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Considering the high variability of Covid-19 and unknown sequelae of rebound infections. We may be caught in a long-term struggle against the virus. The evaluation and summary of past anti-epidemic policies highlight profound practical significance for either decision makers or individuals. This paper applies both theoretical and empirical approaches to study the impact of city lockdown and air pollution on Covid-19. First, we apply an extended Susceptible-Infected-Removed (SIR) model to identify the relationship between lockdown, air pollution, and Covid-19 cases. Second, we apply the Differences-in-Differences (DID) model and Poisson Pseudo-Maximum Likelihood (PPML) model to test the impact of lockdown on Covid-19, by sorting out lockdown policies implemented by cities during the epidemic. Third, we empirically analyze the impact of air pollution on Covid-19, based on daily data from 257 cities in China. Finally, we examine the mechanism by which lockdown impacts Covid-19. Newly confirmed Covid-19 cases are reduced by 31.1% nationwide (excluding Wuhan) during the lockdown period. Regions with lower air pollution experience fewer Covid-19 cases. Air pollution aggravates Covid-19, with the pollutants PM2.5, PM10, NO2, CO, and O3 having the greatest impact. The results indicate that an increase in one unit of air quality index (AQI) concentrations is associated with 1.723 more newly confirmed cases. The effects of air pollution on the spread of Covid-19 diminish as the population size increases. Lockdown can inhibit the spread of Covid-19 by reducing air pollution and population movement. [ABSTRACT FROM AUTHOR]

A bacterial infection in the lungs can cause viral pneumonia, a disease. Later the middle of December 2019, there have been multiple episodes of pneumonia in Wuhan City, China, with no known cause; it has since been discovered that this pneumonia is actually a new respiratory condition brought on by coronavirus infection. Humans who have lung abnormalities are more likely to develop high-risk conditions; this risk can be decreased with much quicker and more effective therapy. The symptoms of Covid-19 pneumonia are similar to those of viral pneumonia; they are not distinctive. X-ray or Computed Tomography (CT) scan images are used to identify lung abnormalities. Even for a skilled radiologist, it might be challenging to identify Covid-19/Viral pneumonia by looking at the X-ray images. For prompt and effective treatment, accurate diagnosis is essential. In this epidemic condition, delayed diagnosis can cause the number of cases to double, hence a suitable tool is required is necessary for the early identification of Covid-19. This paper highlights various AI techniques as a part of our contribution to swift identification and curie Covid-19 to front-line corona. The safety of Covid-19 people who have viral pneumonia is a concern. Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), two AI technologies from Deep Learning (DL), were utilized to identify Covid-19/Viral pneumonia. The Algorithm is taught utilizing non-public local hospitals or Covid-19 wards, as well as X-ray images of healthy lungs, fake lungs from viral pneumonia, and ostentatious lungs from Covid-19 that are all publicly available. The model is also validated over a lengthy period of time using the transfer learning technique. The results correspond with clinically tested positive Covid-19 patients who underwent Swap testing conducted by medical professionals, giving us an accuracy of 78 to 82 percent. We discovered that each DL model has a unique expertise after testing the various models. [ABSTRACT FROM AUTHOR]

Since the infectious coronavirus disease (COVID-19) was first reported in Wuhan, it has become a public health problem in China and even around the world. This pandemic is having devastating effects on societies and economies around the world. The increase in the number of COVID-19 tests gives more information about the epidemic spread, which may lead to the possibility of surrounding it to prevent further infections. However, wearing a face mask that prevents the transmission of droplets in the air and maintaining an appropriate physical distance between people, and reducing close contact with each other can still be beneficial in combating this pandemic. Therefore, this research paper focuses on implementing a Face Mask and Social Distancing Detection model as an embedded vision system. The pretrained models such as the MobileNet, ResNet Classifier, and VGG are used in our context. People violating social distancing or not wearing masks were detected. After implementing and deploying the models, the selected one achieved a confidence score of 100%. This paper also provides a comparative study of different face detection and face mask classification models. The system performance is evaluated in terms of precision, recall, F1-score, support, sensitivity, specificity, and accuracy that demonstrate the practical applicability. The system performs with F1-score of 99%, sensitivity of 99%, specificity of 99%, and an accuracy of 100%. Hence, this solution tracks the people with or without masks in a real-time scenario and ensures social distancing by generating an alarm if there is a violation in the scene or in public places. This can be used with the existing embedded camera infrastructure to enable these analytics which can be applied to various verticals, as well as in an office building or at airport terminals/gates. [ABSTRACT FROM AUTHOR]

In the context of the global pandemic of COVID-19, with the epidemic epicenter located in the Wuhan City, China, patients with severe mental illness have also been deeply affected by the epidemic. In this paper, two patients with schizophrenia who recovered from COVID-19 were reported. Because of the long-term positive results of the SARS-CoV-2 serum antibody IgM test, they had to undergo medical isolation and social restrictions for a long time. After the situation was effectively identified by the medical staff and they were eliminated as a potential virus carrier and released from the medical isolation center. Since psychiatrists often lack systematic knowledge of infectious diseases, the authors hope that this paper can provide a reference to avoid unnecessary wastage of medical resources and prevent placing serious mental burden on such patients in the future. [ABSTRACT FROM AUTHOR]

The general remit of this paper is the role of wildlife trade in pathogen spillover. Its underlying assumption is that, so far from being the exclusive domain of the life sciences, the study of pathogen spillover will be greatly enhanced by multi-perspectival approaches, including One Health and those employed here, namely, non-speciesist green criminology and critical animal studies. The paper moves from discussions of zoonosis, anthroponosis and wildlife trade to the emergence of COVID-19 in Wuhan, China. The paper recommends the abolition of all wildlife trade and the reclamation of wildlife habitat and broaches discussion of the extension of legal personhood to wild animals. [ABSTRACT FROM AUTHOR]

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]

Drawing on a recent online survey combined with city-level data, this paper examines the impact of the COVID-19 on consumers' online food purchase behavior in the short term. To address the potential endogeneity issues, we adopt an instrumental variable (IV) strategy, using the distance from the surveyed city to Wuhan as the instrumental variable. We show that our IV method is effective in minimizing potential bias. It is found that the share of confirmed COVID-19 cases increases the possibility of consumers purchasing food online. This is more likely to be the case for young people having a lower perceived risk of online purchases and living in large cities. Despite some limitations, this paper has policy implications for China and other countries that have been influenced by the COVID-19 epidemic. Specifically, government support and regulation should focus on (i) ensuring the safety of food sold on the internet, (ii) protecting the carrier from becoming infected, and (iii) providing financial support to the poor since they may have difficulties in obtaining access to food living in small cities. Moreover, how to help those who are unable to purchase food online because of their technical skills (e.g., the elderly who are not familiar with smart phones or the internet) also deserves more attention for the government and the public. [ABSTRACT FROM AUTHOR]

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]

The pandemic caused by coronavirus disease 2019(COVID-19) continues to disrupt the global supply chain system, bringing new risks and challenges. The uncertainty created by COVID-19 makes it is difficult for various industries to deal with the pandemic. Since the pandemic, the supply chain's resilience has been discussed and examined in some studies. However, most existing works start from a single industry perspective or pay more attention to the disturbance caused by changes in the production side. Supply chain networks of different industries, mainly transport networks, are relatively limited under the epidemic's impact. In this paper, from the perspective of highway freight transport, a comprehensive competitiveness evaluation framework was proposed to reveal and the disruption and resilience of the supply chain under the outbreak based on nine indexes with five dimensions, including efficiency, capacity, activity, connectivity, and negotiability. Based on the availability of the data(Large-scale truck trajectory), we sorted out seven categories of Chinese industries(related to highway transport) and divided them into four categories respectively: (a) Slight disruption and worse resilience; (b) Slight disruption and remarkable resilience; (c) Serious disruption and worse resilience; (d) Serious disruption and remarkable resilience. The measurement results of supply chain network performance show that the industries (cold-chain, general products, and other industries) dominated by "Efficiency - Negotiability - Connectivity" are slightly disrupted (about 33%), forming a spatial diffusion with Wuhan(the city where the pandemic first broke out) as the disrupted center, spreading outward in a circle structure. Simultaneously, five urban agglomerations surrounding it have been impacted. By contrast, due to the strict isolation measures, the industries (building materials, construction, engineering, and high-value products industry) more vulnerable to be disrupted seriously (about 82%) tend to be the pattern of "Capacity - Activity". However, a large-scale centralized disruption was observed in the Triangle of Central China urban agglomeration was presented, resulting in almost stagnation of industry development. Meanwhile, as the future of the pandemic remains uncertain, the supply chain represented by the engineering industry, construction industry, etc are deserved to be paid more attention in line with they are prone to large-scale centralized damage due to the disruption of a single city node. • Disruption and resilience of multi-industry supply chain under COVID-19 epidemic. • Multi-dimensional comprehensive competitiveness evaluation framework for supply chain performance. • Supply chain destruction and repair performance of seven industries in China under COVID-19 epidemic. • Characteristic differences of supply chain between different industries from the perspective of highway freight transport. [ABSTRACT FROM AUTHOR]

The global outbreak of COVID-19 has further exposed deficiencies in city logistics based on human and ground roads, such as poor emergency response capacity and high risk of infection during transportation. Metro-based underground logistics system (M-ULS) may be an innovative approach to deal with this city-level disaster due to its efficient operation, contactless and driverless characteristics. However, the market evolution process and the quantitative calculation framework of comprehensive benefits after the application of M-ULS are still unclear, which has become a problem of mutual restriction with the extensive application of M-ULS. This paper attempts to use the system dynamics method, based on the real-world simulation, to analyze the quantitative relationship between the M-ULS implementation and the city logistics performance under epidemic outbreaks. Wuhan city in China was selected as the empirical background, and five simulation scenarios were set under different implementation strategies of M-ULS in response to the epidemic. Six variables were selected to measure city logistics performance and M-ULS operation status, including demand fill-rate, unit delivery time, total deprivation cost, total transportation cost, total number of susceptible people, and utilization rate of M-ULS. The results show that M-ULS is effective in improving the performance of city logistics and responding to the epidemic. The delivery time and transportation cost have a strong impact on the market share of M-ULS. Finally, a set of incentive policies was designed to promote the adoption of M-ULS. The findings not only provide a method for evaluating the overall performance of M-ULS, but also provide a unique perspective for promoting the implementation of M-ULS and responding to the transportation challenges brought by the epidemic. • M-ULS is introduced to break through the plight of city logistics. • A set of effective macro-micro incentive policies are established to promote the implementation of M-ULS. • The delivery time, transportation cost and government subsidies play different roles in the market penetration of M-ULS. • The benefits of M-ULS have been analyzed. [ABSTRACT FROM AUTHOR]

The coronavirus outbreak in Wuhan, China has sparked a global epidemic, which the World Health Organization declared a public health emergency of international concern on 31st January 2020 (Beijing time). This crisis has attracted intense media attention. Recently, some media outlets inappropriately labelled the coronavirus by race, using such headlines as "Chinese virus pandemonium" and even suggesting "China kids stay home." The biased and misleading coverage presented via Western media channels has incited anger throughout the Chinese community and has placed undue stress upon Chinese individuals living outside China. This post-published review takes a tourism-focused perspective to examine findings from a quantitative study (Rodriguez-Seijas, Stohl, Hasin, & Eaton, 2015) published in 2015 in JAMA Psychiatry. The current paper highlights the potential impacts of misleading and biased media coverage on Chinese individuals' mental health. Specifically, this work considers perceived racial discrimination stemming from coronavirus as a public health crisis and the effects of such discrimination on individuals of Chinese heritage. Similarly imperative are pertinent effects on country image and destination image with respect to tourism marketing and tourist behaviour during times of crisis. By considering racism in the context of the coronavirus outbreak, this paper identifies potential avenues for relevant research in tourism and hospitality. [ABSTRACT FROM AUTHOR]

Difficulties to use convenient data during the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic outbreak and complexities of the problem attitude crucial challenges in infectious disease modelling studies. Motivated by the on-going reach to predict a potential reactivated SARS-CoV-2 (COVID-19), we suggest a prediction model that beyond the clinical characteristics based evaluation approaches. In particular, we developed a possibly available and more efficient prediction model to predict a potential reactivated SARS-CoV-2 (COVID-19) patient. Our paper aims to explore the applicability of a modified Technique for Order Preference by Similarity to Ideal Solutions (MTOPSIS) integrated Design of Experiment (DoE) method to predict a potential reactivated COVID-19 patient in real-time clinical or laboratory applications. The presented novel model may be of interest to the readers studying similar research areas. We illustrate MTOPSIS integrated DoE method by applying it to the COVID-19 pandemic real clinical cases from Wuhan/China-based data. Despite the small sample size, our study provides an encouraging preliminary model framework. Finally, a step by step algorithm is suggested in the study for future research perspectives. [ABSTRACT FROM AUTHOR]

Coronavirus Disease 2019 (COVID-19), first reported in December 2019 from Wuhan in China, had reached the stage of a pandemic. To date (28.06.2021), there are more than 181.9 million confirmed cases of the disease in the world. Even though vaccines have been developed, antiviral drugs are yet to be developed for management and treatment of SARS-CoV-2. Since several medicinal plants are used in traditional medicines, though with controversial efficacy claims, they can be considered as sources of new antiviral drug compounds against emerging viruses. In this context, spices are noteworthy as their anti-oxidant, anti-viral, anti-inflammatory and immunostimulatory properties are well studied and documented. The emerging scientific literature includes a number of papers on the anti-SARS-CoV-2 activity of spice extracts and specific compounds proven through different types of laboratory experiments. Here, the information pertaining to anti-viral properties of spice-based phytochemicals or natural compounds (not crude extracts) is summarized in this review. Spice-based compounds discussed here are an option for testing in COVID-19 patients though we don't have strong data to support their active recommendation. Because of their natural origin, safety, and low cost, they can be a viable option in our fight against viruses and this compilation may be useful for planning and designing more robust experiments in future. [ABSTRACT FROM AUTHOR]

Thee coronavirus which appeared in December 2019 in Wuhan has spread out worldwide and caused the death of more than 330,000 people (as of May 29, 2020, submission date for the present article). Since February 2020, doubts were raised about the numbers of confirmed cases and deaths reported by the Chinese government. In this paper, we examine data available from China at the city and provincial levels and we compare them with Canadian provincial data, US state data and French regional data. We consider cumulative and daily numbers of confirmed cases and deaths and examine these numbers through the lens of their first two digits and in particular we measure departures of these first two digits to the Newcomb-Benford distribution, often used to detect frauds. Our finding is that there is no evidence that cumulative and daily numbers of confirmed cases and deaths for all these countries have different first or second digit distributions. We also show that the Newcomb-Benford distribution cannot be rejected for these data. [ABSTRACT FROM AUTHOR]

This paper examines the gendered impacts of the COVID-19 pandemic on the Chinese migrants who had returned to their hometowns for the Spring Festival before the Wuhan lockdown, using data from a recent nationally representative survey. The study finds that women migrants were less likely than men migrants to return to the cities and also less likely to return to paid work after the pandemic outbreak. It also finds that having a preschool-age child had a strong negative effect on women migrants' employment decisions, but it had no effect on men migrants' decisions. These results expand the literature on the economic vulnerabilities of Chinese migrant workers. More importantly,~the findings indicate that the COVID-19 pandemic has caused a setback in the~progress made in pre-pandemic times in advancing Chinese rural women's position in the labor market. HIGHLIGHTS The COVID-19 pandemic had negative employment consequences for Chinese migrant workers. Women migrants were the hardest hit and more likely to withdraw from migration flows and paid work. Women's caregiving roles and employment in face-to-face services are the main causes of their withdrawal. The pandemic has reinforced traditional gender roles and heightened labor market inequalities. [ABSTRACT FROM AUTHOR]

Coronavirus outbreak in Wuhan, China, turned into a pandemic in record time. Communication of disease presentation and mechanism of spread remain keys to getting ahead of the virus and limiting its spread beyond the capacity of management. Owing to huge academic focus and pandemic concern around the globe, this bibliometric analysis investigated research productivity related to coronavirus disease (COVID-19) pandemic using the Web of Science database. The relevant data were harvested, and search query was further refined by publication years (2020 OR 2019) and document types (article, book chapter, and proceedings paper). Finally, 6694 records were imported and downloaded in Plaintext and BibTeX formats on August 1, 2020. The data analysis was performed using MS Excel, VOS viewer, and Biblioshiny software. Of the 6694 publications that appeared in that period, the USA and Chinese research institutions topped the numbers. At the same time, the Journal of Medical Virology and CUREUS (Cureus Journal of Medical Science), remained favorite journals for publications. The pattern of multi-author publications has outstripped that of single-authors. Apart from COVID-19 and the novel coronavirus, the important keywords mentioned included pandemic, pneumonia, epidemiology, public health, outbreak, epidemic, China, infection, and treatment. The analysis shows a strong local research response from China, with large teams reporting on the disease outbreak. Subsequent studies will document a global response as the virus spreads worldwide. The initial research related to the current coronavirus outbreak was reported from within China. The data and patterns were supposed to alter as the virus spread globally. [ABSTRACT FROM AUTHOR]

The Coronavirus Disease 2019 (COVID-19) has proved a globally prevalent outbreak since December 2019. As a focused country to alleviate the epidemic impact, China implemented a range of public health interventions to prevent the disease from further transmission, including the pandemic lockdown in Wuhan and other cities. This paper establishes China's mobility network by a flight dataset and proposes a model without epidemiological parameters to indicate the spread risks through the network, which is termed as epidemic strength. By simply adjusting an intervention parameter, traffic volumes under different travel-restriction levels can be simulated to analyze how the containment strategy can mitigate the virus dissemination through traffic. This approach is successfully applied to a network of Chinese provinces and the epidemic strength is smoothly interpreted by flow maps. Through this node-to-node interpretation of transmission risks, both overall and detailed epidemic hazards are properly analyzed, which can provide valuable intervention advice during public health emergencies. [ABSTRACT FROM AUTHOR]

Purpose: The present study reflects the trend and growth of publications on COVID-19 viral disease spreading around the world. With the emergence of COVID-19 in Wuhan, China in December 2019, scholars started publishing their researches in form of different kind of publications. Methodology: The data has been extracted from the Scopus database using key TERMS Covid-19 and corona virus 2019. Findings: During six month period around ten thousand publications are contributed by scientists around the globe. The literature produced in different fields but highest output is made in the field of Medicine. BMJ and Journal of Medical Virology journals produced highest amount of research on COVID. Highest numbers of publications have been contributed by China based two institutions viz. Huazhong University of Science and Technology and Tongji Medical College, China. Mahase, E. of UK contributed maximum papers followed by Wiwanitkit, V. of China. [ABSTRACT FROM AUTHOR]

Covid-19 pandemic started in Wuhan in December 2019 and then spread to the rest of China and the world. This paper examines the relationship between inter-provincial migration and the diffusion of covid-19 outbreak in Mainland China from 26 January to 6 March 2020. Statistical analysis shows that the migrants who moved into Hubei in 2010–2015 are a good indicator of the population flow from Hubei to other provinces that caused the spread of covid-19 in early 2020. Many migrants traveled back to hometown before the traffic ban of Wuhan city for the spring holiday. Thus, the migration flow from a province to Hubei in the period 2010–2015 had the highest correlation coefficient with the number of covid-19 cases in four selected dates. The population flow based on the big data from the Baidu map on 20 January 2020 was also highly correlated with the number of cases, but not as good as the above migration data. The finding demonstrates the role of established migrant networks in the spread of covid-19. [ABSTRACT FROM AUTHOR]

Wuhan, a city of China, is the epicenter for the pandemic outbreak of coronavirus disease‐2019 (COVID‐19). It has become a severe public health challenge to the world and established a public health emergency of international worry. This infectious disease has pulled down the economy of almost all top developed nations. The coronaviruses (CoVs) known for various epidemics caused time to time. Infectious diseases such as severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS), followed by COVID‐19, are all coronaviruses led outbreaks that scourged the history of mankind. CoVs evolved themselves to more infectious, transmissible, and more pandemic with time. To prevent the spread of the SARS‐CoV‐2, many countries have ordered the complete lockdown to combat the outbreak. This paper briefly discussed the historical background of CoVs and the evolution of human coronaviruses (HCoVs), the case studies and the development of their antiviral medications. The viral infection encountered with present‐day challenges and futuristic approaches with the help of nanotechnology to minimize the spread of infectious viruses. The antiviral drugs and their clinical advances, along with herbal medicines for viral inhibition and immunity boosters, are described. Elaboration of tables related to CoVs for the compilation of the literature has been adopted for the better understanding. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) pneumonia, firstly reported in Wuhan, Hubei province, China, has rapidly spread around the world with high mortality rate among critically ill patients. The use of corticosteroids in COVID-19 remains a major controversy. Available evidences are inconclusive. According to WHO guidance, corticosteroids are not recommended to be used unless for another reason. Chinese Thoracic Society (CTS) proposes an expert consensus statement that suggests taking a prudent attitude of corticosteroid usage. In our clinical practice, we do not use corticosteroids routinely; only low-to-moderate doses of corticosteroids were given to several severely ill patients prudently. In this paper, we will present two confirmed severe COVID-19 cases admitted to isolation wards in Optical Valley Campus of Tongji hospital, Tongji Medical College, Huazhong University of Science and Technology. We will discuss questions related to corticosteroids usages. [ABSTRACT FROM AUTHOR]

We propose a varying coefficient Susceptible-Infected-Removal (vSIR) model that allows changing infection and removal rates for the latest corona virus (COVID-19) outbreak in China. The vSIR model together with proposed estimation procedures allow one to track the reproductivity of the COVID-19 through time and to assess the effectiveness of the control measures implemented since Jan 23 2020 when the city of Wuhan was lockdown followed by an extremely high level of self-isolation in the population. Our study finds that the reproductivity of COVID-19 had been significantly slowed down in the three weeks from January 27th to February 17th with 96.3% and 95.1% reductions in the effective reproduction numbers R among the 30 provinces and 15 Hubei cities, respectively. Predictions to the ending times and the total numbers of infected are made under three scenarios of the removal rates. The paper provides a timely model and associated estimation and prediction methods which may be applied in other countries to track, assess and predict the epidemic of the COVID-19 or other infectious diseases. [ABSTRACT FROM AUTHOR]

Since December 2019, a novel coronavirus pneumonia (COVID-19) has broken out in Wuhan, China and spread rapidly. Recent studies have found that ⁓ 15.7% of patients develop severe pneumonia, and cytokine storm is an important factor leading to rapid disease progression. Currently, there are no specific drugs for COVID-19 and the cytokine storm it causes. IL-6 is one of the key cytokines involved in infection-induced cytokine storm. Tocilizumab, which is the IL-6 receptor antagonist, has been approved by the US FDA for the treatment of cytokine release syndrome (CRS), is expected to treat cytokine storm caused by COVID-19 and is now in clinical trials. In this paper, we will elaborate the role of cytokine storm in COVID-19, the mechanism of tocilizumab on cytokine storm and the key points of pharmaceutical care based on the actual clinical application for COVID-19 in our hospital, the latest research reports, clinical trial progress of tocilizumab, drug instruction from the US FDA, and "Diagnosis and Treatment Plan of Novel Coronavirus Pneumonia (seventh trial edition)" in China, so as to provide reference for the treatment of COVID-19. [ABSTRACT FROM AUTHOR]

The emergence of an unusual Corona virus (COVID-19) flu pandemic starting in China in December 2019, spreading all around the globe is a major threat to public health. The investigations have shown this virus originated from a seafood market in Wuhan. However, the unavailability of medicines for the new disease is a big challenge all around. An attempt has been made in the present article to familiarise about the morphology of the virus. The study of effect of pH, temperature and relative humidity is also depicted. Various preventive measures have also been discussed. The natural dietary measures suggested in the paper would be very beneficial to improve and boost the immunity of the mankind. [ABSTRACT FROM AUTHOR]

The emergence of an unusual Corona virus (COVID-19) flu pandemic starting in China in December 2019, spreading all around the globe is a major threat to public health. The investigations have shown this virus originated from a seafood market in Wuhan. However, the unavailability of medicines for the new disease is a big challenge all around. An attempt has been made in the present article to familiarise about the morphology of the virus. The study of effect of pH, temperature and relative humidity is also depicted. Various preventive measures have also been discussed. The natural dietary measures suggested in the paper would be very beneficial to improve and boost the immunity of the mankind. [ABSTRACT FROM AUTHOR]

• The latest summary of the COVID-19 outbreak in China; • There might be an oral-fecal transmission of the virus; • Aggregates and consolidates the epidemiology, clinical manifestations, diagnosis, treatments and preventions of this new type of coronavirus. There is a current worldwide outbreak of the novel coronavirus Covid-19 (coronavirus disease 2019; the pathogen called SARS-CoV-2; previously 2019-nCoV), which originated from Wuhan in China and has now spread to 6 continents including 66 countries, as of 24:00 on March 2, 2020. Governments are under increased pressure to stop the outbreak from spiraling into a global health emergency. At this stage, preparedness, transparency, and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak site and from laboratories supporting the investigation. This paper aggregates and consolidates the epidemiology, clinical manifestations, diagnosis, treatments and preventions of this new type of coronavirus. [ABSTRACT FROM AUTHOR]

In December 2019, a new virus (initially called 'Novel Coronavirus 2019-nCoV' and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China, and rapidly spread to other parts of China and other countries around the world, despite China's massive efforts to contain the disease within Hubei. As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza, geographic information systems and methods, including, among other application possibilities, online real-or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time, are proving indispensable for timely and effective epidemic monitoring and response. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the 2019/2020 coronavirus epidemic and associated events as they unfold around the world. Some of these dashboards and applications are receiving data updates in near-real-time (at the time of writing), and one of them is meant for individual users (in China) to check if the app user has had any close contact with a person confirmed or suspected to have been infected with SARS-CoV-2 in the recent past. We also discuss additional ways GIS can support the fight against infectious disease outbreaks and epidemics. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19), first reported in December 2019 in Wuhan, China, has progressed to a pandemic associated with substantial morbidity and mortality. Little is known about the healthcare workers who died fighting the disease in China. This paper analyzed the data of 78 Chinese healthcare workers who died in the fight against COVID-19 between 23 January and 2 June, 2020, and revealed the following characteristics. First, compared to the number of deaths directly attributable to COVID-19, more healthcare workers died from pre-existing disease attack induced by excessive fatigue or died from accidents. Second, the median age of the healthcare workers who died directly from COVID-19 was younger than that of the Wuhan non- healthcare workers who died of COVID 19. Third, although more women than men were involved in fighting the pandemic, more men died. Fourth, more healthcare workers died in Hubei than in other provinces. Fifth, most of the healthcare workers who died directly from COVID-19 were non-professionals. [ABSTRACT FROM AUTHOR]

An outbreak of coronavirus disease (COVID-19) in Wuhan, China caused by SARS-CoV-2 has led to a serious epidemic in China and other countries, resulting in worldwide concern. With active efforts of prevention and control, more and more patients are being discharged. However, how to manage these patients normatively is still challenging. This paper reports an asymptomatic discharged patient with COVID-19 who retested positive for SARS-CoV-2, which arouses concern regarding the present discharge standards of COVID-19. [ABSTRACT FROM AUTHOR]

• A deep learning COVID-19 diagnostic system is developed using state-of-the-art deep learning architectures. • A detailed analysis of different methods used for detecting COVID-19 is presented in this paper. • Chest X-rays from different sources are collected to build a robust classification model. • The developed diagnostic model provided efficient results, even with a limited number of input images. • The results produced in this work are validated by an expert radiologist. In recent months, a novel virus named Coronavirus has emerged to become a pandemic. The virus is spreading not only humans, but it is also affecting animals. First ever case of Coronavirus was registered in city of Wuhan, Hubei province of China on 31st of December in 2019. Coronavirus infected patients display very similar symptoms like pneumonia, and it attacks the respiratory organs of the body, causing difficulty in breathing. The disease is diagnosed using a Real-Time Reverse Transcriptase Polymerase Chain reaction (RT-PCR) kit and requires time in the laboratory to confirm the presence of the virus. Due to insufficient availability of the kits, the suspected patients cannot be treated in time, which in turn increases the chance of spreading the disease. To overcome this solution, radiologists observed the changes appearing in the radiological images such as X-ray and CT scans. Using deep learning algorithms, the suspected patients' X-ray or Computed Tomography (CT) scan can differentiate between the healthy person and the patient affected by Coronavirus. In this paper, popular deep learning architectures are used to develop a Coronavirus diagnostic systems. The architectures used in this paper are VGG16, DenseNet121, Xception, NASNet, and EfficientNet. Multiclass classification is performed in this paper. The classes considered are COVID-19 positive patients, normal patients, and other class. In other class, chest X-ray images of pneumonia, influenza, and other illnesses related to the chest region are included. The accuracies obtained for VGG16, DenseNet121, Xception, NASNet, and EfficientNet are 79.01%, 89.96%, 88.03%, 85.03% and 93.48% respectively. The need for deep learning with radiologic images is necessary for this critical condition as this will provide a second opinion to the radiologists fast and accurately. These deep learning Coronavirus detection systems can also be useful in the regions where expert physicians and well-equipped clinics are not easily accessible. [ABSTRACT FROM AUTHOR]

Large-scale and diffuse population flow amplifies the localized COVID-19 outbreak into a widespread pandemic. Network analysis provides a new methodology to uncover the topology and evolution of the population flow and understand its influence on the early dynamics of COVID-19 transmission. In this paper, we simulated 42 transmission scenarios to show the distribution of the COVID-19 outbreak across China. We predicted some original (Guangzhou, Shanghai, Shenzhen) had higher total aggregate population outflows than Wuhan, indicating larger spread scopes and faster growth rates of COVID-19 outbreak. We built an importation risk model to identify some major cities (Dongguan and Foshan) with the highest total importation risk values and the highest standard deviations, indicating the core transmission chains (Dongguan-Shenzhen, Foshan-Guangzhou). We built the population flow networks to analyze their Spatio-temporal characteristics and identify the influential sub-groups and spreaders. By removing different influential spreaders, we identified Guangzhou can most influence the network's topological characteristics, and some major cities' degree centrality was significantly decreased. Our findings quantified the effectiveness of travel restrictions on delaying the epidemic growth and limiting the spread scope of COVID-19 in China, which helped better derive the geographical COVID-19 transmission related to population flow networks' structural features. • 42 transmission scenarios were simulated to test contribution of different original epicenters to seeding COVID-19 in China. • An importation risk model was built to test contribution of population flow among multiple epicenters to spreading COVID-19. • A population flow network was built to capture evolution of COVID-19 transmission and identify influential spreaders. • This paper quantified the effectiveness of travel restrictions on reducing the numbers of confirmed COVID-19 cases in China. [ABSTRACT FROM AUTHOR]

This study presents an in-depth investigation on the transmission of the novel coronavirus (COVID-19) from the urban perspective. It focuses on the "aftermath" of the outbreak and the spread of the infection among cities. Especially, this study provides insights of the fundamentals of the factors that may affect the spread of the infection in cities, where the marginal effects of some most influential factors to the virus transmission are estimated. It reveals that the distance to epicenter is a very strong influential factor, and is negatively linked with the spread of COVID-19. In addition, subway, wastewater and residential garbage are positively connected with the virus transmission. Moreover, both urban area and population density are negatively associated with the spread of COVID-19 at the early stage of the epidemic. Furthermore, this study also provides high precision estimation of the number of COVID-19 infection in Wuhan city, which is the epicenter of the outbreak in China. Based on the real-world data of cities outside Wuhan on March 2, 2020, the estimated number is 56,944.866 (mean value), which is very close to the officially reported number. The methodology and main conclusions shown in this paper are of general interest, and they can be applied to other countries to help understand the local transmission of COVID-19 as well. • This study presents an in-depth investigation on the transmission of the novel coronavirus (COVID-19) from the urban perspective. • It provides insights of the fundamentals of the factors that may affect the spread of the infection in cities. • It also provides high precision estimation of the number of COVID-19 infection in Wuhan city, which is the epicenter of the outbreak in China. • The methodology and main conclusions shown in this paper are of general interest, and they can be applied elsewhere. [ABSTRACT FROM AUTHOR]

This paper investigates the imppact of COVID-19 travel restrictions on population flow in the People's Republic of China. We discover an "unreasonable" surge in population flow after the Wuhan travel ban. We further find out that such a sure of population flow is attributed to the "spill-over" effect of the Wuhan travel ban. We utilize a logistic regression model to quantify that the spill-over effect linearly decays with the travel distance to the Pandemic center city. Because of the "spill-over" effect of the travel ban policy, government authorities should design redundancy polity to simultaneously implement a travel ban for the pandemic center city and its neighboring cities to restrain human movement and pandemic transmission. • We discovered the "spill-over" effect of the Wuhan travel ban. • A travel ban policy may stimulate human movement if it's not properly designed • The transportation distance to the COVID-19 pandemic center city negatively linearly determines the "spill-over" effect. • The "spill-over" effects can help city administrators to predicate population flow and make traffic control plans when pandemic outbreaks. [ABSTRACT FROM AUTHOR]

In November 2019, the novel coronavirus disease COVID-19 was reported in Wuhan city, China, and was reported in other countries around the globe. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Strategies such as contact tracing and a vaccination program have been imposed to keep COVID-19 under control. Furthermore, a fast, noninvasive and reliable testing device is needed urgently to detect COVID-19, so that contact can be isolated and ringfenced before the virus spreads. Although the reverse transcription polymerase chain reaction (RT-PCR) test is considered the gold standard method for the diagnosis of SARS-CoV-2 infection, this test presents some limitations which cause delays in detecting the disease. The antigen rapid test (ART) test, on the other hand, is faster and cheaper than PCR, but is less sensitive, and may limit SARS-CoV-2 detection. While other tests are being developed, accurate, noninvasive and easy-to-use testing tools are in high demand for the rapid and extensive diagnosis of the disease. Therefore, this paper reviews current diagnostic methods for COVID-19. Following this, we propose the use of expired carbon dioxide (CO2) as an early screening tool for SARS-CoV-2 infection. This system has already been developed and has been tested on asthmatic patients. It has been proven that expired CO2, also known as capnogram, can help differentiate between respiratory conditions and, therefore, could be used to detect SARS-CoV-2 infection, as it causes respiratory tract-related diseases. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 is a kind of systemic virus, and lungs are not the only target organ. SARS-CoV-2 attacks digestive system, urogenital system, nervous system and circulatory system. Some new mechanisms about SARS-CoV-2 invading human cell. SARS-CoV-2 plays an important role in "Inflammatory Cascade". Since early December 2019, a number of pneumonia cases associated with unknown coronavirus infection were identified in Wuhan, China, and many additional cases were identified in other regions of China and in other countries within 3 months. Currently, more than 80,000 cases have been diagnosed in China, including more than 3000 deaths. The epidemic is spreading to the rest of the world, posing a grave challenge to prevention and control. On February 12, 2020, the International Committee on Taxonomy of Viruses and the World Health Organization officially named the novel coronavirus and associated pneumonia as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19), respectively. According to the recent research on SARS-CoV-2, the virus mainly infects the respiratory system but may cause damage to other systems. In this paper, we will systematically review the pathogenic features, transmission routes, and infection mechanisms of SARS-CoV-2, as well as any adverse effects on the digestive system, urogenital system, central nervous system, and circulatory system, in order to provide a theoretical and clinical basis for the diagnosis, classification, treatment, and prognosis assessment of SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

Summary: Since cases first emerged in December 2019, COVID‐19 (a type of coronavirus) has rapidly become pandemic. This fast‐tracked paper (published quickly) from China on COVID‐19 is written by dermatologists at the epicentre of the outbreak in Wuhan. Dermatology clinic staff may be at risk because protective equipment is not routinely available, and skin lesions might possibly transmit the virus indirectly. These authors suggest preventive measures based on experience in this and previous coronavirus outbreaks. Online consultation for non‐urgent patients reduces the numbers of patients attending clinics. Nurse‐led triage, to identify patients with possible COVID‐19, at the entrances of hospital and skin clinics directs patients with a cough or fever to a specific COVID‐19 area and a dermatologist is consulted if the fever might be related to skin disease. Clinic staff wear N95 masks and observe hand hygiene during consultations. Patients are admitted to a ward only if routine blood tests and chest CT scans exclude COVID‐19. Triage will not detect patients who are showing no symptoms but who are developing the disease, so the hospital should provide an on‐call expert team to discuss inpatients suspected or diagnosed with COVID‐19 and refer them to radiology, respiratory or intensive care colleagues as required. Confirmed cases are managed following local policies. Skin disorders in COVID‐19 inpatients can usually be managed remotely using photographs, email and teleconferencing. If necessary a multidisciplinary team (a team of medical staff from different specialties) can meet in the clean area of the isolation ward. If the dermatologist must see the patient, all records should be provided in advance to minimise exposure time. With these precautions, as of 20th February 2020 no infected patients were detected in the Wuhan Dermatology Department. This is a summary of the study: Emergency management for preventing and controlling nosocomial infection of 2019 novel coronavirus: implications for the dermatology department Linked Article: Tao et al. Br J Dermatol 2020; 182:1477–1478 [ABSTRACT FROM AUTHOR]

The sudden outbreak of the COVID-19 pandemic has brought drastic changes to people's daily lives, work, and the surrounding environment. Investigations into these changes are very important for decision makers to implement policies on economic loss assessments and stimulation packages, city reopening, resilience of the environment, and arrangement of medical resources. In order to analyze the impact of COVID-19 on people's lives, activities, and the natural environment, this paper investigates the spatial and temporal characteristics of Nighttime Light (NTL) radiance and Air Quality Index (AQI) before and during the pandemic in mainland China. The monthly mean NTL radiance, and daily and monthly mean AQI are calculated over mainland China and compared before and during the pandemic. Our results show that the monthly average NTL brightness is much lower during the quarantine period than before. This study categorizes NTL into three classes: residential area, transportation, and public facilities and commercial centers, with NTL radiance ranges of 5–20, 20–40 and greater than 40 (nW· cm − 2 · sr − 1 ), respectively. We found that the Number of Pixels (NOP) with NTL detection increased in the residential area and decreased in the commercial centers for most of the provinces after the shutdown, while transportation and public facilities generally stayed the same. More specifically, we examined these factors in Wuhan, where the first confirmed cases were reported, and where the earliest quarantine measures were taken. Observations and analysis of pixels associated with commercial centers were observed to have lower NTL radiance values, indicating a dimming behavior, while residential area pixels recorded increased levels of brightness after the beginning of the lockdown. The study also discovered a significant decreasing trend in the daily average AQI for mainland China from January to March 2020, with cleaner air in most provinces during February and March, compared to January 2020. In conclusion, the outbreak and spread of COVID-19 has had a crucial impact on people's daily lives and activity ranges through the increased implementation of lockdown and quarantine policies. On the other hand, the air quality of mainland China has improved with the reduction in non-essential industries and motor vehicle usage. This evidence demonstrates that the Chinese government has executed very stringent quarantine policies to deal with the pandemic. The decisive response to control the spread of COVID-19 provides a reference for other parts of the world. [ABSTRACT FROM AUTHOR]

Background: The current outbreak of COVID-19 infection, which started in Wuhan, Hubei province, China, in December 2019, is an ongoing challenge and a significant threat to public health requiring surveillance, prompt diagnosis, and research efforts to understand a new, emergent, and unknown pathogen and to develop effective therapies. Despite the increasing number of published studies on COVID-19, in all the examined studies the lack of a well-defined pathophysiology of death among patients who died following COVID-19 infection is evident. Autopsy should be considered mandatory to define the exact cause of death, thus providing useful clinical and epidemiologic information as well as pathophysiological insights to further provide therapeutic tools. Methods: A literature review was performed on PubMed database, using the key terms: "COVID-19", "nCov 19", and "Sars Cov 2". 9709 articles were retrieved; by excluding all duplicated articles, additional criteria were then applied: articles or abstracts in English and articles containing one of the following words: "death", "died", "comorbidity", "cause of death", "biopsy", "autopsy", or "pathological". Results: A total of 50 articles met the inclusion criteria. However, only 7 of these studies reported autopsy-based data. Discussion: The analysis of the main data from the selected studies concerns the complete analysis of 12,954 patients, of whom 2269 died (with a mortality rate of 17.52%). Laboratory confirmation of COVID-19 infection was obtained in all cases and comorbidities were fully reported in 46 studies. The most common comorbidities were: cardiovascular diseases (hypertension and coronary artery disease), metabolic disorders (diabetes, overweight, or obesity), respiratory disorders (chronic obstructive pulmonary disease), and cancer. The most common reported complications were: acute respiratory distress syndrome (ARDS), acute kidney injury, cardiac injury, liver insufficiency, and septic shock. Only 7 papers reported histological investigations. Nevertheless, only two complete autopsies are described and the cause of death was listed as COVID-19 in only one of them. The lack of postmortem investigation did not allow a definition of the exact cause of death to determine the pathways of this infection. Based on the few histopathological findings reported in the analyzed studies, it seems to be a clear alteration of the coagulation system: frequently prothrombotic activity with consequent thromboembolism was described in COVID-19 patients. As a scientific community, we are called on to face this global threat, and to defeat it with all the available tools necessary. Despite the improvement and reinforcement of any method of study in every field of medicine and science, encouraging the autopsy practice as a tool of investigation could also therefore, help physicians to define an effective treatment to reduce mortality. [ABSTRACT FROM AUTHOR]

COVID-19 (SARS-CoV-2) is currently a global pandemic. This paper will attempt to estimate global infection rates and potential resultant mortality in the absence of effective treatment and/or vaccination. Calculations are based on World Health Organisation data from Wuhan in China: 14% of infected cases are severe, 5% require intensive care and 4% die. Estimated infection rates and mortality rates at the level of continents and some individual countries (when these are of sufficient size) are tabulated. This pandemic may cause close to half a billion deaths, i.e. 6% of the global population - and potentially more. At the risk of sounding sensational, but with a sober sense of realism, healthcare risks being plunged into the Middle-Ages if the public do not do their part. Infection cannot occur in the absence of contact. The only way to mitigate these numbers is to apply social distancing and take the standard precautions so frequently reiterated by Public Health: hand washing, avoid touching the face and so on. These measures are crucial as the human cost is going to be unthinkable even in the best-case scenarios that epidemiologists are modelling. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]