceptibility to SARS‐CoV‐2, while other domestic species including pigs and poultry do not appear susceptible. Naturally occurring SARS‐CoV‐2 infections in animals appear uncommon, with 14 pets, 8 captive big cats and an unreported number of farmed mink testing positive at the time of writing (early July 2020). Infections typically appear asymptomatic in dogs, while clinical signs of respiratory and/or gastrointestinal disease tend to be mild to moderate in felines, and severe to fatal in mink. Most animals are presumed to have been infected by close contact with COVID‐19 patients. In domestic settings, viral transmission is self‐limiting; however in high‐density animal environments, there can be sustained between‐animal transmission. To date, two potential cases of animal‐to‐human transmission are being investigated, on infected mink farms. Given the millions of COVID‐19 cases worldwide and ongoing potential for further zoonotic and anthroponotic viral transmission, further research and surveillance activities are needed to definitively determine the role of animals in community transmission of SARS‐CoV‐2.