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1.
Preprint | EuropePMC | ID: ppcovidwho-291209

ABSTRACT

The outbreak of a novel coronavirus (SARS-CoV-2) in many countries in the world from late 2019 to 2020 resulted in millions of infected people, and caused serious damage to the social environments with significant changes in human power and material resources in the world. The novel coronavirus is an RNA virus. RNA mutation is common in nature. This makes it extremely difficult to develop a virus vaccine in a short period. The evolution of the virus has been in a mutation state, in which a certain sequence changes associated with time and environments in similar distributions. A larger number of genomes were collected in various open source databases for scientists in further explorations. In this paper, a 2D similarity comparison scheme on the A2 module of the MAS is proposed for extracting internal information among a genome undertaken M segment partitions to provide visual results based on probability measures and quantitative statistics. First, a genome is segmented into corresponding numerical transformations, and then four numbers of meta symbols in each segment are counted. Corresponding probability measures are calculated. Second, the probability is transformed into polar coordinates, and the polar coordinates are mapped into a M × M matrix. Then, a 1D genome can be processed into 2D measures with similarity properties in sequence. Through this correlation matrix, relevant similarity results are analyzed.

2.
Preprint in English | EuropePMC | ID: ppcovidwho-291208

ABSTRACT

COVID-19 triggered by SARS-CoV-2 has become a common problem faced by people all over the world. With the development of bioinformatics and the breakthrough progress of gene technologies. It is a challenging topic to use genomic datasets for SARS-CoV-2 research. In this paper, a 3D visualization method is pro-posed to show the A9 module of the metagenomic analysis system MAS. Seven coronaviruses of genera were illustrated and briefly analyzed. Comparing the visualization results, various SARS-CoV-2 genomes were represented as 2D and 3D maps under different conditions. Through related specific projections, the characteristics of the coronavirus can be observed intuitively from the projection results to provide an effective viewpoint for studying viral genomes.

3.
Preprint in English | EuropePMC | ID: ppcovidwho-291207

ABSTRACT

Since the emergence of Corona Virus Disease 2019 (COVID-19) in Wuhan city, Hubei Province, China, it has caused thousands of deaths. As the ongoing outbreak of COVID-19 around the world, the number of deaths will definitely continue to increase. We aimed to further describe the clinical characteristics of dead cases with COVID-19 through a large sample and multi-centered study and to find some clinical predictors for the deterioration of COVID-19 during the process. Methods One hundred and seven patients (16 patients from Lei Shen-Shan Hospital, 54 patients from Seventh Hospital of Wuhan and 37 patients from Zhongnan Hospital of Wuhan University) with COVID-19 were enrolled in our research from Jan 22 to Feb 29, 2020. The demographic, clinical, radiological, laboratory and treatment data of all cases were analysed. Results Of the 107 dead patients with COVID-19, 71 (66.4%) were male and 36 (33.6%) were female. The mean age of the patients was 71.2 ± 12.1 years. 82 (76.6%) of patients had chronic diseases. The mean duration from admission to death was 9 (IQR,5-14) days. Respiratory functional damage was the most common one followed by heart and kidney. Hematuria was found in 36(33.6%) patients. 89(83.2%) patients’ albumin levels were decreased. 68(63.6%) patients had anemia. concerning laboratory results, 55 (69.6%) and 56 (70.1%) patients have the elevated white blood cells and elevated Neutrophils during the process;only 43 (54.4%) have the decreased Lymphocytes;The values of platelets and haemoglobin decreased in 64(81.0%) and 58 (73.4%) patients. Alanine aminotransferase and aspartate aminotransferase elevated in near half of patients, while almost 80% of patients have the decreased albumin. The elevated blood urea nitrogen and cystatin C were manifested in about 70% of patients. Procalcitonin was elevated in 38 (71.7%) patients. Conclusions In conclusion, the older men with chronic diseases are more likely to die from COVID-19. Apart from that, more attention should be pay on timely treatment, coinfections, malnutrition, and dysfunction of kidney and coagulation. The rising values (white blood cell, blood urea nitrogen, cystatin C, PCT and PT) and the decreased values (PLT, Hb and albumin) maybe meaningful for predict the poor prognosis.

4.
Preprint in English | EuropePMC | ID: ppcovidwho-291206

ABSTRACT

The novel coronavirus (COVID-19) pandemic started in December 2019 in Wuhan (Hubei, China) and spread rapidly;therefore, it is essential to detect the disease at an early stage and immediately isolate the infected patients [1]. The most common symptoms of COVID-19 infection include fever, asthenia, cough and dyspnea [2]. However, some patients are asymptomatic from the respiratory symptoms, and may only present abdominal manifestations as an initial finding, what creates a diagnostic challenge.We describe two cases with diagnostic confirmations of COVID-19 who showed up at the Emergency Department with abdominal symptoms before presenting respiratory manifestations, and who had their initial suspicion based on the findings of the thoracoabdominal transition, demonstrating the importance of an adequate assessment of the lung base images.

5.
Preprint in English | EuropePMC | ID: ppcovidwho-291205

ABSTRACT

Background: The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread all over the world. The specific information about immunity of non-survivors with COVID-19 is scarce. We aimed to describe the clinical characteristics and abnormal immunity of the confirmed COVID-19 non-survivors. Methods: In this single-centered, retrospective, observational study, we enrolled 125 patients with COVID-19 who were died between Jan, 13 and Mar 4, 2020 from Renmin Hospital of Wuhan University. 414 randomly recruited patients with confirmed COVID-19 who were discharged from the same hospital during the same period served as control. Demographic and clinical characteristics, laboratory findings and chest computed tomograph results at admission, and treatment were collected. The immunity-related risk factors associated with in-hospital death were detected. Results: Non-survivors were older than survivors. More than half of non-survivors was male. Nearly half of the patients had chronic medical illness. The common signs and symptoms at admission of non-survivors were fever. Non-survivors had higher white blood cell (WBC) count, more elevated neutrophil count, lower lymphocytes and platelete count, raised concentration of procalcitonin and C-reactive protein (CRP) than survivors. The levels of CD3 + T cells, CD4 + T cells, CD8 + T cells, CD19 + T cells, and CD16 + 56 + T cells were significantly decreased in non-survivors when compared with survivors. The concentrations of immunoglobulins (Ig) G, IgA and IgE were increased, whereas the levels of complement proteins (C)3 and C4 were decreased in non-survivors when compared with survivors. Non-survivors presented lower levels of oximetry saturation at rest and lactate. Old age, comorbidity of malignant tumour, neutrophilia, lymphocytopenia, low CD4 + T cells, decreased C3, and low oximetry saturation were the risk factors of death in patients with confirmed COVID-19. The frequency of CD4 + T cells positively correlated with the numbers of lymphocytes and the level of oximetry saturation, whereas CD4 + T cells were negatively correlated with age and the numbers of neutrophils. Conclusion: Abnormal cellular immunity and humoral immunity were considerable in non-survivors with COVID-19. Neutrophilia, lymphocytopenia, low CD4 + T cells, and decreased C3 were the immunity-related risk factors predicting mortality of patients with COVID-19.

6.
Preprint in English | EuropePMC | ID: ppcovidwho-291204

ABSTRACT

A novel coronavirus (2019-nCoV) that is initially found to trigger human severe respiratory illness in Wuhan City of China, 2019, has been recognized as a public health emergency of international concern. In the past two months, this deadly agent has caused 77,785 cases with 2,666 deaths via rapid person-to-person transmission and reached at least 25 countries. However, its evolutionary origin is poorly understood. Here we show integrative evidence that 2019-nCoV is a possible progenitor for SARS-CoV with bat origin. Our finding underscores the importance of tracing origin in the efficient monitoring, and effectively preventing the interspecies transmission of such emerging/re-emerging coronaviruses.

7.
Preprint in English | EuropePMC | ID: ppcovidwho-291203

ABSTRACT

COVID-19 is outbreaking in worldwide. It caused millions of infections, killing hundreds of thousands of people and making all countries loss immeasurable trade. For finding the secret of SARS-CoV-2, researchers need to analyze various variation information such as multiple coronaviruses in different times over distinct countries. In this paper, the metagenetic analysis system MAS is used to analyze SARS-CoV-2 genomes collected from different countries as input datasets, and special genomic indices are provided to be a global characteristic quantity based on the A1 and C1 modules of the MAS for visualizations. In this method, one RNA sequence is split into M segments and counting the number of genetic probability measures for 16 combinations of four genomic symbols. After statistical probability processes, each probability distribution can be transferred into an entropy quantity on both 2D and 1D histograms to show these results for all collected genomes. Under this approach, a pair of combinatorial entropies determine a 2D genomic index map to generate a heatmap for more massive clusters of genomes with similarity contents to provide basic quantitative in variants to organize further collected genomes as a construction of a phylogenetic tree. Further explorations are required.

8.
Preprint in English | EuropePMC | ID: ppcovidwho-291202

ABSTRACT

Research significance: The extended version of this paper has been accepted by IEEE Internet of Things journal (DOI: 10.1109/JIOT.2020.2991456), please cite the journal version. During the epidemic prevention and control period, our study can be helpful in prognosis, diagnosis and screening for the patients infected with COVID-19 (the novel coronavirus) based on breathing characteristics. According to the latest clinical research, the respiratory pattern of COVID-19 is different from the respiratory patterns of flu and the common cold. One significant symptom that occurs in the COVID-19 is Tachypnea. People infected with COVID-19 have more rapid respiration. Our study can be utilized to distinguish various respiratory patterns and our device can be preliminarily put to practical use. Demo videos of this method working in situations of one subject and two subjects can be downloaded online. Research details: Accurate detection of the unexpected abnormal respiratory pattern of people in a remote and unobtrusive manner has great significance. In this work, we innovatively capitalize on depth camera and deep learning to achieve this goal. The challenges in this task are twofold: the amount of real-world data is not enough for training to get the deep model;and the intra-class variation of different types of respiratory patterns is large and the outer-class variation is small. In this paper, considering the characteristics of actual respiratory signals, a novel and efficient Respiratory Simulation Model (RSM) is first proposed to fill the gap between the large amount of training data and scarce real-world data. The proposed deep model and the modeling ideas have the great potential to be extended to large scale applications such as public places, sleep scenario, and office environment.

9.
Preprint in English | EuropePMC | ID: ppcovidwho-291201

ABSTRACT

A 1900-2016 time series model predicts former Vice President Joe Biden will win 55.44 percent of the 2020 US presidential popular vote. A change in party control of the U.S. House of Representatives two years before a presidential election has a significant coefficient to explain the popular vote that has not been explored in the past 25 years. A cross-section 50 state Electoral College probit model projects President Trump’s reelection, winning 26 states with 279 electoral votes while Biden receives 259. These popular vote and electoral vote forecasts surely have wide discrepancies. Biden is forecast to win the Electoral College vote under several circumstances. If he wins Wisconsin’s 10 electoral votes, which are predicted for Trump, the candidates could tie with 269 electoral votes and the House of Representatives would select the president. Biden would be elected if he wins Wisconsin and the popular vote in one Congressional district in Nebraska or both districts in Maine. Biden could win with victories in several states where he is forecast to lose close contests. Numbers of COVID-19 virus cases and deaths are not highly correlated with states where Trump is projected to win. The effects of factors such as the President’s health and candidates’ closing campaign behavior cannot be measured. Forecasting US presidential outcomes in the 21st century has become a highly risky activity.

10.
Preprint in English | EuropePMC | ID: ppcovidwho-291200

ABSTRACT

A 1900-2016 time series model predicts former Vice President Joe Biden will win 55.44 percent of the 2020 US presidential popular vote. A change in party control of the U.S. House of Representatives two years before a presidential election has a significant coefficient to explain the popular vote that has not been explored in the past 25 years. A cross-section 50 state Electoral College probit model projects President Trump’s re-election, winning 26 states with 279 electoral votes while Biden receives 259. These popular vote and electoral vote forecasts surely have wide discrepancies.<br><br>Biden is forecast to win the Electoral College vote under several circumstances. If he wins Wisconsin’s 10 electoral votes, which are predicted for Trump, the candidates could tie with 269 electoral votes and the House of Representatives would select the president. Biden would be elected if he wins Wisconsin and the popular vote in one Congressional district in Nebraska or both districts in Maine. Biden could win with victories in several states where he is forecast to lose close contests. Numbers of COVID-19 virus cases and deaths are not highly correlated with states where Trump is projected to win. The effects of factors such as the President’s health and candidates’ closing campaign behavior cannot be measured. Forecasting US presidential outcomes in the 21st century has become a highly risky activity.<br>

11.
Preprint in English | EuropePMC | ID: ppcovidwho-291199

ABSTRACT

Animals like mink, cats and dogs are susceptible to SARS-CoV-2 infection. In the Netherlands, 69 out of 127 mink farms were infected with SARS-CoV-2 between April and November 2020 and all mink on infected farms were culled after SARS-CoV-2 infection to prevent further spread of the virus. On some farms, (feral) cats and dogs were present. This study provides insight into the prevalence of SARS-CoV-2 positive cats and dogs in ten infected mink farms and their possible role in transmission of the virus. Throat and rectal swabs of 101 cats (12 domestic and 89 feral cats) and 13 dogs of ten farms were tested for SARS-CoV-2 using PCR. Serological assays were performed on serum samples from 62 adult cats and all 13 dogs. Whole Genome Sequencing was performed on one cat sample. Cat-to-mink transmission parameters were estimated using data from all ten farms. This study shows evidence of SARS-CoV-2 infection in twelve feral cats and two dogs. Eleven cats (19%) and two dogs (15%) tested serologically positive. Three feral cats (3%) and one dog (8%) tested PCR-positive. The sequence generated from the cat throat swab clustered with mink sequences from the same farm. The calculated rate of mink-to-cat transmission showed that cats on average had a chance of 12% (95%CI 10% to 18%) of becoming infected by mink, assuming no cat-to-cat transmission. As only feral cats were infected it is most likely that infections in cats were initiated by mink, not by humans. Whether both dogs were infected by mink or humans remains inconclusive. This study presents one of the first reports of interspecies transmission of SARS-CoV-2 that does not involve humans, namely mink-to-cat transmission, which should also be considered as a potential risk for spread of SARS-CoV-2.

12.
Preprint in English | EuropePMC | ID: ppcovidwho-291198

ABSTRACT

2020 has been highly affected by the COVID-19 outbreak. The urgent needs for a potent and effective drug for treatment of this malignance put pressure on researchers and scientists worldwide to develop potential drug or a vaccine to resist SARS-CoV-2. We report in this paper the assessment of the efficiency of thirty alkaloid compounds derived from African medicinal plants against the SARS-CoV-2 main protease through molecular docking and bioinformatics approaches. The results reveal four potential inhibitors (ligands 18 , 21 , 23 and 24 ) with the highest binding energies up to 12.26 kcal/mol with good profile of ADMET, as well as fully obey the Lipinski’s rule of five.

13.
Preprint in English | EuropePMC | ID: ppcovidwho-291197

ABSTRACT

COVID-19 clearly dominated many of the pressing issues in the world in 2020 and necessitated changes such as the suspension of wrongful trading provisions to help financially distressed firms and the restriction on share buybacks in the case of the CARES Act in the US for government bail-outs and by the MAS for financial institutions given capital adequacy relief in Singapore. It also brought greater focus back on the real economy as opposed to the over-financialized one that was described in the introduction to this chapter in the previous Annual Review. One positive thing to come out of a pandemic is that it may reduce the inequalities seen in the world since the 1990s, in particular, without the even greater upheaval that has been thought necessary to level society.

14.
Preprint in English | EuropePMC | ID: ppcovidwho-291196

ABSTRACT

We present an automatic COVID1-19 diagnosis framework from lung CT-scan slice images. In this framework, the slice images of a CT-scan volume are first proprocessed using segmentation techniques to filter out images of closed lung, and to remove the useless background. Then a resampling method is used to select one or multiple sets of a fixed number of slice images for training and validation. A 3D CNN network with BERT is used to classify this set of selected slice images. In this network, an embedding feature is also extracted. In cases where there are more than one set of slice images in a volume, the features of all sets are extracted and pooled into a global feature vector for the whole CT-scan volume. A simple multiple-layer perceptron (MLP) network is used to further classify the aggregated feature vector. The models are trained and evaluated on the provided training and validation datasets. On the validation dataset, the accuracy is 0.9278 and the F1 score is 0.9261.

15.
Preprint in English | EuropePMC | ID: ppcovidwho-291195

ABSTRACT

Noncovalent interaction energetics associated with ACE2 affinity differences are investigated using electronic structure methods;Our results were found to challenge previous predictions – claiming a higher affinity for 2019-nCoV compared to SARS-CoV based merely on "chemical intuition". In addition, we demonstrate that a broadly-used classical molecular dynamics force field – MMFF94 – is clearly incapable of reproducing DFT-based noncovalent interaction energetics for the systems at hand (despite being specifically parameterized for van der Waals interactions).

16.
Preprint in English | EuropePMC | ID: ppcovidwho-291194

ABSTRACT

The five-year average tax burden in the UK is now at a 70-year high. The impact and opportunities of Brexit, coupled with the need to revitalise the economy in the wake of the COVID-19 crisis, mean 2021 would be a good time for the government to embark on a tax-cutting programme. This paper analyses twenty taxes that could be scrapped or significantly changed. If carried out, these reforms would simplify the tax system, reduce the overall burden of taxation, and eliminate harmful distortions that stifle the UK’s productivity and prosperity. The TV Licence, Inheritance Tax, Stamp Duty Land Tax, stamp duties on buying shares, Apprenticeship Levy, Vehicle Excise Duty, Capital Gains Tax, the bank surcharge, and duties on alcohol, tobacco, and gambling, could be scrapped. Other property taxes, such as Council Tax, Community Infrastructure Levy, business rates, and affordable housing and other s106 obligations, could be replaced with a single land value tax. Under this proposed system, disincentives for property improvements and housebuilding would be removed. The Climate Change Levy and renewables obligations add economic distortion and complexity to the tax system and could be revamped into either through the Emissions Trading Scheme or a comprehensive carbon tax. Corporation Tax and the Diverted Profit Tax could be replaced with a single tax on capital income administered at the corporate level, similar to how PAYE works on wages. Doing so would promote neutrality between capital income and labour, eliminate the debt-capital bias, and spur productivity growth.

17.
Preprint in English | EuropePMC | ID: ppcovidwho-291193

ABSTRACT

Starting on February 20, 2020, the global stock markets began to suffer the worst decline since the Great Recession in 2008, and the COVID-19 has been widely blamed on the stock market crashes. In this study, we applied the log-periodic power law singularity (LPPLS) methodology based on multilevel time series to unravel the underlying mechanisms of the 2020 global stock market crash by analyzing the trajectories of 10 major stock market indexes from both developed and emergent stock markets, including the S&P 500, DJIA, NASDAQ, FTSE, DAX, NIKKEI, CSI 300, HSI, BSESN, and BOVESPA. In order to effectively distinguish between endogenous crash and exogenous crash, we proposed using the LPPLS confidence indicator as a classification proxy. The results show that the apparent LPPLS bubble patterns of the super-exponential increase, corrected by the accelerating logarithm-periodic oscillations, have indeed presented in the price trajectories of the seven indexes: S&P 500, DJIA, NASDAQ, DAX, CSI 300, BSESN, and BOVESPA, indicating that the large positive bubbles have formed endogenously prior to the 2020 stock market crash, and the subsequent crashes for the seven indexes are endogenous, stemming from the increasingly systemic instability of the stock markets, while the well-known external shocks such as the COVID-19 pandemic etc. only acted as sparks during the 2020 global stock market crash. In contrast, the obvious signatures of the LPPLS model have not been observed in the price trajectories of the three remaining indexes: FTSE, NIKKEI, and HSI, signifying that the crashes in these three indexes are exogenous, stemming from external shocks. The novel classification method of crash types proposed in this study can also be used to analyze regime changes of any price trajectories in global financial markets.

18.
Preprint in English | EuropePMC | ID: ppcovidwho-291192

ABSTRACT

The ability to teach is an attribute of a great leader. During the COVID-19 pandemic, leaders faced new challenges in developing teaching skills that include using video communication technology to engage teams scattered in remote locations. This article contains teaching suggestions for leaders based on experience in teaching business school courses during the pandemic.

19.
Preprint in English | EuropePMC | ID: ppcovidwho-291191

ABSTRACT

Food supply and demand chains are highly sensitive to global shocks. Unstable and sudden food price hikes cause serious malnutrition problems and increase the number of food-insecure people, especially in developing countries. Using FAO Food Price Index (FFPI), this study makes one of the first attempts to utilize monthly observations of FFPI in a dynamic time series ARDL and ARX settings for identifying food price effects of the COVDI 19 infection rates V.s. 2008 global financial crises. Our empirical findings confirm that the pandemic has a mild impact on food prices relative to the 2008 crisis, wherein 1 million new COVID 19 infection cases are associated with an increase of only 0.0509 points in FFPI.

20.
Preprint in English | EuropePMC | ID: ppcovidwho-291190

ABSTRACT

Contact tracing is an important measure to counter the COVID-19 pandemic. In the early phase, many countries employed manual contact tracing to contain the rate of disease spread, however it has many issues. The manual approach is cumbersome, time consuming and also requires active participation of a large number of people to realize it. In order to overcome these drawbacks, digital contact tracing has been proposed that typically involves deploying a contact tracing application on people's mobile devices which can track their movements and close social interactions. While studies suggest that digital contact tracing is more effective than manual contact tracing, it has been observed that higher adoption rates of the contact tracing app may result in a better controlled epidemic. This also increases the confidence in the accuracy of the collected data and the subsequent analytics. One key reason for low adoption rate of contact tracing applications is the concern about individual privacy. In fact, several studies report that contact tracing applications deployed in multiple countries are not privacy friendly and have potential to be used for mass surveillance by the concerned governments. Hence, privacy respecting contact tracing application is the need of the hour that can lead to highly effective, efficient contact tracing. As part of this study, we focus on various cryptographic techniques that can help in addressing the Private Set Intersection problem which lies at the heart of privacy respecting contact tracing. We analyze the computation and communication complexities of these techniques under the typical client-server architecture utilized by contact tracing applications. Further we evaluate those computation and communication complexity expressions for India scenario and thus identify cryptographic techniques that can be more suitably deployed there.

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