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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]

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]

Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported as a worldwide emergency. Due to the extensiveness of spread and death, it has been declared as a pandemic. This review focused on the current pandemic situation and understanding the prevention and control strategies of COVID-19. Data presented here was by April 3, 2020. A total of 1,016,399 cases of COVID-19 with 53,238 deaths was reported from 204 countries and territories including two international conveyances over the world. After China, most of the new cases were from Europe, particularly Italy acting as the source of importation to many of the other countries around the world. China has obtained success by ascribing control strategies against COVID-19. The implementation of China's strategy, as well as the development of a vaccine, may control the pandemic of COVID-19. Further robust studies are required for a clear understanding of transmission parameters, prevention, and control strategies of SARSCoV-2. This review paper describes the nature of COVID-19 and the possible ways for the effective controlling of the COVID-19 or similar viral diseases that may come in the future. [ABSTRACT FROM AUTHOR]

Copyright of Gazi Medical Journal is the property of Galenos Yayinevi Tic. LTD. STI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Released in China in the winter of 2019, COVID-19 (caused by SARS-CoV-2 virus) lead to a world pandemic and highly stressed all medical systems around the world. Although the knowledge of this new coronavirus is in development, the most common reason for hospitalization of patients with COVID-19 is a severe respiratory disorder. The thought that any nation can be an island in a coordinated worldwide economy is demonstrated off-base by the presence of the new COVID-19. Worldwide participation, in specific within the field of open wellbeing and financial advancement is basic. All major nations must take an interest effectively. It is as well late to act once the illness has taken hold in numerous other countries and attempt to shut borders once a widespread begun. The aim of this paper is to make an analysis as accurat as possible on the general picture of the pandemic with COVID-19, given that most studies have been conducted clinically and medically, and less in terms of economical effects of this pandemic, the end of which cannot yet be predicted. [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]

Background: Telehealth systems can significantly improve the triage, treatment and care of COVID-19 patients. Both patients and health providers are strongly motivated to use telehealth services, due to the quarantine and social distancing policies. Objective: This study aimed to systematically review the characteristics of telehealth-based services developed to support COVID-19 patients and/or healthcare providers. Material and Methods: A comprehensive search for the English language articles had been conducted up to 13 May 2020 using PubMed and Scopus electronic databases. In this review paper, only studies have been included that focus on a telehealth-based service to support COVID-19 patients and/or healthcare providers. Later, the general and detailed characteristics of the included studies were extracted. Results: In this review, fifteen out of the 1,291 retrieved articles met the study eligibility criteria. The studies came from 7 countries, where most of them (9, 56.25%) were conducted in the United States, and 3 (18.75%) of them implemented in China. The majority of studies (n=14, 93.4%) addressed patients as the telehealth recipients. Seven studies (46.6%) introduced a mobile application as the main means of the needed communication, followed by videoconferencing or video calls (6, 40%), and phone calls (5, 33.3%) as the media. 10 studies used a synchronous communication, four used an asynchronous communication, and one addressed both communications. Four studies (26.6%) developed a guideline-based telehealth tool. Of 15 included studies, seven (46.6%) addressed diagnosis, three (20%) prevention, three (20%) treatment, and three (20%) follow-up aspects of COVID-19. Totally, 10 group barriers were identified in literature. Conclusion: This review reveals the usefulness of the telehealth-based services during the COVID-19 outbreak. The existing challenges identified through the literature pointed out the need for clear guidelines, scientific evidence, and innovative policies to implement successful telehealth projects. [ABSTRACT FROM AUTHOR]

The coronavirus disease (COVID-19) outbreak reported in China in December 2019 has spread throughout the world. The WHO declared it as a pandemic in March 2020. The pandemic severely affected public health and the global economy. Many studies conducted on the coronavirus have helped us to elucidate its pathogenicity and pathophysiology. However, it is important to study the behavior of the pathogen in the environment to develop effective control measures. While studying the persistence and transmission of viruses in drinking water and wastewater systems, a low concentration of coronavirus and its nucleic acids have been detected in municipal wastewaters. This could be due to their high susceptibilities to degradation in aqueous environments. Epidemiological study on coronaviruses in wastewater will serve two purposes, i.e., in early detection of outbreak and in identifying asymptomatic carriers. In such cases, the epidemiological study will help in early detection of the presence of the virus in the community. Secondly, it will help in knowing if there are asymptomatic carriers, as such people do not show any signs of symptoms but shed the viruses in feces. The present review focuses on the epidemiological surveillance of wastewater for coronaviruses, as in recent years these are increasingly causing global pandemics. In this review we have discussed, the four pertinent areas of coronavirus study: (1) occurrence of coronavirus in wastewater, (2) wastewater based epidemiological surveillance of coronaviruses, (3) epidemiological surveillance tools used for detection of coronaviruses in sewage, and (4) persistence and sustainability of coronaviruses in wastewater. [ABSTRACT FROM AUTHOR]

A coronavirus disease-19 (COVID-19) caused by a novel coronavirus has appeared in China by the end of 2019 and later recognized as a global pandemic. This pandemic has evolved as a global public health menace. It has affected every aspect of human life. In line with these concerns, governments and the scientific community react promptly to the outbreak of this pandemic. These efforts are devoted to develop vaccine and curative medicines. Further efforts are dedicated to assessing the impacts of the pandemic in relation to socioeconomic, psychological, and environmental dimensions. In this regard, it is important to follow up developments and research activities on this global issue. The present work intended to tracking the current hotspots and research trends on COVID-19 in environmental fields. Bibliometric analysis and visualization mapping were utilized with the objective of revealing and evaluating the developments in knowledge on COVID-2019 and its impacts based on a collection of environmental sources. A sum of 729 documents were collected from Scopus database limiting to environmental sources only. Of all these publications, 563 (77.2%) were articles, 56 (7.7%) were reviews, and 110 (15.0%) were others. China has the highest share of publications (163; 22.4%). It is followed by the USA (139; 19.15), and Italy (110; 15.1%). Most publications on COVID-19 were in prestigious journals. The most productive institution at global level was Chinese Academy of Sciences, China (24 documents; 3.3%). The most prevalent topics are in relation to impacts of the pandemic on air quality, mental health, psychological, and economic aspects. The development of these topics is based on cross-sectional studies, evidence-based tools, remote sensing, satellite mapping, geographic information systems, market analysis and sampling. The progress of environmental research on COVID-19 will guide the development of global environmental strategies to control future global environmental risks. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic brought with it not only the risk of infection with a new virus but also the possibility of attacks on national security by affecting national critical infrastructure. Maintaining a greater focus on national security is a necessity in any situation. During this pandemic period, the most affected critical infrastructure sector is health. We hope that the measures taken will lead us to a stabilisation of the situation and not to witness a more pronounced affectation of this sector. We must also pay special attention to the trust in the public administration in order not to be undermined by state or non-state actors with various economic and geostrategic interests on the Romanian territory. [ABSTRACT FROM AUTHOR]

Copyright of Electronic Turkish Studies is the property of Electronic Turkish Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

COVID-19 is caused by a novel coronavirus (2019-nCoV), which was declared as a pandemic after it emerged in China 2019. A vast international effort has been conducted to prevent and treat COVID-19 due to its high transmissibility and severe morbidity and mortality rates, particularly in individuals with chronic co-morbidities. In addition, polymorphic variants increased the need for proper vaccination to overcome the infectivity of new variants that are emerging across the globe. Many treatment options have been proposed and more than 25 vaccines are in various stages of development; however, the infection peaks are oscillating periodically, which raises a significant question about the effectiveness of the prevention measures and the persistence of this pandemic disease. In this review, we are exploring the most recent knowledge and advances in the treatment and vaccination options as well as the new emerging variants of 2019-nCoV and the possible mitigation of one of the most aggressive pandemics in the last centuries. [ABSTRACT FROM AUTHOR]

The effective control over the outbreak of COVID-19 in China showcases a prompt government response, in which, however, the allocation of attention, as an essential parameter, remains obscure. This study is designed to clarify the evolution of the Chinese government's attention in tackling the pandemic. To this end, 674 policy documents issued by the State Council of China are collected to establish a text corpus, which is then used to extract policy topics by applying the latent dirichlet allocation (LDA) model, a topic modelling approach. It is found that the response policies take different tracks in a four-stage controlling process, and five policy topics are identified as major government attention areas in all stages. Moreover, a topic evolution path is highlighted to show internal relationships between different policy topics. These findings shed light on the Chinese government's dynamic response to the pandemic and indicate the strength of applying adaptive governance strategies in coping with public health emergencies. [ABSTRACT FROM AUTHOR]

A satellite survey of the cumulative radiant emissions from electric lighting across China reveals a large radiance decline in lighting from December 2019 to February 2020—the peak of the lockdown established to suppress the spread of COVID-19 infections. To illustrate the changes, an analysis was also conducted on a reference set from a year prior to the pandemic. In the reference period, the majority (62%) of China's population lived in administrative units that became brighter in March 2019 relative to December 2018. The situation reversed in February 2020, when 82% of the population lived in administrative units where lighting dimmed as a result of the pandemic. The dimming has also been demonstrated with difference images for the reference and pandemic image pairs, scattergrams, and a nightly temporal profile. The results indicate that it should be feasible to monitor declines and recovery in economic activity levels using nighttime lighting as a proxy. [ABSTRACT FROM AUTHOR]