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The emergence of the Covid-19 pandemic has led to the publication of many scientific papers. The goal of the present research was to analyze these papers using the Altmetric Attention Score (AAS). Statistics for 100 publications with high AAS scores were selected and exported from the Dimension database on May 22nd 2020. The major findings were that these publications were published in 34 different journals or preprint repositories. More than one-third of the total of 657, 350 social media posts were collected from the Twitter platform. The top contributing countries were China, followed by the USA. The paper "The proximal origin of SARS-CoV-2" by Andersen, Kristian G., etal., 2020 had the highest AAS (33 514). These findings may help others to design studies of the AAS in Coronavirus literature and compare them with traditional citations. [ABSTRACT FROM AUTHOR]

Purpose: Previous studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have focused on factors that influence the achievement of negative conversion of viral RNA. This study aimed to investigate the effects of the genetic mutations in different SARS-CoV-2 strains on the negative conversion time (NCT) among imported cases in Hangzhou, Zhejiang Province, China, in order to provide valuable insights for developing targeted epidemic prevention guidelines., Methods: This retrospective study involved 146 imported SARS-CoV-2 cases in Hangzhou from 8 April 2021 to 11 June 2022. We compared the SARS-CoV-2-specific indicators, clinical indexes, and NCT among the wild-type (WT), Delta, and Omicron groups. Spearman correlation analysis was used to identify the correlations of NCT with mutation types/frequencies., Results: The mean age of the imported cases was 35.3 (SD: 12.3) years, with 71.92 % males and 28.08 % females. The mean cycle threshold (Ct) values of open reading frame 1ab (ORF1ab) and nucleocapsid (N) RNA were 25.17 (SD: 6.44) and 23.4 (SD: 6.76), respectively. The mutations of SARS-CoV-2 strains were mainly located in N, membrane (M), spike (S), ORF1a, ORF1b, ORF3a, ORF6, and ORF9b genes among the WT, Delta, and Omicron groups. NCT was significantly prolonged in the WT and Delta groups compared to the Omicron group. T lymphocyte, white blood cell, eosinophil, and basophil counts were dramatically higher in the WT group than the Delta group. White blood cell, red blood cell, and basophil counts were significantly lower in the Delta group than the Omicron group. Spearman correlation analysis revealed a significant correlation between the NCT of viral RNA and mutation types of viral genes of WT and Omicron strains. Additionally, NCT was markedly negatively correlated with the frequencies of five mutations in Omicron strains (ORF1b:P1223L, ORF1b:R1315C, ORF1b:T2163I, ORF3a:T223I, and ORF6:D61L)., Conclusions: This study indicates that five mutations in Omicron strains (ORF1b:P1223L/R1315C/T2163I, ORF3a:T223I and ORF6:D61L) shortened NCT in imported SARS-CoV-2 cases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The papers in this special section focus on modeling and simulation in disaster and emergency management. The COVID-19 pandemic of 2020 has wrought damage globally to a degree that is totally unprecedented in human history.Within three months that the first known death from the illness caused by the so-called novel Coronavirus was reported by state media in China on the 11th of January 2020, close to 1.8 million people worldwide had tested positive, with more than 100,000 deaths reported. By the time the pandemic will have been declared to be under control, millions more are expected to have been infected and tens (possibly hundreds) of thousands more will have perished as a result of the disease. Not only are the numbers of COVID-19 infected people and deaths staggering. Economies throughout the world have suffered tremendously, with many companies forced to shut down, or at the very least significantly scale down, their production of goods and services as a result of the need for social distancing and self-isolation required to prevent the unmitigated transmission of the disease. All this has led to hundreds of millions worldwide losing their employment or other sources of livelihood. Governments of all nations, large and small, developed and underdeveloped, have needed to pump into their economy and onto their struggling citizens whatever financial resources they could manage to generate. [ABSTRACT FROM AUTHOR]

This paper evaluates the effects of economic shocks to current and expected income reduction on mental wellbeing. We use individual-level data from three East Asian countries; China, Japan, and South Korea, during the early phases of the pandemic when the COVID-induced economic shocks were severe. The findings reveal significant causal effects from current and expected income reduction on different aspects of mental health deterioration, including anxiety, trouble sleeping, boredom, and loneliness. Interestingly, we found that expectations of future income loss have a significantly larger effect on people's mental wellbeing compared to current falls in income. This has significant implications for the design of policies to support income during pandemics., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The novel coronavirus disease (COVID-19) pandemic has profoundly impacted the global economy and human health. The paper mainly proposed an improved susceptible-exposed-infected-recovered (SEIR) epidemic model with media coverage and limited medical resources to investigate the spread of COVID-19. We proved the positivity and boundedness of the solution. The existence and local asymptotically stability of equilibria were studied and a sufficient criterion was established for backward bifurcation. Further, we applied the proposed model to study the trend of COVID-19 in Shanghai, China, from March to April 2022. The results showed sensitivity analysis, bifurcation, and the effects of critical parameters in the COVID-19 model.

Since the global outbreak of COVID-19, the virus has continuously mutated and can survive in the air for long periods of time. This paper establishes and analyzes a model of COVID-19 with self-protection and quarantine measures affected by viruses in the environment to investigate the influence of viruses in the environment on the spread of the outbreak, as well as to develop a rational prevention and control measure to control the spread of the outbreak. The basic reproduction number was calculated and Lyapunov functions were constructed to discuss the stability of the model equilibrium points. The disease-free equilibrium point was proven to be globally asymptotically stable when $ R&#95;0 < 1 $, and the endemic equilibrium point was globally asymptotically stable when $ R&#95;0 > 1 $. The model was fitted using data from COVID-19 cases in Chongqing between November 1 to November 25, 2022. Based on the numerical analysis, the following conclusion was obtained: clearing the virus in the environment and strengthening the isolation measures for infected people can control the epidemic to a certain extent, but enhancing the self-protection of individuals can be more effective in reducing the risk of being infected and controlling the transmission of the epidemic, which is more conducive to the practical application.

Objective: Coronavirus disease 19 (COVID-19) is a highly contagious disease characterized by severe respiratory infection by SARS-CoV-2 virus. COVID-19 was first appeared in Wuhan, China, in December 2019 and then rapidly became a global pandemic from a local outbreak. The present study aims to present the rapid increase of scientific productivity on COVID-19 by comparing publications of the first quarter with the first half of 2020. Materials and Methods: Web of Science (WoS) software was used for the search and the analysis. To compare scientific productivity of two periods as the first quarter and the first half of the pandemic era, all scientific papers published about COVID-19 included in Science Citation Index Expanded (SCI-E) from January 1st to April 5th and from January 1st to July 9th of 2020 were searched using the following terms: "COVID-19","2019-n-CoV","SARS-CoV-2","Coronavirus disease 19" and "2019 novel coronavirus" as nomenclatures of COVID-19. Results: Overall, 337 and 11.704 scientific papers related to COVID-19, indexed by SCI-E, were found in the first quarter and the first half of 2020, respectively. While the biggest contribution for publications was from People's Republic of China (PRC) in the first quarter and was from the USA in the first half of 2020 for COVID-19. Conclusion: We found a close correlation between the rapid acceleration of scientific papers and turning the disease from a local outbreak to a global pandemic. Since sharing experiences is as important as struggling with these kinds of novel diseases, we believe that encouraging researchers to make scientific publications for others is more important than ever in the circumstances like this. [ABSTRACT FROM AUTHOR]

Background Para-infectious encephalopathy is an acute inflammatory encephalopathy secondary to a systemic infectious disease, including acute necrotizing encephalopathy (ANE) and mild encephalitis/encephalopathy with a reversible splenial lesion (MERS). This paper reports on 3 cases of SARS-CoV-2 related to para-infectious encephalopathy diagnosed and treated in The Ordos Central Hospital of Inner Mongolia Autonomous Region from December 2022 to February 2023, and reviews relevant literature to summarize the clinical characteristics of the disease. Methods and Results The 3 patients with SARS-CoV-2 related to para-infectious encephalopathy, including 2 cases of SARS-CoV-2 related to ANE and one case of SARS-CoV-2 related to MERS were reported. Three patients developed consciousness disorder 2-4 d after fever, and still had aphasia, mental abnormality, convulsions, etc.. SARS-CoV-2 throat swab was positive. Head MRI showed one abnormal signal of brain stem and bilateral thalamus, one abnormal signal of bilateral thalamus, and one abnormal pressure of corpus callosum. All received hormone shock therapy and (or) intravenous immunoglobulin. One died, and 2 cases were recovered. Conclusions SARS-CoV-2 related to para-infectious encephalopathy including SARS-CoV-2 related to ANE and MERS and other clinical subtypes, the former has rapid progress, severe disease, high disability rate and fatality rate and poor prognosis, while the latter has relatively mild symptoms and better prognosis. [ABSTRACT FROM AUTHOR]

China's urbanization has received as much attention as its economic growth in recent years. While rapid urbanization has promoted modernization and wealth creation, it has also brought many problems and challenges. So, since 2014, the Chinese government has implemented a new urbanization policy nationwide. However, few researchers have examined whether China's new urbanization policies promote sustainable urbanization. This paper evaluates the sustainable urbanization of 19 urban agglomerations in China using the elastic coefficient. The results indicate a significant increase in the number of cities achieving sustainable urbanization since the implementation of China's new urbanization policy. The number has risen from 46 in the period of 2010–2015 to 71 in the period of 2015–2021. Considering the impact of the new coronavirus on economy, there would have been even more cities entering sustainable urbanization during the latter period. This indicates that the new urbanization policy has a positive influence on the sustainable urbanization of China's urban agglomerations. The sustainable urbanization status is not static and changes with different policies that are implemented in different time periods. Therefore, it is important to find useful policies that can guide and enhance the urbanization process in these cities. In addition, cities that have a sustainable urbanization status are not perfect. To address this issue, it is important to categorize and implement targeted policies for cities experiencing both sustainable and non-sustainable urbanization. Changes in a city's size or urbanization rates are not related to the city's sustainable urbanization status. A larger city size does not indicate sustainable urbanization, and, similarly, cities with faster urbanization rates do not exhibit a higher level of urbanization sustainability. [ABSTRACT FROM AUTHOR]

The appearance of a novel coronavirus in late 2019 radically changed the community of researchers working on coronaviruses since the 2002 SARS epidemic. In 2020, coronavirus-related publications grew by 20 times over the previous two years, with 130,000 more researchers publishing on related topics. The United States, the United Kingdom and China led dozens of nations working on coronavirus prior to the pandemic, but leadership consolidated among these three nations in 2020, which collectively accounted for 50% of all papers, garnering well more than 60% of citations. China took an early lead on COVID-19 research, but dropped rapidly in production and international participation through the year. Europe showed an opposite pattern, beginning slowly in publications but growing in contributions during the year. The share of internationally collaborative publications dropped from pre-pandemic rates; single-authored publications grew. For all nations, including China, the number of publications about COVID track closely with the outbreak of COVID-19 cases. Lower-income nations participate very little in COVID-19 research in 2020. Topic maps of internationally collaborative work show the rise of patient care and public health clusters—two topics that were largely absent from coronavirus research in the two years prior to 2020. Findings are consistent with global science as a self-organizing system operating on a reputation-based dynamic. [ABSTRACT FROM AUTHOR]

This paper addresses the reactions of domestic helpers to the Wuhan (Hubei Province) lockdown that began on January 23, 2020. We use a novel dataset containing the information of over 40,000 Chinese domestic helpers registered on a leading professional website from November 2019 to June 2020. The results indicate a declining pattern of short-term labor supply of domestic helpers across 11 major Chinese cities, which shows an increase in the expected monthly wage of domestic helpers in these cities. More importantly, using a difference-in-difference (DID) model, this paper provides some evidence on the existence of labor market discrimination against domestic helpers born in Hubei Province due to employers' fear of infection. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is often absent or at low levels in the cerebrospinal fluid (CSF) of patients with previous SARS-CoV-2-associated Guillain-Barré syndrome (GBS). This has led to speculation that SARS-CoV-2-associated GBS is more likely mediated by post-infectious immunity or a parainfection. This understanding has influenced the development of treatment regimens for SARS-CoV-2-associated GBS. This paper reports our experience with four Chinese patients with SARS-CoV-2-associated GBS who tested positive for SARS-CoV-2 RNA in the CSF. They developed symptoms of peripheral nerve damage 4–15 days after fever and confirmed SARS-CoV-2 infection, all of whom presented with progressive weakness of both lower limbs; three with autonomic nerve function impairment such as constipation and urination disorder; and one with polycranial neuritis and Miller–Fisher syndrome. Three patients were tested for anti-ganglioside antibodies, and one tested positive for GD1a-IgG. Four patients recovered well after treatment with anti-viral drugs combined with intravenous immunoglobulin. The present results showed that SARS-CoV-2 RNA can be detected via mNGS in the CSF of some patients with SARS-CoV-2-associated GBS, suggesting that SARS-CoV-2-associated GBS may have multiple pathogeneses. [ABSTRACT FROM AUTHOR]

The new coronavirus (COVID-19) has generated an unprecedented degree of social and economic impact on the planet, but few researchers have explored the repercussion of COVID-19 for sustainable development (SD) and corporate social responsibility (CSR), especially from the perspective of Chinese businesses. This paper is the first to outline the priority changes of both SD and CSR over the period of COVID-19 incidence in China. An online questionnaire survey of 1161 owners and managers of Chinese companies was conducted, and respondents were asked to score the priorities of their company over the pre, during and post COVID-19 periods. The research was carried out at the end of the first COVID-19 wave in China but during the period of lockdown in some parts of the country. It was found that there was a priority change regarding three dimensions of sustainable development and 13 aspects of CSR. While the social dimension of SD was prioritized during and post COVID-19, the environmental dimension was the only one deemed to be less important and less prioritized over the longer term after the pandemic. The top three short-term CSR priorities were having in place a workplace health and safety plan, engaging in philanthropic activities and protecting biodiversity, and the top three longer-term CSR priorities were job creation, protecting biodiversity and having in place a workplace health and safety plan. Environmental protection and using clean energy were not reported as a CSR priority. The paper concludes that China's recovery mode cannot be called 'green' and suggests ways this could be changed. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease (SARS-CoV-2) has caused many infections and deaths throughout the world; the spread of the coronavirus pandemic is still ongoing and continues to affect healthcare systems and economies of countries worldwide. Mathematical models are used in many applications for infectious diseases, including forecasting outbreaks and designing containment strategies. In this paper, we study two types of SIR and SEIR models for the coronavirus. This study focuses on the discrete-time and fractional-order of these models; we study the stability of the fixed points and orbits using the Jacobian matrix and the eigenvalues and eigenvectors of each case; moreover, we estimate the parameters of the two systems in fractional order. We present a statistical study of the coronavirus model in two countries: Saudi Arabia, which has successfully recovered from the SARS-CoV-2 pandemic, and China, where the number of infections remains significantly high. [ABSTRACT FROM AUTHOR]

The emergence of SARS-CoV-2 in China in December 2019 has posed a major challenge to health systems in all countries around the world. One of the most relevant epidemiological measures to consider during the course of a pandemic is the proportion of cases that eventually die from the disease (case fatality ratio, CFR). Monitoring the evolution of this indicator is of paramount importance because it allows for the assessment of both variations in the lethality of the virus and the effectiveness of the control measures implemented by health authorities. One of the problems with estimating the CFR in practice is that the available data only show daily or weekly counts of new cases and deaths; there is no information on when each deceased patient was infected and therefore it is not possible to know exactly how many cases there were at the time the patient became infected. Various approaches have been proposed for calculating the CFR by correcting for the time lag between infection and death. In this paper, we present a novel methodology to perform a non-parametric estimation of the evolution of the CFR by initially identifying an optimal time lag between infections and deaths. The goodness of this procedure is assessed by means of a simulation study and the method is applied to the estimation of the CFR in Spain in the period from July 2020 to March 2022., (© 2022. The Author(s).)

Background: The outbreak of severe acute respiratory syndrome coronavirus (SARS-CoV-2) Omicron variant occurred in Tianjin, China, at the beginning of 2022. In the present study, we identified risk factors that may affect positive (RP) RNA re-testing in recovered patients infected with Omicron variants during recovery in hospital., Methods: We retrospectively analyzed the medical records of 425 patients with Omicron variant infection admitted to our medical center from January 21, 2022 to February 24, 2022, based on the recurrence of RT-PCR positive results for SARS-CoV-2 after cure and discharge. Patients were divided into re-tested positive (RP) and non-re-detectable positive patients (NRP) groups, and clinical data from both groups were analyzed to investigate the characteristics and risk factors of RP patients., Results: Univariate analysis showed significant differences in age, vaccination rate and dose, partial signs and symptoms, most co-existing disorders, and levels of CRP and IL-6 between the RP and NRP groups (all P < 0.05), while multifactorial logistic regression analysis showed that vaccination status and levels of IL-6 were independent risk factors for RP patients., Conclusion: Our results suggested that clinicians should assess the probability of "re-positive" nucleic acid tests after discharge, taking the following indicators into account: pre-admission underlying diseases, unvaccinated status, and high levels of CRP and IL-6. Post-discharge isolation and follow-up should also be strengthened., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The goal of this study was to identify the genomic variants and determine molecular epidemiology of SARS-CoV-2 virus during the early pandemic stage in Bangladesh. Viral RNA was extracted, converted to cDNA, and amplified using Ion AmpliSeq™ SARS-CoV-2 Research Panel. 413 unique mutants from 151 viral isolates were identified. 80% of cases belongs to 8 mutants: 241C toT, 1163A toT, 3037C toT, 14408C toT, 23403A toG, 28881G toA, 28,882 G toA, and 28883G toC. Observed dominance of GR clade variants that have strong presence in Europe, suggesting European channel a possible entry route. Among 37 genomic mutants significantly associated with clinical symptoms, 3916CtoT (associated with sore-throat), 14408C to T (associated with cough-protection), 28881G to A, 28882G to A, and 28883G to C (associated with chest pain) were notable. These findings may inform future research platforms for disease management and epidemiological study., Competing Interests: Conflicts of interest The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022. Published by Elsevier Inc.)

Millions of people have died as a result of SARS-CoV-2, which was first discovered in China and has since spread globally. Patients with SARS-CoV-2 infection may show a range of symptoms, including fever, coughing, and shortness of breath, or they may show no symptoms at all. To treat COVID-19 symptoms and avoid serious infections, many medications and vaccinations have been employed. However, to entirely eradicate COVID-19 from the world, next-generation vaccine research is required because of the devastating consequences it is having for humanity and every nation's economy. Scientists are working hard to eradicate this dangerous virus across the world. SARS-CoV-2 has also undergone significant mutation, leading to distinct viral types such as the alpha, beta, gamma, delta, and omicron variants. This has sparked discussion about the effectiveness of current vaccines for the newly formed variants. A proper comparison of these vaccinations is required to compare their efficacy as the number of people immunized against SARS-CoV-2 globally increases. Population-level statistics evaluating the capacity of these vaccines to reduce infection are therefore being developed. In this paper, we analyze the many vaccines on the market in terms of their production process, price, dosage needed, and efficacy. This article also discusses the challenges of achieving herd immunity, the likelihood of reinfection, and the importance of convalescent plasma therapy in reducing infection. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for the Coronavirus disease 2019 (COVID-19). COVID-19 was first reported in China in December 2019. SARS-CoV-2 is highly contagious and spread primarily via an airborne route. Hand hygiene, surgical masks, vaccinations and boosters, air filtration, environmental sanitization, instrument sterilization, mouth rinses, and social distancing are essential infection control measures against the transmission of SARS-CoV-2. This paper aims to provide healthcare professionals with evidence-based protective strategies. [ABSTRACT FROM AUTHOR]

As a global pandemic, COVID-19 shows no sign of letting up. With the control of the epidemic in China, the proportion of patients with severe and critical diseases being cured and discharged from hospital has increased, and the recovery of COVID-19 patients has become an important issue that urgently needs attention and solutions. By summarizing the exercise rehabilitation strategies and progress of SARS in 2003, this paper analyzed the differences in clinical indicators and recovery characteristics of severe pneumonia caused by the two viruses, and provided comprehensive exercise guidance and intervention strategies for COVID-19 patients for rehabilitation and nursing by referring to the problems and treatment strategies in the rehabilitation and nursing work of SARS. In the post-epidemic period, China will build a multi-dimensional epidemic prevention system by improving the effectiveness of mass training and strengthening local risk prevention and control. This paper discusses the exercise rehabilitation strategy of SARS patients after recovery, which has guiding significance for exercise intervention and scientific fitness of COVID-19 patients after recovery during epidemic prevention period. [ABSTRACT FROM AUTHOR]

Novel coronavirus (COVID-19) is started from Wuhan (City in China), and is rapidly spreading among people living in other countries. Today, around 215 countries are affected by COVID-19 disease. WHO announced approximately number of cases 11,274,600 worldwide. Due to rapidly rising cases daily in the hospitals, there are a limited number of resources available to control COVID-19 disease. Therefore, it is essential to develop an accurate diagnosis of COVID-19 disease. Early diagnosis of COVID-19 patients is important for preventing the disease from spreading to others. In this paper, we proposed a deep learning based approach that can differentiate COVID- 19 disease patients from viral pneumonia, bacterial pneumonia, and healthy (normal) cases. In this approach, deep transfer learning is adopted. We used binary and multi-class dataset which is categorized in four types for experimentation: (i) Collection of 728 X-ray images including 224 images with confirmed COVID-19 disease and 504 normal condition images (ii) Collection of 1428 X-ray images including 224 images with confirmed COVID-19 disease, 700 images with confirmed common bacterial pneumonia, and 504 normal condition images. (iii) Collections of 1442 X- ray images including 224 images with confirmed COVID-19 disease, 714 images with confirmed bacterial and viral pneumonia, and 504 images of normal conditions (iv) Collections of 5232 X- ray images including 2358 images with confirmed bacterial and 1345 with viral pneumonia, and 1346 images of normal conditions. In this paper, we have used nine convolutional neural network based architecture (AlexNet, GoogleNet, ResNet-50, Se-ResNet-50, DenseNet121, Inception V4, Inception ResNet V2, ResNeXt-50, and Se-ResNeXt-50). Experimental results indicate that the pre trained model Se-ResNeXt-50 achieves the highest classification accuracy of 99.32% for binary class and 97.55% for multi-class among all pre-trained models. [ABSTRACT FROM AUTHOR]

The exploration of the dependency structure of the Chinese and EU carbon trading markets is crucial to the construction of a globally harmonized carbon market. In this paper, we studied the characteristics of structural interdependency between China's major carbon markets and the European Union (EU) carbon market before and after the launch of the national carbon emissions trading scheme (ETS) and the occurrence of the new coronavirus (COVID-19) by applying the C-vine copula method, with the carbon trading prices of the EU, Beijing, Shanghai, Guangdong, Shenzhen and Hubei as the research objects. The study shows that there exists a statistically significant dependence between the EU and the major carbon markets in China and their extremal dependences and dependence structures are different at different stages. After the launch of the national carbon ETS, China has become more independent in terms of interdependency with the EU carbon market, and is more relevant between domestic carbon markets. Most importantly, we found that the dependence between the EU and Chinese carbon markets has increased following the outbreak of COVID-19, and tail dependency structures existed before the launch of the national carbon ETS and during the outbreak of the COVID-19. The results of this study provide a basis for the understanding of the linkage characteristics of carbon trading prices between China and the EU at different stages, which in turn can help market regulators and investors to formulate investment decisions and policies. [ABSTRACT FROM AUTHOR]

Two years after the start of the COVID-19 pandemic, key questions about the emergence of its aetiological agent (SARS-CoV-2) remain a matter of considerable debate. Identifying when SARS-CoV-2 began spreading among people is one of those questions. Although the current canonically accepted timeline hypothesises viral emergence in Wuhan, China, in November or December 2019, a growing body of diverse studies provides evidence that the virus may have been spreading worldwide weeks, or even months, prior to that time. However, the hypothesis of earlier SARS-CoV-2 circulation is often dismissed with prejudicial scepticism and experimental studies pointing to early origins are frequently and speculatively attributed to false-positive tests. In this paper, we critically review current evidence that SARS-CoV-2 had been circulating prior to December of 2019, and emphasise how, despite some scientific limitations, this hypothesis should no longer be ignored and considered sufficient to warrant further larger-scale studies to determine its veracity., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

At the end of 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was discovered in China, causing a new coronavirus disease, termed COVID-19 by the WHO on February 11, 2020. At the time of this paper (January 31, 2021), more than 100 million cases have been recorded, which have claimed over 2 million lives worldwide. The most important clinical presentation of COVID-19 is severe pneumonia; however, many patients present various neurological symptoms, ranging from loss of olfaction, nausea, dizziness, and headache to encephalopathy and stroke, with a high prevalence of inflammatory central nervous system (CNS) syndromes. SARS-CoV-2 may also target the respiratory center in the brainstem and cause silent hypoxemia. However, the neurotropic mechanism(s) by which SARS-CoV-2 affects the CNS remain(s) unclear. In this paper, we first address the involvement of astrocytes in COVID-19 and then elucidate the present knowledge on SARS-CoV-2 as a neurotropic virus as well as several other neurotropic flaviviruses (with a particular emphasis on the West Nile virus, tick-borne encephalitis virus, and Zika virus) to highlight the neurotropic mechanisms that target astroglial cells in the CNS. These key homeostasis-providing cells in the CNS exhibit many functions that act as a favorable milieu for virus replication and possibly a favorable environment for SARS-CoV-2 as well. The role of astrocytes in COVID-19 pathology, related to aging and neurodegenerative disorders, and environmental factors, is discussed. Understanding these mechanisms is key to better understanding the pathophysiology of COVID-19 and for developing new strategies to mitigate the neurotropic manifestations of COVID-19. [ABSTRACT FROM AUTHOR]

Recently, most countries have entered the outbreak period of the novel coronavirus epidemic. This sudden outbreak has caused a huge impact on the global economy, which has intensified the division of globalization and the recession of the global economy. Although the epidemic situation in China has gradually stabilized, the severe situation in the world still inevitably impacts China's economy. Based on the uncertainty of future epidemic, this paper sets up three scenarios to analyze the impact of the epidemic on China's economy. The first is that in June, the epidemic both at home and abroad is under control without rebound; the second is that the domestic epidemic is basically controlled but the foreign situation is not effectively controlled; the third is that the epidemic situation in China has a serious rebound due to the influence of the imported cases from abroad, which destroy the economy again. At the same time, some corresponding guidelines are put forward for the recovery of economy, and to minimize the economic losses as well as accelerate the pace of national economic recovery. In addition, it is believed that these suggestions may have certain reference value to other countries. [ABSTRACT FROM AUTHOR]

This project is funded by the US National Science Foundation (NSF) through their NSF RAPID program under the title "Modeling Corona Spread Using Big Data Analytics." The project is a joint effort between the Department of Computer & Electrical Engineering and Computer Science at FAU and a research group from LexisNexis Risk Solutions. The novel coronavirus Covid-19 originated in China in early December 2019 and has rapidly spread to many countries around the globe, with the number of confirmed cases increasing every day. Covid-19 is officially a pandemic. It is a novel infection with serious clinical manifestations, including death, and it has reached at least 124 countries and territories. Although the ultimate course and impact of Covid-19 are uncertain, it is not merely possible but likely that the disease will produce enough severe illness to overwhelm the worldwide health care infrastructure. Emerging viral pandemics can place extraordinary and sustained demands on public health and health systems and on providers of essential community services. Modeling the Covid-19 pandemic spread is challenging. But there are data that can be used to project resource demands. Estimates of the reproductive number (R) of SARS-CoV-2 show that at the beginning of the epidemic, each infected person spreads the virus to at least two others, on average (Emanuel et al. in N Engl J Med. 2020, Livingston and Bucher in JAMA 323(14):1335, 2020). A conservatively low estimate is that 5 % of the population could become infected within 3 months. Preliminary data from China and Italy regarding the distribution of case severity and fatality vary widely (Wu and McGoogan in JAMA 323(13):1239–42, 2020). A recent large-scale analysis from China suggests that 80 % of those infected either are asymptomatic or have mild symptoms; a finding that implies that demand for advanced medical services might apply to only 20 % of the total infected. Of patients infected with Covid-19, about 15 % have severe illness and 5 % have critical illness (Emanuel et al. in N Engl J Med. 2020). Overall, mortality ranges from 0.25 % to as high as 3.0 % (Emanuel et al. in N Engl J Med. 2020, Wilson et al. in Emerg Infect Dis 26(6):1339, 2020). Case fatality rates are much higher for vulnerable populations, such as persons over the age of 80 years (> 14 %) and those with coexisting conditions (10 % for those with cardiovascular disease and 7 % for those with diabetes) (Emanuel et al. in N Engl J Med. 2020). Overall, Covid-19 is substantially deadlier than seasonal influenza, which has a mortality of roughly 0.1 %. Public health efforts depend heavily on predicting how diseases such as those caused by Covid-19 spread across the globe. During the early days of a new outbreak, when reliable data are still scarce, researchers turn to mathematical models that can predict where people who could be infected are going and how likely they are to bring the disease with them. These computational methods use known statistical equations that calculate the probability of individuals transmitting the illness. Modern computational power allows these models to quickly incorporate multiple inputs, such as a given disease's ability to pass from person to person and the movement patterns of potentially infected people traveling by air and land. This process sometimes involves making assumptions about unknown factors, such as an individual's exact travel pattern. By plugging in different possible versions of each input, however, researchers can update the models as new information becomes available and compare their results to observed patterns for the illness. In this paper we describe the development a model of Corona spread by using innovative big data analytics techniques and tools. We leveraged our experience from research in modeling Ebola spread (Shaw et al. Modeling Ebola Spread and Using HPCC/KEL System. In: Big Data Technologies and Applications 2016 (pp. 347-385). Springer, Cham) to successfully model Corona spread, we will obtain new results, and help in reducing the number of Corona patients. We closely collaborated with LexisNexis, which is a leading US data analytics company and a member of our NSF I/UCRC for Advanced Knowledge Enablement. The lack of a comprehensive view and informative analysis of the status of the pandemic can also cause panic and instability within society. Our work proposes the HPCC Systems Covid-19 tracker, which provides a multi-level view of the pandemic with the informative virus spreading indicators in a timely manner. The system embeds a classical epidemiological model known as SIR and spreading indicators based on causal model. The data solution of the tracker is built on top of the Big Data processing platform HPCC Systems, from ingesting and tracking of various data sources to fast delivery of the data to the public. The HPCC Systems Covid-19 tracker presents the Covid-19 data on a daily, weekly, and cumulative basis up to global-level and down to the county-level. It also provides statistical analysis for each level such as new cases per 100,000 population. The primary analysis such as Contagion Risk and Infection State is based on causal model with a seven-day sliding window. Our work has been released as a publicly available website to the world and attracted a great volume of traffic. The project is open-sourced and available on GitHub. The system was developed on the LexisNexis HPCC Systems, which is briefly described in the paper. [ABSTRACT FROM AUTHOR]

The novel coronavirus has had a huge impact on the world, not only for those infected, but for the population at large in the context of the work, money incoming, economy. In this paper, our objective is to study different types of tweets collected from Twitter from different perspectives of analysis, and machine learning classification. Previous work extracted a large corpus of tweets based on keywords such as [الصین ، تفشي ، السفر ، كورونا,[which translate to China, Corona, outbreak, travel; however, we hypothesis that not all these are genuinely relevant to Covid-19. In this work, we combine different machine learning models to classify tweets into those that do discuss the Coronavirus and those that do not. In our result, based on the different analysis and models, we have seen that more than 55% of these tweets were talking about topics other than the Coronavirus. These indicates the care that must be taken when extracting tweets, particularly in a language like Arabic, which has many nuances that make simple keyword approaches prone to error. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19) has affected almost all the countries globally, and it is considered a global pandemic. Hence, this study conducted a bibliometric analysis of scientific output on the COVID-19 pandemic outbreak using the Web of Science (WoS) database. A specific search technique was developed based on Corona virus-related keywords from January 1, 2019, until June 24, 2020. A total of 10850 documents related to COVID-19 published from January 1, 2019, to June 24, 2020, were retrieved from the WoS database. The researchers downloaded the data from WoS as a WoS plain text file, and the data were analyzed using R studio (biblioshiny) software. Out of the total of 10850 documents published in 1736 scientific journals, 10845 papers belonging to the year 2020, which constituents 99.954% of the total documents (N=10850). Wang Y is the most productive author who contributed 0.60% (n=65) of the total documents published. USA is the predominant country that produced 2701 documents related to COVID-19, and China follows it with 1937 documents. The most active collaboration held between the USA and China, and it accounted for 2.75% (n=298) of the entire documents (N=10850). [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) remains a global pandemic at present. Although the human-to-human transmission route for this disease has been well established, its transmission mechanism is not fully understood. In this paper, we propose a mathematical model for COVID-19 which incorporates multiple transmission pathways and which employs time-dependent transmission rates reflecting the impact of disease prevalence and outbreak control. Applying this model to a retrospective study based on publicly reported data in China, we argue that the environmental reservoirs play an important role in the transmission and spread of the coronavirus. This argument is supported by our data fitting and numerical simulation results for the city of Wuhan, for the provinces of Hubei and Guangdong, and for the entire country of China.

This paper surveyed 422 financial managers before the number of novel coronavirus (COVID-19) infections in China peaked and used path analysis to study the risk decision-making mechanisms of financial managers. The study found that whether financial managers developed coping strategies depends on their assessment of potential business revenue losses. There are two transmission paths: the direct effect refers to the risk perception directly caused by COVID-19, while the indirect effect refers to managers' fear that they will not make timely adjustments or will make judgment errors, resulting in the loss of competitive advantage. It is worth noting that the indirect effect exceeds the direct effect, which indicates that financial managers are more rational than ordinary people in dealing with COVID-19, that they are relatively more concerned about competitor changes, and that they may even view COVID-19 as an important opportunity to obtain a better competitive position. [ABSTRACT FROM AUTHOR]

On 31 December 2019, WHO received inputs of pneumonia cases in Wuhan city of China, but the cause of infection could not be known initially. However, after some time, the medical researchers of China disclosed a novel coronavirus as the cause on 7 January 2020, named "2019-nCoV." The coronavirus (CoV) belongs to Severe Acute Respiratory Syndrome (SARS) species that leads to infection, causing illness, which ranges from the common cold to serious sickness. Finally, on 11 March 2020, the WHO Director-General Dr. Tedros Adhanom Ghebreyesus announced the outbreak as a pandemic. As the fear and ambiguity rose among companies and firms, the profit rate seemed to be lower due to the COVID-19 global impact. Nearly US$6 trillion in wealth from 24th to 28 February 2020 of the stock market has been wiped out. There was a great decrease in value over the S&P index, which abolished over $5 trillion in the same week. However, the largest 10 companies of S&P faced a loss of $1.4 trillion. The investors make an analytical prediction that firms' profits may drop in response to the impact of coronavirus. The prime focus is on the importance of digital business practices and how different sectors have been affected in terms of economic loss during this pandemic outbreak in this paper. [ABSTRACT FROM AUTHOR]

Vaccination against coronavirus disease 2019 (COVID-19) has become an important public health solution. Developing a safe and effective vaccine against COVID-19 is a viable long-term solution to control the pandemic. As one of the two inactivated severe acute respiratory syndrome virus 2 (SARS-CoV-2) vaccines developed in China that entered the WHO emergency use list, Sinopharm BBIBP-CorV, an aluminum-hydroxide-adjuvanted, inactivated whole-virus vaccine, has been widely distributed, with more than 400 million doses administered in more than 40 countries. The evidence of the safety, efficacy, and effectiveness of BBIBP-CorV is gathered and reviewed. We further comment on one of the latest papers that disclosed the effectiveness results between BBIBP-CorV, rAd26-rAd5, and ChAdOx1. [ABSTRACT FROM AUTHOR]

Background: Policy changes are often necessary to contain the detrimental impact of epidemics such as those brought about by coronavirus disease (COVID-19). In the earlier phases of the emergence of COVID-19, China was the first to impose strict restrictions on movement (lockdown) on January 23rd, 2020. A strategy whose effectiveness in curtailing COVID-19 was yet to be determined. We, therefore, sought to study the impact of the lockdown in reducing the incidence of COVID-19., Methods: Daily cases of COVID-19 that occurred in China which were registered between January 12th and March 30th, 2020, were extracted from the Johns Hopkins CSSE team COVID-19 ArcGIS® dashboards. Daily cases reported were used as data points in the series. Two interrupted series models were run: one with an interruption point of 23 January 2020 (model 1) and the other with a 14-day deferred interruption point of 6th February (model 2). For both models, the magnitude of change (before and after) and linear trend analyses were measured, and β -coefficients reported with 95% confidence interval (CI) for the precision., Results: Seventy-eight data points were used in the analysis. There was an 11% versus a 163% increase in daily cases in models 1 and 2, respectively, in the preintervention periods ( p ≤ 0.001). Comparing the period immediately following the intervention points to the counterfactual, there was a daily increase of 2,746% ( p < 0.001) versus a decline of 207% ( p = 0.802) in model 2. However, in both scenarios, there was a statistically significant drop in the daily cases predicted for this data and beyond when comparing the preintervention periods and postintervention periods ( p < 0.001)., Conclusion: There was a significant decrease the COVID-19 daily cases reported in China following the institution of a lockdown, and therefore, lockdown may be used to curtail the burden of COVID-19., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Mooketsi Molefi et al.)

A pneumonia outbreak was primarily reported in the fall of 2019 in Wuhan, Hubei province, China, with the identity SARS-CoV-2, a novel coronavirus. It quickly grew from a local epidemic to a global pandemic and was declared a public health emergency by the WHO. A total of three prominent waves were identified across the globe, with a slight temporal variability as per the geographical locations, and has impacted several sectors which connect the world. By March 2022, the coronavirus had infected 444.12 million people and claimed 6.01 million human lives worldwide, and these numbers have not yet stabilized. Our paper enlightens readers on the seven strains of human coronaviruses, with special emphasis on the three severe deadliest outbreaks (SARS-2002, MERS-2012, and COVID-19). This work attempts a comprehensive understanding of the coronavirus and its impact on the possible sectors that link the world through the economic chain, climate conditions, SDGs, recycling of the event, and mitigations. There are many points that are raised by the authors in the possible sectors, which are emerging or are as yet unnoticed and thus have not been taken into consideration. This comprehension will leave sets of new challenges and opportunities for the researchers in various streams, especially in earth sciences. Science-integrated research may help to prevent upcoming disasters as a by-product of (existing) epidemics in the form of coronavirus. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread rapidly worldwide. This study is the first to report the tolerability, safety, pharmacokinetics (PK), and immunogenicity of a recombinant human anti-SARS-CoV-2 monoclonal antibody, etesevimab (CB6, JS016, LY3832479, or LY-CoV016), in healthy adults. This paper describes a randomized, double-blind, placebo-controlled, phase 1 study. A total of 40 participants were enrolled to receive a single intravenous dose of either etesevimab or placebo in one of four sequential ascending intravenous dose cohorts. All 40 participants completed the study. Seventeen (42.5%) participants experienced 22 treatment emergent adverse events (TEAEs) that were drug-related, and the rates of these TEAEs among different dose cohorts were numerically comparable. No difference was observed between the combined etesevimab group and the placebo group. The exposure after etesevimab infusion increased in an approximately proportional manner as the dose increased from 2.5 to 50 mg/kg. The elimination half-life ( t 1/2 ) value did not differ among different dose cohorts and was estimated to be around 4 weeks. Etesevimab was well tolerated after administration of a single dose at a range of 2.5 mg/kg to 50 mg/kg in healthy Chinese adults. The PK profiles of etesevimab in healthy volunteers showed typical monoclonal antibody distribution and elimination characteristics. (This study has been registered at ClinicalTrials.gov under identifier NCT04441918.).

Objective: To estimate the proportion of presymptomatic transmission of SARS-CoV-2 infection that can occur, and the timing of transmission relative to symptom onset., Setting/design: Secondary analysis of international published data., Data Sources: Meta-analysis of COVID-19 incubation period and a rapid review of serial interval and generation time, which are published separately., Participants: Data from China, the Islamic Republic of Iran, Italy, Republic of Korea, Singapore and Vietnam from December 2019 to May 2020., Methods: Simulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset, and the proportion of presymptomatic transmission, were estimated., Outcome Measures: Transmission time of SARS-CoV-2 relative to symptom onset and proportion of presymptomatic transmission., Results: Based on 18 serial interval/generation time estimates from 15 papers, mean transmission time relative to symptom onset ranged from -2.6 (95% CI -3.0 to -2.1) days before infector symptom onset to 1.4 (95% CI 1.0 to 1.8) days after symptom onset. The proportion of presymptomatic transmission ranged from 45.9% (95% CI 42.9% to 49.0%) to 69.1% (95% CI 66.2% to 71.9%)., Conclusions: There is substantial potential for presymptomatic transmission of SARS-CoV-2 across a range of different contexts. This highlights the need for rapid case detection, contact tracing and quarantine. The transmission patterns that we report reflect the combination of biological infectiousness and transmission opportunities which vary according to context., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The spatial diffusion of epidemic disease follows distance decay law in geography and social physics, but the mathematical models of distance decay depend on concrete spatio-temporal conditions. This paper is devoted to modeling spatial diffusion patterns of COVID-19 stemming from Wuhan city to Hubei province, China. The modeling approach is to integrate analytical method and experimental method. The local gravity model is derived from allometric scaling and global gravity model, and then the parameters of the local gravity model are estimated by observational data and least squares calculation. The main results are as below. The local gravity model based on power law decay can effectively describe the diffusion patterns and process of COVID-19 in Hubei Province, and the goodness of fit of the gravity model based on negative exponential decay to the observational data is not satisfactory. Further, the goodness of fit of the model to data entirely became better and better over time, the size elasticity coefficient increases first and then decreases, and the distance attenuation exponent decreases first and then increases. Moreover, the significance of spatial autoregressive coefficient in the model is low, and the confidence level is less than 80%. The conclusions can be reached as follows. (1) The spatial diffusion of COVID-19 of Hubei bears long range effect, and the size of a city and the distance of the city to Wuhan affect the total number of confirmed cases. (2) Wuhan direct transmission is the main process in the spatial diffusion of COVID-19 in Hubei at the early stage, and the horizontal transmission between regions is not significant. (3) The effect of spatial lockdown and isolation measures taken by Chinese government against the transmission of COVID-19 is obvious. This study suggests that the role of urban gravity (size and distance) should be taken into account to prevent and control epidemic disease., Competing Interests: The authors have declared that no competing interests exist.

Objectives: This study is aimed at exploring the relationship of the viral load of coronavirus disease 2019 (COVID-19) with lymphocyte count, neutrophil count, and C-reactive protein (CRP) and investigating the dynamic change of patients' viral load during the conversion from mild COVID-19 to severe COVID-19, so as to clarify the correlation between the viral load and progression of COVID-19., Methods: This paper included 38 COVID-19 patients admitted to the First Hospital of Jiaxing from January 28, 2020, to March 6, 2020, and they were clinically classified according to the Guidelines on the Novel Coronavirus-Infected Pneumonia Diagnosis and Treatment. According to the instructions of the Nucleic Acid Detection Kit for the 2019 novel coronavirus (SARS-CoV-2), respiratory tract specimens (throat swabs) were collected from patients for nucleic acid testing. Patients' lymphocyte count and neutrophil count were determined by blood routine examination, and CRP was measured by biochemical test., Results: The results of our study suggested that the cycle threshold (Ct) value of Nucleocapsid protein (N) gene examined by nucleic acid test was markedly positively correlated with lymphocyte count ( p = 0.0445, R 2 = 0.1203), but negatively correlated with neutrophil count ( p = 0.0446, R 2 = 0.1167) and CRP ( p = 0.0393, R 2 = 0.1261), which indicated that patients with a higher viral load tended to have lower lymphocyte count but higher neutrophil count and CRP. Additionally, we detected the dynamic change of Ct value in patients who developed into a severe case, finding that viral load of 3 patients increased before disease progression, whereas this phenomenon was not found in 2 patients with underlying diseases., Conclusion: The results of this study demonstrated that viral load of SARS-CoV-2 is significantly negatively correlated with lymphocyte count, but markedly positively correlated with neutrophil count and CRP. The rise of viral load is very likely to be the key factor leading to the overloading of the body's immune response and resulting in the disease progression into severe disease., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2021 Wenyu Chen et al.)

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is a highly infectious virus that is transmitted primarily through droplets or by coming in close contact with an infected person. In 2020, there was a global outbreak of COVID-19, resulting in an unprecedented global burden of disease, health care costs, and had a significant economic impact. Recently, SARS-CoV-2 was detected on the outer packaging of imported cold chain items in China and has led to virus transmission events, causing great concern. This paper analyses the factors of SARS-CoV-2 survival and transmission in different places and environments, especially the characteristics of low temperatures and object surfaces. It was found that SARS-CoV-2 could survive on surfaces of cold and moist objects in the cold chain for more than 3 weeks, potentially causing COVID-19 transmission. We believe that the low-temperature environment in winter may accelerate the spread of the outbreak and new outbreaks may occur. Overall, SARS-CoV-2 transmission that is susceptible to low winter temperatures is critical for predicting winter pandemics, allowing for the appropriate action to be taken in advance., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Chi, Wang, Chen and Zheng.)

Human coronaviruses (HCoVs) are associated with a range of respiratory complications. In the last two decades, three major outbreaks have been reported due to HCoVs including the current pandemic. In December 2019, a newly emerged virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan city, China. This paper presents a detailed review of the literature and discusses the uncertain spread of coronavirus disease 2019 (COVID-19) using fuzzy set as classical set theory logic to measure uncertainty and vagueness of COVID-19 in China. Our findings show that both infection and death rate touched the peak (normal fuzzy sets) and have shown a decline. The graphs are not convex, which shows that there remains much uncertainty in the spread of COVID-19. Effective vaccines are clearly needed to control and prevent the COVID-19 pandemic.

Introduction: This paper aims to estimate the incubation period and serial intervals for SARS-CoV-2 based on confirmed cases in Jiangxi Province of China and meta-analysis method., Methodology: Distributions of incubation period and serial interval of Jiangxi epidemic data were fitted by "fitdistrplus" package of R software, and the meta-analysis was conducted by "meta" package of R software., Results: Based on the epidemic data of Jiangxi, we found the median days of incubation period and serial interval were 5.9 days [IQR: 3.8 - 8.6] and 5.7 days [IQR: 3.6 - 8.3], respectively. The median days of the infectivity period at pre-symptomatic was 1.7 days [IQR: 1.1 - 2.4]. The meta-analysis based on 64 papers showed the pooled means of the incubation period and serial interval were 6.25 days (95% CrI: 5.75 - 6.75) and 5.15 days (95% CrI: 4.73 - 5.57), respectively., Conclusions: Our results contribute to a better understanding of COVID-19 and provide useful parameters for modelling the dynamics of disease transmission. The serial interval is shorter than the incubation period, which indicates that the patients are infectious at pre-symptomatic period, and isolation of detected cases alone is likely to be difficult to halt the spread of SARS-CoV-2., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2021 Tianchen Zhang, Sheng Ding, Zhili Zeng, Huijian Cheng, Chengfeng Zhang, Xiangqun Mao , Huanhong Pan , Guanghui Xia, Daping Che.)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in December 2019 and rapidly spread to other provinces in China as well as other countries. In this study, 262 patients diagnosed with moderate to severe SARS-CoV-2 pneumonia in Wuhan, China, were analyzed. Data were compared between survivors and nonsurvivors. Of all the 262 patients, 23 (8.8%) patients died and 239 (91.2%) were discharged. The median age was 63.5 years and 46.9% of patients were male. The main complaints were fever (83.6%), cough (63.4%), and fatigue (49.2%) in the surviving group, while there were more complaints of dyspnea (39.1%) and shortness of breath (56.5%) in the nonsurviving group. The main comorbidities were hypertension (35.5%), diabetes mellitus (16.4%), and coronary artery disease (9.9%). Morbidity is higher in elderly patients with more comorbidities. Patients were mainly treated with nasal cannula (93.9%), while the nonsurviving group received more invasive mechanical ventilation (39.1%). Arbidol (80.9%), ribavirin (36.6%), oseltamivir (38.9%), interferon (16.4%), and ganciclovir (14.5%) were used for the antiviral treatment. In the nonsurviving group, the number of white blood cells (WBC) was significantly increased and lymphocytes were decreased, and lymphopenia was more common. The levels of aspartate transaminase (AST), brain natriuretic peptide (BNP), creatine kinase isoenzyme MB (CK-MB), lactate dehydrogenase (LDH), and C-reactive protein (CRP) were also significantly increased in the nonsurviving group. The adjusted hazard ratios (HRs) for association of known variables for all-cause mortality due to the coronavirus disease 2019 were 2.467 (95% confidence interval [CI], 1.007-6.044; p  = 0.048) for shortness of breath and 1.025 (95% CI, 1.001-1.049; p  = 0.042) for AST. Elderly patients with more comorbidities and complaints of dyspnea and shortness of breath had increased risk of death. Patients with lymphopenia and high levels of WBC, AST, BNP, CK-MB, LDH, and CRP may be more likely to deteriorate.

The spread of COVID-19 is closely related to the structure of human social networks. Based on 237 cases, by using epidemiological retrospective statistics, data visualization, and social network analysis methods, this paper summarized characteristics of patients with COVID-19 in Shaanxi, China, and analyzed these patients' dynamic contact network structure. The study found that there are many clustered infections through strong ties, about one-third of cases are caused by relatives' infection. In early stages of the epidemic, imported cases were the most, and in the later stages, local infection cases were the most. The infected people were mostly middle-aged men. Symptoms of imported cases occurred on average of 3 days after they arrived, and medical measures were taken 5 days later on average. All cases showed symptoms in less than 2 days on average and were then taken to medical treatment. The contact network can be divided into multiple disconnected components. The largest component has 12 patients. The average degree centrality in the network is 0.987, average betweenness degree is 0, average closeness degree is 0.452, and average PageRank index is 0.0042. The number of contacts of patients is unevenly distributed in the network.

Novel coronavirus, known as COVID-19, is a very dangerous virus. Initially detected in China, it has since spread all over the world causing many deaths. There are several variants of COVID-19, which have been categorized into two major groups. These groups are variants of concern and variants of interest. Variants of concern are more dangerous, and there is a need to develop a system that can detect and classify COVID-19 and its variants without touching an infected person. In this paper, we propose a dual-stage-based deep learning framework to detect and classify COVID-19 and its variants. CT scans and chest X-ray images are used. Initially, the detection is done through a convolutional neural network, and then spatial features are extracted with deep convolutional models, while handcrafted features are extracted from several handcrafted descriptors. Both spatial and handcrafted features are combined to make a feature vector. This feature vector is called the vocabulary of features (VoF), as it contains spatial and handcrafted features. This feature vector is fed as an input to the classifier to classify different variants. The proposed model is evaluated based on accuracy, F1-score, specificity, sensitivity, specificity, Cohen's kappa, and classification error. The experimental results show that the proposed method outperforms all the existing state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Background: The global spread of the novel coronavirus pneumonia is still continuing, and a new round of more serious outbreaks has even begun in some countries. In this context, this paper studies the dynamics of a type of delayed reaction-diffusion novel coronavirus pneumonia model with relapse and self-limiting treatment in a temporal-spatial heterogeneous environment.Methods: First, focus on the self-limiting characteristics of COVID-19, incorporate the relapse and self-limiting treatment factors into the diffusion model, and study the influence of self-limiting treatment on the diffusion of the epidemic. Second, because the traditional Lyapunov stability method is difficult to determine the spread of the epidemic with relapse and self-limiting treatment, we introduce a completely different method, relying on the existence conditions of the exponential attractor of our newly established in the infinite-dimensional dynamic system to determine the diffusion of novel coronavirus pneumonia. Third, relapse and self-limiting treatment have led to a change in the structure of the delayed diffusion COVID-19 model, and the traditional basic reproduction number [Formula: see text] no longer has threshold characteristics. With the help of the Krein-Rutman theorem and the eigenvalue method, we studied the threshold characteristics of the principal eigenvalue and found that it can be used as a new threshold to describe the diffusion of the epidemic.Results: Our results prove that the principal eigenvalue [Formula: see text] of the delayed reaction-diffusion COVID-19 system with relapse and self-limiting treatment can replace the basic reproduction number [Formula: see text] to describe the threshold effect of disease transmission. Combine with the latest official data and the prevention and control strategies, some numerical simulations on the stability and global exponential attractiveness of the diffusion of the COVID-19 epidemic in China and the USA are given.Conclusions: Through the comparison of numerical simulations, we find that self-limiting treatment can significantly promote the prevention and control of the epidemic. And if the free activities of asymptomatic infected persons are not restricted, it will seriously hinder the progress of epidemic prevention and control. [ABSTRACT FROM AUTHOR]

In this paper, deterministic and stochastic models are proposed to study the transmission dynamics of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China. The deterministic model is formulated by a system of ordinary differential equations (ODEs) that is built upon the classical SEIR framework. The stochastic model is formulated by a continuous-time Markov chain (CTMC) that is derived based on the ODE model with constant parameters. The nonlinear CTMC model is approximated by a multitype branching process to obtain an analytical estimate for the probability of a disease outbreak. The local and global dynamics of the disease are analyzed by using the deterministic model with constant parameters, and the result indicates that the basic reproduction number $ \mathcal{R}&#95;0 $ serves as a sharp disease threshold: the disease dies out if $ \mathcal{R}&#95;0\le 1 $ and persists if $ \mathcal{R}&#95;0 > 1 $. In contrast to the deterministic dynamics, the stochastic dynamics indicate that the disease may not persist when $ \mathcal{R}&#95;0 > 1 $. Parameter estimation and validation are performed to fit our ODE model to the public reported data. Our result indicates that both the exposed and infected classes play an important role in shaping the epidemic dynamics of COVID-19 in Wuhan, China. In addition, numerical simulations indicate that a second wave of the ongoing pandemic is likely to occur if the prevention and control strategies are not implemented properly.

Background: Since the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-reviewed original articles., Methods: The data sources were Pubmed, Cochrane COVID-19 register study, arXiv, medRxiv and bioRxiv, from 01/11/2019 to 01/05/2020. Peer-reviewed and preprints publications related to COVID-19 were included, written in English or Chinese. No limitations were placed on study design. Reviewers screened and categorized studies according to i) publication type, ii) country of publication, and iii) topics covered. Original articles were critically appraised using validated quality assessment tools., Results: Among the 11,452 publications identified, 10,516 met the inclusion criteria, among which 7468 (71.0%) were peer-reviewed articles. Among these, 4190 publications (56.1%) did not include any data or analytics (comprising expert opinion pieces). Overall, the most represented topics were infectious disease (n = 2326, 22.1%), epidemiology (n = 1802, 17.1%), and global health (n = 1602, 15.2%). The top five publishing countries were China (25.8%), United States (22.3%), United Kingdom (8.8%), Italy (8.1%) and India (3.4%). The dynamic of publication showed that the exponential growth of COVID-19 peer-reviewed articles was mainly driven by publications without original data (mean 261.5 articles ± 51.1 per week) as compared with original articles (mean of 69.3 ± 22.3 articles per week). Original articles including patient data accounted for 713 (9.5%) of peer-reviewed studies. A total of 576 original articles (80.8%) showed intermediate to high risk of bias. Last, except for simulation studies that mainly used large-scale open data, the median number of patients enrolled was of 102 (IQR = 37-337)., Conclusions: Since the beginning of the COVID-19 pandemic, the majority of research is composed by publications without original data. Peer-reviewed original articles with data showed a high risk of bias and included a limited number of patients. Together, these findings underscore the urgent need to strike a balance between the velocity and quality of research, and to cautiously consider medical information and clinical applicability in a pressing, pandemic context. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/5zjyx/.

The current outbreak of coronavirus disease 2019 (COVID-19) has become a global crisis due to its quick and wide spread over the world. A good understanding of the dynamic of the disease would greatly enhance the control and prevention of COVID19. However, to the best of our knowledge, the unique features of the outbreak have limited the applications of all existing dynamic models. In this paper, a novel stochastic model was proposed aiming to account for the unique transmission dynamics of COVID-19 and capture the effects of intervention measures implemented in Mainland China. We found that: (1) instead of aberration, there was a remarkable amount of asymptomatic virus carriers, (2) a virus carrier with symptoms was approximately twice more likely to pass the disease to others than that of an asymptomatic virus carrier, (3) the transmission rate reduced significantly since the implementation of control measures in Mainland China, and (4) it was expected that the epidemic outbreak would be contained by early March in the selected provinces and cities in China.

Introduction: In December 2019, a new coronavirus has emerged out of China, the SARS‐CoV‐2 virus, causing a disease known as COVID‐19, which steadily has progressed into a pandemic. This coronavirus affects many organs, including the skin, whose manifestations are a consequence of the disease itself, as well as the preventative measures taken to avoid the infection. This paper reviews the cutaneous manifestations which currently have been encountered during this pandemic. Methods: A search was conducted on PubMed, and all relevant articles were included. Results: The results show the occurrence of many cutaneous findings, ranging from those related to the infection itself and to various dermatitides related to the use of personal protective equipment (PPE) utilized by healthcare workers while attending to infected patients. Discussion: Recognizing these findings is important for the accurate diagnosis of those infected with COVID‐19 as well as the prompt treatment of the side effects caused by PPE that might further impair the effectiveness of healthcare workers. [ABSTRACT FROM AUTHOR]