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Unlike in developed countries, most public toilets in China do not provide toilet paper onsite and users must bring their toilet paper. Moreover, an open waste bin is placed in each user's cubicle to collect used toilet paper and tissues. Such practices, which are common in East Asia and central America, have induced a dilemma of toilet paper disposal because some municipalities have removed waste bins from public toilets to prevent virus transmission by fecal matter. As a consequence, users were forced to flush down their used toilet paper and tissues. Yet, it is unknown whether standard toilet paper can be flushed easily without causing issues in sewer operations. Here, we surveyed the conditions of toilets in university campus and other public facilities in different regions across China. We also evaluated the disintegration characteristics of toilet paper products both by conducting online surveys and by physical disintegration experiments. We found that only 15% of toilets provided toilet paper, while open waste bins occurred at nearly all sites. Further, our survey indicated that 82% of toilet paper products sold in China did not give any indication on their flushability, whereas 77% of US products did. Disintegration results showed that none of the five popular, best-selling toilet paper products passed the flushability standard. We propose strategies to solve the current toilet paper dilemma in developing communities. [ABSTRACT FROM AUTHOR]

During the last three years, numerous research papers have been reported which use social media data to explore several issues related to the COVID-19 pandemic. Bibliometric methods in this work are used to analyze 1427 peer-reviewed documents from the last three years extracted from the Web of Science database. The results of this study show that there was high growth in publications in open access journals with an annual rate reaching 19.3% and they also identify the top cited journals and research papers. The thematic analysis of papers shows that research topics related to social media for surveillance and monitoring of public attitudes and perceptions, mental health, misinformation, and fake news are important and well-developed, whereas topics related to distance-learning education with social media are emerging. The results also show that the USA, China, and the UK have published many papers and received a high number of citations because of their strong international collaboration. [ABSTRACT FROM AUTHOR]

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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]

When labeling an infectious disease, officially sanctioned scientific names, e.g., "H1N1 virus," are recommended over place-specific names, e.g., "Spanish flu." This is due to concerns from policymakers and the WHO that the latter might lead to unintended stigmatization. However, with little empirical support for such negative consequences, authorities might be focusing on limited resources on an overstated issue. This paper empirically investigates the impact of naming against the current backdrop of the 2019–2020 pandemic. The first hypothesis posited that using place-specific names associated with China (e.g., Wuhan Virus or China Virus) leads to greater levels of sinophobia, the negative stigmatization of Chinese individuals. The second hypothesis posited that using a scientific name (e.g., Coronavirus or COVID-19) leads to increased anxiety, risk aversion, beliefs about contagiousness of the virus, and beliefs about mortality rate. Results from two preregistered studies [ N(Study 1) = 504; N(Study 2) = 412], conducted across three countries with the first study during the early outbreak (April 2020) and the second study at a later stage of the pandemic (August 2020), found no evidence of any adverse effects of naming on sinophobia and strong support for the null hypothesis using Bayesian analyses. Moreover, analyses found no impact of naming on anxiety, risk aversion, beliefs about contagiousness of the virus, or beliefs about mortality rate, with mild to strong support for the null hypothesis across outcomes. Exploratory analyses also found no evidence for the effect of naming being moderated by political affiliation. In conclusion, results provide no evidence that virus naming impacted individual's attitudes toward Chinese individuals or perceptions of the virus, with the majority of analyses finding strong support for the null hypothesis. Therefore, based on the current evidence, it appears that the importance given to naming infectious diseases might be inflated. [ABSTRACT FROM AUTHOR]

Purpose: This study is an attempt to evaluating the growth of scientific literature in the domain of coronavirus and Covid-19 pandemic research based on scientometric indicators: prolific countries and relative citation impact (RCI); influential institutions; author analysis and network, h-index and citation; DC (degree of collaboration), CC (collaboration coefficient), MCI (modified collaboration index) in the subject domain of coronavirus and Covid-19 research. Design/methodology/approach: The authors adopted approaches to obtain the literature data from Scopus database from 2000 to 2020 by conducting a systematic search using keywords related to the studied subject domain. In total, 15,297 numbers of records were considered for the literature analysis considering the real significant growth of this subject domain. This study presented the scientometric analysis of these publications. Furthermore, statistical correlations have been used to understand the collaboration pattern. Visualization tool VOSviewer is used to construct the co-author network. Findings: The present study found that 53.57% (8,195) of the research documents published on the open-access platform. Journal of Virology was found to be most preferred journal by the researcher producing around 839(5.48%) articles. USA and China dominate in the research output, and the University of Hong Kong has produced the highest number of research paper 547(3.58%). A significant portion of the research documents are published in the subject domain of medicine (49.70%), followed by immunology and microbiology (35.72%), and biochemistry, genetics and molecular biology subject domains (22.32%). There has been an unparalleled proliferation of publications on COVID-19 since January 2020 and also a significant distribution of research funds across the globe. Research limitations/implications: The study exclusively examines 15,297 research outputs which have been indexed in the Scopus database from 2000 to 2020 (till 01 April 2020). Thus, documents published in any other different channels and sources which are not covered in Scopus are excluded from the purview of research. Practical implications: It will be beneficial for researchers and practitioners worldwide for understanding the growth of scientific literature in the coronavirus and COVID-19 and identifying potential collaborator. Originality/value: Considering the global impact and social distress due to the outbreak of COVID-19 pandemic, this study is significant in the present scenario for identifying the growth of scientific literature in this field and evolving of this domain of research around the globe. The research results are useful to identify valuable research patterns from publications and of developments in the field of coronavirus and COVID-19. [ABSTRACT FROM AUTHOR]

Grassland ecosystems are vital terrestrial ecosystems. As areas sensitive to climate change, they are critical for assessing the effects of global climate change. In China, grasslands account for over 40% of the land area. There is currently limited information on microbial diversity evolution in different grassland areas, particularly microorganisms with ice nucleation activity (INA) and their potential resources with potential influence to regulate regional precipitation and climate. We used Illumina MiSeq to sequence the 16S rRNA V3-V4 hypervariable region and performed a simple droplet freezing experiment to determine the variation in the grassland microbial community species composition and community structure. Rainwater and topsoil samples from the Hulunbuir Grassland in Inner Mongolia collected over three years were characterized. The dominant bacterial genus in the rainwater was Massilia, and the dominant fungus was Cladosporium. Additionally, the dominant bacteria in the soil were Sphingomonas, and the dominant fungus was Gibberella. There were differences in the microbial communities before and after the coronavirus disease epidemic. Pathogenic microorganisms exhibited inconsistent responses to environmental changes. The low relative abundance of known high-INA microorganisms and the higher freezing temperature indicated that unknown high-efficiency biological ice nucleating particles may be present. We found significant differences in species diversity and richness between the rainwater and soil populations in grassland areas by analyzing the sample community structures. Our research results revealed the species composition and structure of the microbiota in grassland ecosystems in China, indicating that environmental media and human activities may affect the microbiota in the grassland area and indicating underlying microorganisms with high INA., 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 © 2021 Elsevier B.V. All rights reserved.)

This paper explores a contingent sub-public sphere promoted by a group of former critical journalists in China during the coronavirus outbreak at the beginning of 2020. During the initial outbreak of coronavirus in China, the observed former journalists, who left the field of critical journalism during the re-structure of Chinese news industries under Xi Jinping's leadership, drew on their knowledge of Chinese politics and censorship to contest information cover-up by the state, online censorship, and the state's discourses of China as a successful model of combating the virus. Their activities effectively engaged mass participation of Chinese people and promoted critical opinions of the public. The paper bears the primary aim to deepen the understanding of the episodic formation of elite-driven public spheres in China by investigating the nuances of each case. I therefore, in this particular case study, explore concepts of habitus and capital from Bourdieu's field theory as analytical tools in the investigation of the persistence of political participation and government scrutiny by former critical journalists on social media after leaving the field of critical journalism. The empirical research combines materials collected through 15 former critical journalists' WeChat accounts between January and May 2020, along with in-depth interviews. [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]

This paper investigates, for the first time, the presence of financial contagion among several important Chinese coronavirus concept-based stock indices during the recent COVID-19 global pandemic. We utilize a regime-switching skew-normal (RSSN) methodology to test for contagion through the correlation and coskewness channels while considering structural breaks in the different moments. Our results present evidence of contagion effects, which are robust across identified crisis and non-crisis periods, including that of the Wuhan lockdown. Our empirical results offer investors and policy-makers an additional layer of information when evaluating response mechanisms to major crises through the use of concept-based indices. [ABSTRACT FROM AUTHOR]

The novel coronavirus (COVID-19) that emerged and transmitted from China (Wuhan City) had a staggering effect on public health and the world economy. The early diagnosis of COVID-19 has become more important for its treatment and for controlling its spread due to its highly transmissible nature. In addition, the restricted supply of test kits calls for an alternative system for diagnosis. Since radiological images of chest of patients with COVID-19 show abnormalities, it is possible to diagnose COVID-19 utilizing chest X-ray images. Therefore, by applying deep convolution neural network (CNN), we have presented a diagnosis of COVID-19 based on chest X-ray images in this paper. For the diagnosis of COVID-19, an exhaustive comparative performance analysis of 16 state-of-the-art models is presented. Moreover, each model is trained with three approaches: transfer learning, fine tuning and scratch learning. The experiments were conducted on the dataset that comprises of 127 images of COVID-19, 500 images of Pneumonia and 500 images of normal cases. We have performed the experiments in two scenarios: binary classification (COVID-19 vs. Normal) and multiclass classification (COVID-19 vs. Pneumonia vs. Normal). Further, we have applied cost-sensitive learning technique to handle the class imbalance issue. In this study, InceptionResNetV2 model with fine-tuning approach achieved highest classification accuracy of 99.20% in binary classification and Xception model achieved classification accuracy of 89.33% in multiclass classification among all considered models. To validate our approach, we have presented the performance of our model on three other datasets and achieved adequate classification accuracy. Hence, the promising results demonstrate that the fine-tuning of deep CNN models is an effective way for diagnosis of COVID-19 and therefore, it can be deployed in diagnostic centers to assist radiologist after its validation with more prominent datasets. [ABSTRACT FROM AUTHOR]

Controlling anthropogenic mercury emissions is an ongoing effort and the effect of atmospheric mercury mitigation is expected to be impacted by accelerating climate change. The lockdown measures to restrict the spread of Coronavirus Disease 2019 (COVID-19) and the following unfavorable meteorology in Beijing provided a natural experiment to examine how air mercury responds to strict control measures when the climate becomes humid and warm. Based on a high-time resolution emission inventory and generalized additive model, we found that air mercury concentration responded almost linearly to the changes in mercury emissions when excluding the impact of other factors. Existing pollution control and additional lockdown measures reduced mercury emissions by 16.7 and 12.5 kg/d during lockdown, respectively, which correspondingly reduced the concentrations of atmospheric mercury by 0.10 and 0.07 ng/m 3 . Emission reductions from cement clinker production contributed to the largest decrease in atmospheric mercury, implying potential mitigation effects in this sector since it is currently the number one emitter in China. However, changes in meteorology raised atmospheric mercury by 0.41 ng/m 3 . The increases in relative humidity (9.5%) and temperature (1.2 °C) significantly offset the effect of emission reduction by 0.17 and 0.09 ng/m 3 , respectively, which highlights the challenge of air mercury control in humid and warm weather and the significance of understanding mercury behavior in the atmosphere and at atmospheric interfaces, especially the impact from relative humidity., 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 © 2020 Elsevier B.V. All rights reserved.)

The coronavirus disease (COVID-19) has become a global public health threaten. A series of strict prevention and control measures were implemented in China, contributing to the improvement of air quality. In this study, we described the trend of air pollutant concentrations and the incidence of COVID-19 during the epidemic and applied generalized additive models (GAMs) to assess the association between short-term exposure to air pollution and daily confirmed cases of COVID-19 in 235 Chinese cities. Disease progression based on both onset and report dates as well as control measures as potential confounding were considered in the analyses. We found that stringent prevention and control measures intending to mitigate the spread of COVID-19, contributed to a significant decline in the concentrations of air pollutants except ozone (O 3 ). Significant positive associations of short-term exposure to air pollutants, including particulate matter with diameters ≤2.5 μm (PM 2.5 ), particulate matter with diameters ≤10 μm (PM 10 ), and nitrogen dioxide (NO 2 ) with daily new confirmed cases were observed during the epidemic. Per interquartile range (IQR) increase in PM 2.5 (lag0-15), PM 10 (lag0-15), and NO 2 (lag0-20) were associated with a 7% [95% confidence interval (CI): (4-9)], 6% [95% CI: (3-8)], and 19% [95% CI: (13-24)] increase in the counts of daily onset cases, respectively. Our results suggest that there is a statistically significant association between ambient air pollution and the spread of COVID-19. Thus, the quarantine measures can not only cut off the transmission of virus, but also retard the spread by improving ambient air quality, which might provide implications for the prevention and control of COVID-19., 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 © 2020 Elsevier Ltd. All rights reserved.)

Although anthropogenic emissions decreased, polluted days still occurred in the Beijing-Tianjin-Hebei (BTH) region during the initial outbreak of the coronavirus disease (COVID-19). Analysis of the characteristics and source distribution of large-scale air pollution episodes during the COVID-19 outbreak (from 23 January to April 8, 2020) in the BTH region is helpful for exploring the efficacy of control measures and policy making. The results indicated that the BTH region suffered two large-scale air pollution episodes (23-28 January and 8-13 February), which were characterized by elevated PM 2.5 , SO 2 , NO 2 , and CO concentrations, while the O 3 concentration decreased by 1.5%-33.9% (except in Shijiazhuang, where it increased by 16.6% during the second episode). These large-scale air pollution episodes were dominated by unfavorable meteorological conditions comprising a low wind speed and increased relative humidity. The transport pathways and source distribution were explored using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT), potential source contribution function (PSCF), and concentration weighted trajectory (CWT) models. The air pollution in the BTH region was mainly affected by local emission sources during the first episode, which contributed 51.6%-60.6% of the total trajectories in the BTH region with a PM 2.5 concentration ranging from 146.2 μg/m 3 to 196.7 μg/m 3 . The short-distance air masses from the southern and southwestern areas of the BTH region were the main transport pathways of airflow arriving in the BTH region during the second episode. These contributed 51.9%-57.9% of the total trajectories and originated in Hebei, Henan, central Shanxi, and Shaanxi provinces, which were the areas contributing the most to the PM 2.5 level and exhibited the highest PSCF and CWT values. Therefore, on the basis of local emission reduction, enhancing regional environmental cooperation and implementing a united prevention and control of air pollution are effective mitigation measures for the BTH region., 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 © 2020 Elsevier Ltd. All rights reserved.)

To control the spread of the novel coronavirus disease 2019 (COVID-19) in China, many anthropogenic activities were reduced and even closed on the national scale. To study the impact of this reduction and closing down, hourly concentrations of PM 2.5 -related elements were measured at a rural site before (12-25 January 2020), during (26 January-9 February 2020) and after (22 March-2 April 2020) the control period when all people remained socially isolated in their homes and could not return to economic zones for work. Nine major sources were identified by the positive matrix factorization model, including fireworks burning, coal combustion, vehicle emissions, dust, Cr industry, oil combustion, Se industry, Zn smelter, and iron and steel industry. Before the control period, K, Fe, Ca, Zn, Ba and Cu were the main elements, and fireworks burning, Zn smelter and vehicle emissions provided the highest contributions to the total element mass with 55%, 12.1% and 10.3%, respectively. During the control period, K, Fe, Ba, Cu and Zn were the dominating elements, and fireworks burning and vehicle emissions contributed 55% and 27% of the total element mass. After the control period, Fe, K, Ca, Zn and Ba were the main elements, and dust and iron and steel industry were responsible for 56% and 21% of the total element mass. The increased contribution from vehicle emissions during the control period could be attributed to our sampling site being near a town hospital and the fact that the vehicle activities were not restricted. The source apportionment results were also related to air mass backward trajectories. The largest reductions of dust, coal combustion, and the industrial sources (Cr industry, Zn smelter, Se industry, iron and steel industry) were distinctly seen for northwest transport (Ulanqab) and were least significant for northeast transport (Tangshan and Tianjin)., 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 © 2020 Elsevier B.V. All rights reserved.)

Due to continuous spread of coronavirus disease 2019 (COVID-19) worldwide, long-term effective prevention and control measures should be adopted for public transport facilities, as they are increasing in popularity and serve as the principal modes for travel of many people. The human infection risk could be extremely high due to length of exposure time window, transmission routes and structural characteristics during travel or work. This can result in the rapid spread of the infection. Based on the transmission characteristics of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the nature of public transport sites, we identified comprehensive countermeasures toward the prevention and control of COVID-19, including the strengthening of personnel management, personal protection, environmental cleaning and disinfection, and health education. Multi-pronged strategies can enhance safety of public transportation. The prevention and control of the disease during the use of public transportation will be particularly important when all countries in the world resume production. The aim of this study is to introduce experience of the prevention and control measures for public transportation in China to promote the global response to COVID-19., 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 © 2020 Elsevier Ltd. All rights reserved.)

The novel coronavirus disease (COVID-19) is a highly pathogenic, transmittable and invasive pneumococcal disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which emerged in December 2019 and January 2020 in Wuhan city, Hubei province, China and fast spread later on the middle of February 2020 in the Northern part of Italy and Europe. This study investigates the correlation between the degree of accelerated diffusion and lethality of COVID-19 and the surface air pollution in Milan metropolitan area, Lombardy region, Italy. Daily average concentrations of inhalable particulate matter (PM) in two size fractions PM2.5, PM10 and maxima PM10 ground level atmospheric pollutants together air quality and climate variables (daily average temperature, relative humidity, wind speed, atmospheric pressure field and Planetary Boundary Layer-PBL height) collected during 1 January-30 April 2020 were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces, or direct human-to-human personal contacts, it seems that high levels of urban air pollution, weather and specific climate conditions have a significant impact on the increased rates of confirmed COVID-19 Total number, Daily New and Total Deaths cases, possible attributed not only to indoor but also to outdoor airborne bioaerosols distribution. Our analysis demonstrates the strong influence of daily averaged ground levels of particulate matter concentrations, positively associated with average surface air temperature and inversely related to air relative humidity on COVID-19 cases outbreak in Milan. Being a novel pandemic coronavirus (SARS-CoV-2) version, COVID-19 might be ongoing during summer conditions associated with higher temperatures and low humidity levels. Presently is not clear if this protein "spike" of the new coronavirus COVID-19 is involved through attachment mechanisms on indoor or outdoor airborne aerosols in the infectious agent transmission from a reservoir to a susceptible host in some agglomerated urban areas like Milan is., Competing Interests: Declaration of competing interest The authors declare no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 National Institute of R&D for Optoelectronics INOE 2000. Published by Elsevier B.V. All rights reserved.)

The novel coronavirus disease 2019 (COVID-19), which first emerged in Hubei province, China, has become a pandemic. However, data regarding the effects of meteorological factors on its transmission are limited and inconsistent. A mechanism-based parameterisation scheme was developed to investigate the association between the scaled transmission rate (STR) of COVID-19 and the meteorological parameters in 20 provinces/municipalities located on the plains in China. We obtained information on the scale of population migrated from Wuhan, the world epicentre of the COVID-19 outbreak, into the study provinces/municipalities using mobile-phone positioning system and big data techniques. The highest STRs were found in densely populated metropolitan areas and in cold provinces located in north-eastern China. Population density had a non-linear relationship with disease spread (linearity index, 0.9). Among various meteorological factors, only temperature was significantly associated with the STR after controlling for the effect of population density. A negative and exponential relationship was identified between the transmission rate and the temperature (correlation coefficient, -0.56; 99% confidence level). The STR increased substantially as the temperature in north-eastern China decreased below 0 °C (the STR ranged from 3.5 to 12.3 when the temperature was between -9.41 °C and -13.87 °C), whilst the STR showed less temperature dependence in the study areas with temperate weather conditions (the STR was 1.21 ± 0.57 when the temperature was above 0 °C). Therefore, a higher population density was linearly whereas a lower temperature (<0 °C) was exponentially associated with an increased transmission rate of COVID-19. These findings suggest that the mitigation of COVID-19 spread in densely populated and/or cold regions will be a great challenge., 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 © 2020 Elsevier B.V. All rights reserved.)

Since the outbreak of a cluster of patients with pneumonia of unknown cause in Wuhan, Hubei Province, China, in December 2019, the disease was later officially named coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), quickly spreading globally. Pregnant women and children are particularly vulnerable during disasters and emergencies. Comprehensive and applicable emergency preparedness and response are definitely important methods to prevent and contain the COVID-19 pandemic. The rational allocation of pharmaceutical resources plays an important role in the medical emergency plan. This paper aimed to share experiences for the allocation of pharmaceutical resources in hospitals focusing primarily on women and children during the COVID-19 pandemic.

Background: The coronavirus disease 2019 (COVID-19) is not just a disease of the respiratory system. The virus can affect the gastrointestinal (GI) tract as well. Recognizing the various manifestations in every organ system is important because these manifestations can contribute to community-based transmission. Methods:We outline the evidence of the pathophysiology of COVID-19 in the GI tract, the effects of the virus on the gut and liver, the presence of the virus in stool samples, and the potential for fecal-oral transmission of COVID-19. Most of the literature sources used in this paper are case studies from China following the surge of COVID-19 infection. Results: In patients with COVID-19, GI symptoms such as anorexia, nausea, vomiting, diarrhea, and abdominal pain have presented in conjunction with respiratory symptoms such as fever, shortness of breath, and cough. Evidence also shows acute hepatocellular injury, indicated by elevated liver enzymes such as alanine aminotransferase, aspartate aminotransferase, and gamma-glutamyl transferase. Fecal-oral transmission of COVID-19 is suspected because of the presence of COVID-19 RNA in stool samples of COVID-19-positive patients. Conclusion: Even without the presence of respiratory symptoms, several GI symptoms are associated with COVID-19 infection, as well as possible fecal-oral transmission. Therefore, COVID-19 infection should be considered for patients presenting with primarily GI symptoms. [ABSTRACT FROM AUTHOR]

This paper investigates the expected results of the current COVID-19 outbreak to arrivals of Chinese tourists to the USA and Australia. The growing market share of Chinese tourism and the fact that the county was the first to experience the pandemic make China a suitable proxy for predictions on global tourism. We employ data from the 2003 SARS outbreak to train a deep learning artificial neural network named Long Short Term Memory (LSTM). The neural network is calibrated for the particulars of the current pandemic. Our findings, which are cross-validated using backtesting, suggest that recovery of arrivals to pre-crisis levels can take from 6 to 12 months and this can have significant adverse effects not only on the tourism industry but also on other sectors that interact with it. [ABSTRACT FROM AUTHOR]

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.

Results: The outbreak of coronavirus disease 2019 (COVID-19) has become a primary challenging public health issue for not only China but also the world. On March 11, 2020, the World Health Organization declared that the pandemic of COVID-19 had become a public health emergency of global concern. As of May 12, 2020 COVID-19 has been reported in over 180 countries/regions, with a total of 4,178,156 confirmed cases and over 280,000 deaths. The risk of cross-infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might be elevated between dental specialists and patients due to the peculiarity of dental practice. Therefore, detailed and effective infection control measures are imminently needed to prevent nosocomial coronavirus infection. This paper, based on proven effective experience, relevant guidelines, and research, not only presents the fundamental knowledge about the name, etiologic characteristics, epidemiologic characteristics and clinical manifestations of COVID-19, transmission routes and risk points of SARS-CoV-2 in dental clinics but also provides recommended protective measures for dental professionals to interdict the transmission of SARS-CoV-2 in dental clinics. Classification schemes as well as color identification according to the results of the questionnaire survey and temperature measurement in precheck and triages are innovations proposed in this paper., Clinical Significance: This paper, based on proven effective experience, relevant guidelines, and research, not only presents the fundamental knowledge about the name, etiologic characteristics, epidemiologic characteristics and clinical manifestations of COVID-19, transmission routes and risk points of SARS-CoV-2 in dental clinics but also provides recommended protective measures for dental professionals to interdict the transmission of SARS-CoV-2 in dental clinics., Competing Interests: The authors declared no conflict of interest., (Copyright©American Journal of Dentistry.)

OBJECTIVE Various integrated Chinese and Western medicines might be beneficial for the treatment of Coronavirus disease 2019 (COVID-19). This study aims to evaluate the efficacy of lung computed tomography (CT) of four integrated Chinese and Western medicines in the treatment of COVID-19 using network meta-analysis (NMA). METHODS Multiple databases were consulted to find randomized controlled trials of four different types of integrated Chinese and Western medicines for the treatment of COVID-19. NMA was conducted on the data using Stata (13.0) software. The odds ratio (OR) was calculated. The studies included in this paper were divided into a control group (Western medicine) and an observation group (one of four integrated Chinese and Western medicines). RESULTS 5 eligible publications were identified. A total of 598 cases were included in the study, and the results showed that the four types of integrated Chinese and Western medicines (symptomatic and supportive care with Qingfei Touxie Fuzheng, Lianhua Qingke, and Xuebijing) were significantly superior (P < 0.05) to symptomatic and supportive care alone, except for symptomatic and supportive care with Lianhua Qingwen. The combination of symptomatic and supportive care with Lianhua Qingke had the highest probability of being the most clinically efficacious intervention, with a surface under the cumulative ranking (SUCRA) curve of 85.7. CONCLUSIONS A combination of symptomatic and supportive care with Lianhua Qingke is the best option among the four integrated Chinese and Western medicines considered for the treatment of COVID-19.

Social and economic factors relate to the prevention and control of infectious diseases. The purpose of this paper was to assess the distribution of COVID-19 morbidity rate in association with social and economic factors and discuss the implications for urban development that help to control infectious diseases. This study was a cross-sectional study. In this study, social and economic factors were classified into three dimensions: built environment, economic activities, and public service status. The method applied in this study was the spatial regression analysis. In the 13 districts in Wuhan, the spatial regression analysis was applied. The results showed that: 1) increasing population density, construction land area proportion, value-added of tertiary industry per unit of land area, total retail sales of consumer goods per unit of land area, public green space density, aged population density were associated with an increased COVID-19 morbidity rate due to the positive characteristics of estimated coefficients of these variables. 2) increasing average building scale, GDP per unit of land area, and hospital density were associated with a decreased COVID-19 morbidity rate due to the negative characteristics of estimated coefficients of these variables. It was concluded that it is possible to control infectious diseases, such as COVID-19, by adjusting social and economic factors. We should guide urban development to improve human health.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus first identified in Wuhan, China, and the etiological agent of Coronavirus Disease-2019 (COVID-19). This infection spreads mainly through direct contact with Flügge micro droplets or core droplets that remain suspended as aerosol. Moreover, it has been reported that infected subjects, both with and without clinical signs of COVID-19, can transmit the virus. Since the infection typically enters through mouth, nose, and eyes, dentistry is one of the medical practices at highest risk of infection due to the frequent production of aerosol and the constant presence of saliva. The World Health Organization (WHO) has suggested that only emergency/urgent procedures should be performed during the coronavirus outbreak. Considering the virus' route of transmission, a specific protocol should be applied to reduce the risk of infection in addition to measures that prevent the spread of infection from a patient to another person or medical tools and equipment (cross-infection). This protocol should be implemented by modifying both patient management and clinical practice, introducing particular devices and organizational practices. This paper aims to discuss and suggest the most appropriate procedures in every aspect of dental practice to reduce infection risk.

The outbreak of 2019 novel coronavirus disease (COVID-19) is spreading rapidly. In order to prevent cluster outbreaks, the government strengthened the management and control of personnel mobility, which had a great impact on the examination and treatment of breast cancer patients. This paper discusses how to realize scientific health management of breast cancer patients outside the hospital based on the existing epidemic situation, characteristics of breast cancer patients and public health safety factors. The breast cancer patients should synthetically consider the epidemic prevention situation of inhabitance, the disease stage and previous therapeutic schedule to decide the next therapeutic schedule. If necessary, after professional discussion and communication between doctors and patients online or offline, the hospital visiting time should be delayed through seeking alternative treatment schemes, and psychological counseling for patients should be paid attention to at the same time.

To investigate the effect of villagers' moral obligation and village cadres' public leadership on villagers' collective action for epidemic prevention and control, against the background of the corona virus disease 2019 (COVID-19) emergency in China, we constructed models based on the institutional analysis and development (IAD) framework and employed principal component analysis (PCA) and ordered probit regression, drawing on survey data from 533 villagers in Henan province adjacent to the COVID-19 origin province, Hubei, China. The results indicate that: (1) generally, both moral obligation and public leadership as well as their constituent indicators contributed positively to collective action for COVID-19 prevention and control; (2) moreover, moral obligation and public leadership can strengthen each other's positive role in collective action for COVID-19 prevention and control. Based on the above findings, this paper suggests that villagers' moral obligation can be perfected through internalizing epidemic prevention and control norms into the villagers' moral norms by the way of villagers mastering the rural public health governance scheme. In addition, public leadership can be improved through professional training of village cadres and by motivating village elites to run for village cadres. With improved villagers' moral obligation and village cadres' public leadership, collective action for epidemic prevention and control could be more likely to be realized.

Background: As part of the response plans for the current outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), authorities are drafting and implementing containment measures across jurisdictions worldwide in the effort to slow down transmission and reduce the infection rate. A solid communication strategy is needed to increase the reach of valid information to health professionals, reduce misinformation, and efficiently implement recommended measures., Objective: The aim of this paper is to describe the utilization of a dedicated mobile health (mHealth) platform to disseminate up-to-date and validated information about SARS-CoV-2 to all medical staff of the Children's Hospital at the University Hospitals of Geneva., Methods: Three documents containing institutional information concerning screening, local containment procedures, and frequently asked questions and answers for parents were made available to the staff through a mobile app developed in the University of Geneva, Switzerland. Using a third-party statistics tool, we anonymously monitored user activity as well as content utilization patterns since the diagnosis of the first case of SARS-CoV-2 in Switzerland on February 25, 2020., Results: From February 25, 2020, to March 13, 2020 (18 days), information documents on SARS-CoV-2 were viewed 859 times, which accounted for 35.6% of the total content views (total views=332). User activity increased significantly with 50.8 (SD 14.4) users per day in this period as compared to the previous weeks (mean 26.4, SD 9.8; P<.001). In addition, session numbers per day more than doubled during the aforementioned period (P<.001). In a survey, medical staff found the information easy to find within the app. On a 10-point Likert scale, the ability of the app to reassure staff in clinical practice was rated as 7.6 (SD 2.1), time-saving ability was rated as 8.5 (SD 2.1), and the need to look for information from other sources was rated as 5.9 (SD 3.3)., Conclusions: The use of an mHealth solution to disseminate novel coronavirus-related information seemed to be an effective and time-saving communication channel within our institution during the SARS-CoV-2 outbreak. Medical staff felt reassured and informed in daily practice. More research should be done on the clinical impact and outcomes of the integration of mHealth solutions as a communication channel of validated information within health institutions., (©Ido Zamberg, Sergio Manzano, Klara Posfay-Barbe, Olivier Windisch, Thomas Agoritsas, Eduardo Schiffer. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.04.2020.)

Previous epidemic management research proves the importance of city-level information, but also highlights limited expertise in urban data applications during a pandemic outbreak. In this paper, we provide an overview of city-level information, in combination with analytical and operational capacity, that define urban intelligence for supporting response to disease outbreaks. We present five components (movement, facilities, people, information, and engagement) that have been previously investigated but remain siloed to successfully orchestrate an integrated pandemic response. Reflecting on the coronavirus disease (COVID-19) outbreak that was first identified in Wuhan, China, we discuss the opportunities, technical challenges, and foreseeable controversies for deploying urban intelligence during a pandemic. Finally, we emphasize the urgency of building urban intelligence through cross-disciplinary research and collaborative practice on a global scale., (©Yuan Lai, Wesley Yeung, Leo Anthony Celi. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.04.2020.)

Coronavirus (COVID-19) is a humanitarian emergency, which started in Wuhan in China in early December 2019, brought into the notice of the authorities in late December, early January 2020, and, after investigation, was declared as an emergency in the third week of January 2020. The WHO declared this as Public Health Emergency of International Concern (PHEIC) on 31th of January 2020, and finally a pandemic on 11th March 2020. As of March 24th, 2020, the virus has caused a casualty of over 16,600 people worldwide with more than 380,000 people confirmed as infected by it, of which more than 10,000 cases are serious. Mainly based on Chinese newspapers, social media and other digital platform data, this paper analyzes the timeline of the key actions taken by the government and people over three months in five different phases. It found that although there was an initial delay in responding, a unique combination of strong governance, strict regulation, strong community vigilance and citizen participation, and wise use of big data and digital technologies, were some of the key factors in China's efforts to combat this virus. Being inviable and non-measurable (unlike radioactive exposure), appropriate and timely information is very important to form the basic foundation of mitigation and curative measures. Infodemic, as it is termed by WHO, is a key word, where different stakeholder's participation, along with stricter regulation, is required to reduce the impact of fake news in this information age and social media. Although different countries will need different approaches, focusing on its humanitarian nature and addressing infodemic issues are the two critical factors for future global mitigation efforts.

The recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously known as 2019-nCoV) outbreak has engulfed an unprepared world amidst a festive season. The zoonotic SARS-CoV-2, believed to have originated from infected bats, is the seventh member of enveloped RNA coronavirus. Specifically, the overall genome sequence of the SARS-CoV-2 is 96.2% identical to that of bat coronavirus termed BatCoV RaTG13. Although the current mortality rate of 2% is significantly lower than that of SARS (9.6%) and Middle East respiratory syndrome (MERS) (35%), SARS-CoV-2 is highly contagious and transmissible from human to human with an incubation period of up to 24 days. Some statistical studies have shown that, on average, one infected patient may lead to a subsequent 5.7 confirmed cases. Since the first reported case of coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 on December 1, 2019, in Wuhan, China, there has been a total of 60,412 confirmed cases with 1370 fatalities reported in 25 different countries as of February 13, 2020. The outbreak has led to severe impacts on social health and the economy at various levels. This paper is a review of the significant, continuous global effort that was made to respond to the outbreak in the first 75 days. Although no vaccines have been discovered yet, a series of containment measures have been implemented by various governments, especially in China, in the effort to prevent further outbreak, whilst various medical treatment approaches have been used to successfully treat infected patients. On the basis of current studies, it would appear that the combined antiviral treatment has shown the highest success rate. This review aims to critically summarize the most recent advances in understanding the coronavirus, as well as the strategies in prevention and treatment.

In a large-scale epidemic outbreak, there can be many high-risk individuals to be transferred for medical isolation in epidemic areas. Typically, the individuals are scattered across different locations, and available quarantine vehicles are limited. Therefore, it is challenging to efficiently schedule the vehicles to transfer the individuals to isolated regions to control the spread of the epidemic. In this paper, we formulate such a quarantine vehicle scheduling problem for high-risk individual transfer, which is more difficult than most well-known vehicle routing problems. To efficiently solve this problem, we propose a hybrid algorithm based on the water wave optimization (WWO) metaheuristic and neighborhood search. The metaheuristic uses a small population to rapidly explore the solution space, and the neighborhood search uses a gradual strategy to improve the solution accuracy. Computational results demonstrate that the proposed algorithm significantly outperforms several existing algorithms and obtains high-quality solutions on real-world problem instances for high-risk individual transfer in Hangzhou, China, during the peak period of the novel coronavirus pneumonia (COVID-19).

Objective: To discuss the research progress in the field of coronavirus (CoVs) treatment based on the visualization analysis of knowledge graph., Methods: The related literatures in the field of CoVs treatment were retrieved from the establishment of Web of Science core collection database to February 15th, 2020, and the literature analysis tool of Web of Science database was used to count the annual trend of published literatures. The VOSviewer software was used to analyze the relationship among countries, institutions, authors, clustering and density of subject words. The HistCite software was used to screen important documents and to draw the evolution process of hot spots. The CiteSpace software was used to analyze the breakout points of subject words, so as to find the front and hot spots in this field., Results: A total of 1 747 data were retrieved, with the exception of 17 duplicate data, and 1 730 data were retained for visualization analysis. In terms of literature volume, the literatures on CoVs therapy rose after 2003 and 2012, and the number of published literatures had remained high since 2014. In terms of countries, the main countries that carried out the research on the treatment of CoVs were the United States (n = 613), China (n = 582), Germany (n = 122), Canada (n = 99), etc., and the cooperation among countries was close. In terms of institutions, the number of papers issued by Chinese Academy of Sciences in the field of CoVs treatment ranked first (n = 82), followed by University of Hong Kong of China (n = 74) and Chinese University of Hong Kong of China (n = 58), followed by National Institute of Allergy and Infectious Diseases (n = 37), and the cooperation among various institutions was close. In terms of literature authors, there were two high-yielding authors in the United States [Ralph S. Baric (n = 21) and Kuochen Chou (n = 17)], two Chinese authors [Yuen Kwok-yung (n = 17) and Jiang Shibo (n = 16)] and one Dutch author [Eric J. Snijder (n = 17)]. In terms of the cluster analysis of authors, the authors were closely related in reverse genetics, respiratory infection, receptor binding domain, etc., and the 15 top-cited papers came mainly from China, the United States, Netherlands and other countries, and the literature content represented the frontiers and hot spots in different periods. The treatment hot spots focused on preventing virus adsorption, inhibiting the virus gene nucleic acid replication, transcription and translation. The main subject words were divided into three main categories, namely, CoVs epidemiology, basic research and drug development, in which basic research and drug development were strongly correlated. In the subject words breakthrough analysis, there were time-related breakthrough points in 1991, 1996 and 2002, and the "diagnosis" and "sequence" were continuous hot spots., Conclusions: Through the visualization analysis of knowledge graph, the development trend and hot spots of CoVs therapy research could be well observed. In this study, the degree of attention in the field of CoVs treatment showed periodic changes, related to the outbreak of new CoVs, and the country, institutions and the author were closely related. The treatment hot spots focused on preventing virus adsorption, inhibiting the virus gene nucleic acid replication, transcription and translation in order to develop new targets of drug.

Background: Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) has challenged public health agencies globally. In order to effectively target government responses, it is critical to identify the individuals most at risk of coronavirus disease-19 (COVID-19), developing severe clinical signs, and mortality. We undertook a systematic review of the literature to present the current status of scientific knowledge in these areas and describe the need for unified global approaches, moving forwards, as well as lessons learnt for future pandemics.Methods: Medline, Embase and Global Health were searched to the end of April 2020, as well as the Web of Science. Search terms were specific to the SARS-CoV-2 virus and COVID-19. Comparative studies of risk factors from any setting, population group and in any language were included. Titles, abstracts and full texts were screened by two reviewers and extracted in duplicate into a standardised form. Data were extracted on risk factors for COVID-19 disease, severe disease, or death and were narratively and descriptively synthesised.Results: One thousand two hundred and thirty-eight papers were identified post-deduplication. Thirty-three met our inclusion criteria, of which 26 were from China. Six assessed the risk of contracting the disease, 20 the risk of having severe disease and ten the risk of dying. Age, gender and co-morbidities were commonly assessed as risk factors. The weight of evidence showed increasing age to be associated with severe disease and mortality, and general comorbidities with mortality. Only seven studies presented multivariable analyses and power was generally limited. A wide range of definitions were used for disease severity.Conclusions: The volume of literature generated in the short time since the appearance of SARS-CoV-2 has been considerable. Many studies have sought to document the risk factors for COVID-19 disease, disease severity and mortality; age was the only risk factor based on robust studies and with a consistent body of evidence. Mechanistic studies are required to understand why age is such an important risk factor. At the start of pandemics, large, standardised, studies that use multivariable analyses are urgently needed so that the populations most at risk can be rapidly protected.Registration: This review was registered on PROSPERO as CRD42020177714 . [ABSTRACT FROM AUTHOR]

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A novel coronavirus which has appeared from China, has been circulating hastily around the world. We summarized the publications including oral manifestation of coronavirus disease 2019 (COVID‐19) cases based on PubMed and Google Scholar data bases, and also present a case that highlights oral lesions 2 days prior to the first COVID‐19 general symptoms. Two authors independently reviewed the papers, 17 studies of more than 170 confirmed cases between ages of 9 and 90 were included. The most common oral manifestation was dry mouth followed by dysgeusia and pseudomembranous fungal structure. Change in tongue sensation and ulceration, muscle pain during mastication, swelling in oral cavity, and herpetic lesions were other common symptoms. Associated symptoms, latency time, treatment, and prognosis have also been meticulously reviewed. We hope that careful clinical intraoral examination on all COVID‐19 positive patients and equally on any patients who need dental care will pave the way for further studies. [ABSTRACT FROM AUTHOR]

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The emergence of the novel coronavirus disease 2019 (COVID-19) is a serious global public health problem. The mystery around the causative agent was revealed on 7 January 2020 when the pathogen was isolated by Chinese scientists and named as novel coronavirus-2019 (2019-nCoV). With quicker reaction to the contagion, the number of scholarly research publications have increased exponentially, which calls for bibliometric analysis and review of the incipient studies. Therefore on 7 Feb 2020, the English language and Chinese publications on COVID-19 were retrieved from PubMed and CNKI (China National Knowledge Infrastructure). A retrospective bibliometric analysis was performed to gauge the output, language, document type, journal, authorship, geographical distribution, research focus, resulting in a total of 154 papers comprising 100 papers in English and another 54 in Chinese. There were 30 journals published at least 2 papers, and the Journal of Medical Virology published the most papers (11). China and USA were the most productive countries, and there were 24 international collaborative papers. Fudan University contributed the most papers. Isaac I. Bogoch, Kunling Shen, Xingguang LI, Hongzhou Lu were the most active authors as first authors, with 2 papers respectively. Among the 154 publications, 35 were opinions papers, and 30 were research articles. Papers were categorized by research areas, and five research foci were identified. Our study offers an overview of the incipient publications and quantitative information for future research on coronavirus. Besides, Chinese publications were also retrieved for an integrated data analysis and diversity comparison. [ABSTRACT FROM AUTHOR]

In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019-2020 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. The symptom of COVID-19 was reported first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting everyone having a smartphone and being able to take a picture to verify that his/her protection mask is correctly positioned on his/her face. Such application can be particularly useful for people using face protection mask for the first time and notably for children and old people. The designed method exploits Haar-like feature descriptors to detect key features of the face and a decision-making algorithm is applied. Experimental results show the potential of this method in the validation of the correct mask wearing. To the best of our knowledge, our work is the only one that currently proposes a mobile application design "CheckYourMask" for validating the correct wearing of protection mask. [ABSTRACT FROM AUTHOR]

A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence about its activity on the virus. It is of high significance to develop a drug that can combat the virus effectively to save valuable human lives. It usually takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods such as deep learning to develop drugs that can combat such a disease effectively since 2019-nCoV is highly homologous to SARS-CoV. In the present work, we first collected virus RNA sequences of 18 patients reported to have 2019-nCoV from the public domain database, translated the RNA into protein sequences, and performed multiple sequence alignment. After a careful literature survey and sequence analysis, 3C-like protease is considered to be a major therapeutic target and we built a protein 3D model of 3C-like protease using homology modeling. Relying on the structural model, we used a pipeline to perform large scale virtual screening by using a deep learning based method to accurately rank/identify protein–ligand interacting pairs developed recently in our group. Our model identified potential drugs for 2019-nCoV 3C-like protease by performing drug screening against four chemical compound databases (Chimdiv, Targetmol-Approved_Drug_Library, Targetmol-Natural_Compound_Library, and Targetmol-Bioactive_Compound_Library) and a database of tripeptides. Through this paper, we provided the list of possible chemical ligands (Meglumine, Vidarabine, Adenosine, d-Sorbitol, d-Mannitol, Sodium_gluconate, Ganciclovir and Chlorobutanol) and peptide drugs (combination of isoleucine, lysine and proline) from the databases to guide the experimental scientists and validate the molecules which can combat the virus in a shorter time. [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]

Originating in China, the coronavirus has reached the world at different speeds and levels of strength. This paper provides an initial understanding of some driving factors and their consequences. Since transmission requires people, the human factor behind globalisation is essential. Globalisation, a major force behind global well‐being and equality, is highly associated with this factor. The analysis investigates the impact globalisation has on the speed of initial transmission to a country and on the scale of initial infections in the context of other driving factors. Our cross‐country analysis finds that measures of globalisation are positively related to the spread of the virus, both in speed and in scale. However, the study also finds that globalised countries are better equipped to keep fatality rates low. The conclusion is not to reduce globalisation to avoid pandemics, but to better monitor the human factor at the outbreak and mobilise collaboration forces to curtail diseases. [ABSTRACT FROM AUTHOR]

Using daily data on the coronavirus disease 2019 (COVID-19) cases from China and the rest of the world, this paper investigates the corresponding effects on the global economic activity. The empirical results based on a structural vector autoregression model using crude oil prices (COP) and the Baltic Exchange Dry Index (BDI) are consistent with increases in COVID-19 cases acting as negative demand shocks in the global economic activity (reflected as reductions in COP) and negative supply shocks in the global transportation of commodities (reflected as increases in BDI). The historical decomposition results further suggest that the effects of COVID-19 cases on COP and BDI have been mostly observed in the early COVID-19 period. [ABSTRACT FROM AUTHOR]

This paper investigates intellectual discourse in China during the COVID-19 coronavirus crisis through two discourse analyses, aiming to see the role of intellectuals in leading public discussion and perception on government decisions in times of crisis. Digital ethnography and digital discourse analysis are implemented to do a micro and in-depth analysis of texts and the media engagement of the Chinese intellectuals. In the context in which the presence and reception of public intellectuals in China has been transformed from pro-West gongzhi (公知) to intellectuals in the system (体制内), this study reviews the moral values and norms that promoted governmental policies and social coherence embedded in a new intellectual discourse. It contributes to the analysis of the dynamics and flexibility of China's public communication in times of crisis within the social context in which online activities and offline realities are closely bonded in modern China. [ABSTRACT FROM AUTHOR]

The current COVID pandemic is happening while the long-term effects of coronavirus infection remain poorly understood. The present article meta-analyzed mental health outcomes (anxiety, depression, etc.) from a previous coronavirus outbreak in China (2002). CNKI, Wanfang, PubMed/Medline, Scopus, Web of Science, Baidu Scholar, and Google Scholar were searched up to early June 2020 for articles in English or Chinese reporting mental illness symptoms of SARS patients. Main outcome measures include SCL-90, SAS, SDS, and IES-R scales. 29 papers met the inclusion criteria. The longest follow-up time included in the analysis was 46 months. The systematic meta-analysis indicated that mental health problems were most serious before or at hospital discharge and declined significantly during the first 12 months after hospital discharge. Nevertheless, average symptom levels remained above healthy norms even at 12 months and continued to improve, albeit slowly, thereafter. The adverse mental health impact of being hospitalized with coronavirus infection long outlasts the physical illness. Mental health issues were the most serious for coronavirus infected patients before (including) hospital discharge and improved continuously during the first 12 months after hospital discharge. If COVID-19 infected patients follow a similar course of mental health development, most patients should recover to normal after 12 months of hospital discharge. [ABSTRACT FROM AUTHOR]