Search

The recent COVID-19 pandemic, which broke at the end of the year 2019 in Wuhan, China, has infected more than 98.52 million people by today (January 23, 2021) with over 2.11 million deaths across the globe. To combat the growing pandemic on urgent basis, there is need to design effective solutions using new techniques that could exploit recent technology, such as machine learning, deep learning, big data, artificial intelligence, Internet of Things, for identification and tracking of COVID-19 cases in near real time. These technologies have offered inexpensive and rapid solution for proper screening, analyzing, prediction and tracking of COVID-19 positive cases. In this paper, a detailed review of the role of AI as a decisive tool for prognosis, analyze, and tracking the COVID-19 cases is performed. We searched various databases including Google Scholar, IEEE Library, Scopus and Web of Science using a combination of different keywords consisting of COVID-19 and AI. We have identified various applications, where AI can help healthcare practitioners in the process of identification and monitoring of COVID-19 cases. A compact summary of the corona virus cases are first highlighted, followed by the application of AI. Finally, we conclude the paper by highlighting new research directions and discuss the research challenges. Even though scientists and researchers have gathered and exchanged sufficient knowledge over last couple of months, but this structured review also examined technological perspectives while encompassing the medical aspect to help the healthcare practitioners, policymakers, decision makers, policymakers, AI scientists and virologists to quell this infectious COVID-19 pandemic outbreak. [ABSTRACT FROM AUTHOR]

This 21st century is notable for experiencing so many disturbances at economic, social, cultural, and political levels in the entire world. The outbreak of novel corona virus 2019 (COVID-19) has been treated as a Public Health crisis of global Concern by the World Health Organization (WHO). Various outbreak models for COVID-19 are being utilized by researchers throughout the world to get well-versed decisions and impose significant control measures. Amid the standard methods for COVID-19 worldwide epidemic prediction, easy statistical, as well as epidemiological methods have got more consideration by researchers and authorities. One main difficulty in controlling the spreading of COVID-19 is the inadequacy and lack of medical tests for detecting as well as identifying a solution. To solve this problem, a few statistical-based advances are being enhanced and turn into a partial resolution up-to some level. To deal with the challenges of the medical field, a broad range of intelligent based methods, frameworks, and equipment have been recommended by Machine Learning (ML) and Deep Learning. As ML and DL have the ability of identifying and predicting patterns in complex large datasets, they are recognized as a suitable procedure for producing effective solutions for the diagnosis of COVID-19. In this paper, a perspective research has been conducted in the applicability of intelligent systems such as ML, DL and others in solving COVID-19 related outbreak issues. The main intention behind this study is (i) to understand the importance of intelligent approaches such as ML and DL for COVID-19 pandemic, (ii) discussing the efficiency and impact of these methods in the prognosis of COVID-19, (iii) the growth in the development of type of ML and advanced ML methods for COVID-19 prognosis,(iv) analyzing the impact of data types and the nature of data along with challenges in processing the data for COVID-19,(v) to focus on some future challenges in COVID-19 prognosis to inspire the researchers for innovating and enhancing their knowledge and research on other impacted sectors due to COVID-19. [ABSTRACT FROM AUTHOR]

As of July 17, 2020, more than thirteen million people have been diagnosed with the Novel Coronavirus (COVID-19), and half a million people have already lost their lives due to this infectious disease. The World Health Organization declared the COVID-19 outbreak as a pandemic on March 11, 2020. Since then, social media platforms have experienced an exponential rise in the content related to the pandemic. In the past, Twitter data have been observed to be indispensable in the extraction of situational awareness information relating to any crisis. This paper presents COV19Tweets Dataset (Lamsal 2020a), a large-scale Twitter dataset with more than 310 million COVID-19 specific English language tweets and their sentiment scores. The dataset's geo version, the GeoCOV19Tweets Dataset (Lamsal 2020b), is also presented. The paper discusses the datasets' design in detail, and the tweets in both the datasets are analyzed. The datasets are released publicly, anticipating that they would contribute to a better understanding of spatial and temporal dimensions of the public discourse related to the ongoing pandemic. As per the stats, the datasets (Lamsal 2020a, 2020b) have been accessed over 74.5k times, collectively. [ABSTRACT FROM AUTHOR]

The novel coronavirus 2019 (COVID-19) emerges from the Chinese city Wuhan and its spread to the rest of the world, primarily affected economies and their businesses, leading to a global depression. The explanatory and cross-sectional regression approach assesses the impact of COVID-19 cases on healthcare expenditures, logistics performance index, carbon damages, and corporate social responsibility in a panel of 77 countries. The results show that COVID-19 cases substantially increase healthcare expenditures and decrease corporate social responsibility. On the other hand, an increase in the coronavirus testing capacity brings positive change in reducing healthcare expenditures, increased logistics activities, and corporate social responsibility. The cost of carbon emissions increases when corporate activities begin to resume. The economic affluence supports logistics activities and improves healthcare infrastructure. It linked to international cooperation and their assistance to supply healthcare logistics traded equipment through mutual trade agreements. The greater need to enhance global trade and healthcare logistics supply helps minimize the sensitive coronavirus cases that are likely to provide a safe and healthy environment for living. [ABSTRACT FROM AUTHOR]

The outbreak of the novel coronavirus (COVID-19) forced the governing bodies across the world to ban all kinds of travel involving the movement of people. However, the policymakers have been working hard to mobilize the movement of essential goods and services considering its importance in containing the pandemic. It signifies how important the establishment and maintenance of logistics and supply chain management (LSCM) operations are, both during the containment and the successive periods. Motivated with the paramount importance of LSCM operations during the rapid spread of the novel coronavirus (COVID-19) across the globe, this paper critically reviews the existing literature closely related to it. The main aim is to identify and enhance the understanding of the logistical characteristics that play a vital role during pandemics. The selection of the literature was done using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) methodology. The classification of the selected literature was done using a tripartite framework. Results show that researchers have focused mostly on "Post-event" (48.24%) management of logistical operations followed by the "Pre-event" (31.76%) and least in the "Integrated" (20%.) approaches. Furthermore, the analysis of the results provided useful insights that are discussed in detail. Also, twelve key areas have been identified that need due attention to improve the overall efficiency of the LSCM operations. We believe that the findings from this paper would be useful to the decision-makers and other stakeholders, as far as, maintaining efficient LSCM operations during as well after the pandemics are concerned. [ABSTRACT FROM AUTHOR]

The greatest challenge the world is facing today is to win the battle against COVID-19 pandemic as soon as possible. Until a vaccine is available, personal protection, social distancing, and disinfection are the main tools against SARS-CoV-2. Although it is quite infectious, the SARS-CoV-2 virus itself is an enveloped virus that is relatively fragile because its protective fatty layer is sensitive to heat, ultraviolet radiation, and certain chemicals. However, heat and liquid treatments can damage some materials, and ultraviolet light is not efficient in shaded areas, so other disinfection alternatives are required to allow safe re-utilization of materials and spaces. As of this writing, evidences are still accumulating for the use of ozone gas as a disinfectant for sanitary materials and ambient disinfection in indoor areas. This paper reviews the most relevant results of virus disinfection by the application of gaseous ozone. The review covers disinfection treatments of both air and surfaces carried out in different volumes, which varies from small boxes and controlled chambers to larger rooms, as a base to develop future ozone protocols against COVID-19. Published papers have been critically analyzed to evaluate trends in the required ozone dosages, as a function of relative humidity (RH), contact time, and viral strains. The data have been classified depending on the disinfection objective and the volume and type of the experimental set-up. Based on these data, conservative dosages and times to inactivate the SARS-CoV-2 are estimated. In small chambers, 10–20 mg ozone/m3 over 10 to 50 min can be sufficient to significantly reduce the virus load of personal protection equipment. In large rooms, 30 to 50 mg ozone/m3 would be required for treatments of 20–30 min. Maximum antiviral activity of ozone is achieved at high humidity, while the same ozone concentrations under low RH could result inefficient. At these ozone levels, safety protocols must be strictly followed. These data can be used for reducing significantly the viral load although for assuring a safe disinfection, the effective dosages under different conditions need to be confirmed with experimental data. [ABSTRACT FROM AUTHOR]

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

The world is experiencing a pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19. The USA is also suffering from a catastrophic death toll from COVID-19. Several studies are providing preliminary evidence that short- and long-term exposure to air pollution might increase the severity of COVID-19 outcomes, including a higher risk of death. In this study, we develop a spatiotemporal model to estimate the association between exposure to fine particulate matter PM2.5 and mortality accounting for several social and environmental factors. More specifically, we implement a Bayesian zero-inflated negative binomial regression model with random effects that vary in time and space. Our goal is to estimate the association between air pollution and mortality accounting for the spatiotemporal variability that remained unexplained by the measured confounders. We applied our model to four regions of the USA with weekly data available for each county within each region. We analyze the data separately for each region because each region shows a different disease spread pattern. We found a positive association between long-term exposure to PM2.5 and the mortality from the COVID-19 disease for all four regions with three of four being statistically significant. Data and code are available at our GitHub repository. Supplementary materials accompanying this paper appear on-line. [ABSTRACT FROM AUTHOR]

Nowadays, COVID-19 also known as novel coronavirus has become a global pandemic by causing severe respiratory tract infections in humans without any definite treatment or vaccine. Therefore, disease control measures include slowing down or averting the transfer of this viral infection from person to person. Continuous efforts are carried out to avoid the transmission of this disease to frontline healthcare personnel using single-use personal protective equipment (PPE). However, a critical shortage in this equipment around the world is becoming an alarming concern. Therefore, it is vital to present a possible alternative to overcome the acute shortage of protective gear such as face masks against this infectious disease which can have universal accessibility and is easily available. Additive manufacturing (AM), also known as 3D printing, is a possible solution to overcome the shortage of protective gear and can play a vital role in supporting their conventional production supplies during this global pandemic situation. In this context, this paper provides a brief background study of COVID-19, its conventional preventive measure, and a detailed overview regarding the latest AM efforts including designers' providers and makers in the 3D printing community. Moreover, numerous inquiries and questions such as technical factors, testing recommendations and characterization methods and biological concerns such as biocompatibility and sterilization for the AM manufactured medical devices are addressed in this paper. In the end, two examples of AM medical devices, i.e., face mask and Ambu bag ventilator, are presented and studied through numerical simulations. [ABSTRACT FROM AUTHOR]

Since March of 2020, billions of people worldwide have been asked to limit their social contacts in an effort to contain the spread of the SARS-CoV-2 virus. However, little research has been carried out to date on the impact of such social distancing measures on the social isolation levels of the population. In this paper, we study the impact of the pandemic on the social isolation of the Spanish population, by means of 32,359 answers to a citizen survey collected over a period of 7 months. We uncover (1) a significant increase in the prevalence of social isolation in the population, reaching almost 26%; (2) gender and age differences, with the largest prevalence of isolation among middle-aged individuals; (3) a strong relationship between economic impact and social isolation; and (4) differences in social isolation, depending on the number of COVID-19 protection measures and on the perception of coronavirus infection risk by our participants. Our research sheds quantitative light on the sociological impact of the pandemic, and enables us to identify key factors in the interplay between the deployment of non-pharmaceutical interventions to contain the spread of an infectious disease and a population's levels of social isolation. [ABSTRACT FROM AUTHOR]

Novel Coronavirus (COVID-19) has become one of the deadliest pandemics that has affected almost all the nations in the world. Lockdown and systematic re-opening of shopping malls, offices, etc. is still one of the major weapons against this virus. However, the government and medical agencies take long time to reopen the places due to risks involved in this deadly virus. The delay to reopen places has resulted in sharp decline in the growth of economy. In this paper a current context aware framework is proposed which uses multiple inputs for a specific region to decide whether to open it or not. The proposed framework used series of deep neural network models to generate recommendations specific to a particular region. Most of the inputs are real-time and readily available with the government. The main aim is to develop framework which can be used in any kind of pandemic even in small region to easily contain it. However, it has been tested using opensource data available for COVID-19. Data was crawled from web for 22 districts of Haryana state of India. Experimental result proved the efficiency of proposed framework. [ABSTRACT FROM AUTHOR]

The coronavirus disease COVID-19 has spread throughout the world and has been declared as a pandemic by the World Health Organization on March 11th, 2020. The COVID-19 is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). One possible mode of virus transmission is through surfaces in the healthcare settings. This paper reviews currently used disinfection strategies to control SARS-CoV-2 at the healthcare facilities. Chemical disinfectants include hypochlorite, peroxymonosulfate, alcohols, quaternary ammonium compounds, and hydrogen peroxide. Advanced strategies include no-touch techniques such as engineered antimicrobial surfaces and automated room disinfection systems using hydrogen peroxide vapor or ultraviolet light. [ABSTRACT FROM AUTHOR]

This review summarises and discusses recent findings concerning the pathophysiology, clinical presentation, diagnosis, treatment, and outcome of SARS-CoV-2-associated Guillain-Barre syndrome (SC2-GBS). By the end of December 2020, at least 220 patients with SC2-GBS have been published in 95 papers. SC2-GBS is most likely secondary due to an immune reaction against SARS-CoV-2 since the virus has not been found in the CSF of any SC2-GBS patient so far reported. SC2-GBS occurs in each age group and does not differ from non-SC2-GBS regarding clinical presentation and treatment, but the outcome of SC2-GBS is worse compared to non-CS2-GBS patients, and the prevalence/incidence of GBS most likely increased since the outbreak of the pandemic. Early diagnosis of SC2-GBS is warranted to apply appropriate treatment in due time and to improve the overall outcome from the infection. [ABSTRACT FROM AUTHOR]

The outbreak of severe acute respiratory syndrome coronavirus 2 is regarded as a highly contagious disease that has challenged the healthcare systems worldwide with confirmed cases approaching 12 million and more than 50,000 deaths. Considering the worldwide cases of novel coronavirus disease (COVID-19), it remains a pandemic and the vaccines and therapeutic agents have yet to be developed to stop the spread of this outbreak. Due to the unavailability of specific treatment for the COVID-19, it can be viewed that the risk of cluster infection will continue to be present within the intermittent and small-scale outbreaks. Though the COVID-19 has been identified as a communicable disease, the preventive measures and response policies in South Korea are effectively serving the purpose and gained the confidence to overcome the COVID-19 crisis. This paper includes the exploratory data analysis of COVID-19 cases in South Korea till July 8, 2020. South Korea has reported the lowest death rate with the majority of the deaths, associated with persons with underlying health conditions or elderly infected individuals. Currently the infected patients (total 989) remaining in South Korea are mild cases owing to its robust health care system and quarantine inspection procedures followed by the Ministry of Health and Welfare of South Korea to flatten the COVID-19 curve. Although the COVID-19 countermeasures taken by the South Korean government may not be conclusive or universal for all, but its exemplary approach to tackle COVID-19 can aid countries across the globe to strengthen their response system for the future outbreak of such an infectious disease. [ABSTRACT FROM AUTHOR]

Thousands of articles have been published regarding the coronavirus disease of 2019 (COVID-19). Most of them are not original research articles but reviews and editorials, and therefore, the absence of evidence-based guidelines has been evident. In parallel, the quality of manuscripts is questionable since the number of preprints has increased due to the need of fast publication of COVID-19-related articles. Furthermore, the number of retracted articles during the pandemic is exceptionally high. Media have an important role in the distribution of incorrect information, nevertheless individual people and policy makers are also responsible. As misinformation thrives in crisis periods, well-designed studies are needed to flatten the infodemic curve regarding prevention, diagnosis, and long-term complications of COVID-19. [ABSTRACT FROM AUTHOR]

Objective: To estimate the incidence and describe clinical characteristics and outcome of GBS in COVID-19 patients (COVID19-GBS) in one of the most hit regions during the first pandemic wave, Lombardia. Methods: Adult patients admitted to 20 Neurological Units between 1/3–30/4/2020 with COVID19-GBS were included as part of a multi-center study organized by the Italian society of Hospital Neuroscience (SNO). Results: Thirty-eight COVID19-GBS patients had a mean age of 60.7 years and male frequency of 86.8%. CSF albuminocytological dissociation was detected in 71.4%, and PCR for SARS-CoV-2 was negative in 19 tested patients. Based on neurophysiology, 81.8% of patients had a diagnosis of AIDP, 12.1% of AMSAN, and 6.1% of AMAN. The course was favorable in 76.3% of patients, stable in 10.5%, while 13.2% worsened, of which 3 died. The estimated occurrence rate in Lombardia ranges from 0.5 to 0.05 GBS cases per 1000 COVID-19 infections depending on whether you consider positive cases or estimated seropositive cases. When we compared GBS cases with the pre-pandemic period, we found a reduction of cases from 165 to 135 cases in the 2-month study period in Lombardia. Conclusions: We detected an increased incidence of GBS in COVID-19 patients which can reflect a higher risk of GBS in COVID-19 patients and a reduction of GBS events during the pandemic period possibly due to a lower spread of more common respiratory infectious diseases determined by an increased use of preventive measures. [ABSTRACT FROM AUTHOR]

The issue of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has created enormous threat to global health. In an effort to contain the spread of COVID-19, a huge amount of disinfectants and antibiotics have been utilized on public health. Accordingly, the concentration of disinfectants and antibiotics is increasing rapidly in various environments, including wastewater, surface waters, soils and sediments. The aims of this study were to analyze the potential ecological environment impacts of disinfectants and antibiotics by summarizing their utilization, environmental occurrence, distribution and toxicity. The paper highlights the promoting effects of disinfectants and antibiotics on antibiotic resistance genes (ARGs) and even antibiotic resistant bacteria (ARB). The scientific evidences indicate that the high concentration and high dose of disinfectants and antibiotics promote the evolution toward antimicrobial resistance through horizontal gene transformation and vertical gene transformation, which threaten human health. Further concerns should be focused more on the enrichment, bioaccumulation and biomagnification of disinfectants, antibiotics, antibiotic resistance genes (ARGs) and even antibiotic resistant bacteria (ARB) in human bodies. [ABSTRACT FROM AUTHOR]

2019-nCoV is a virulent virus belonging to the coronavirus family that caused the new pneumonia (COVID-19) which has spread internationally very rapidly and has become pandemic. In this research paper, we set forward a statistical model called SIR-Poisson that predicts the evolution and the global spread of infectious diseases. The proposed SIR-Poisson model is able to predict the range of the infected cases in a future period. More precisely, it is used to infer the transmission of the COVID-19 in the three Maghreb Central countries (Tunisia, Algeria, and Morocco). Using the SIR-Poisson model and based on daily reported disease data, since its emergence until end April 2020, we attempted to predict the future disease period over 60 days. The estimated average number of contacts by an infected individual with others was around 2 for Tunisia and 3 for Algeria and Morocco. Relying on inferred scenarios, although the pandemic situation would tend to decline, it has not ended. From this perspective, the risk of COVID-19 spreading still exists after the deconfinement act. It is necessary, therefore, to carry on the containment until the estimated infected number achieves 0. [ABSTRACT FROM AUTHOR]

In the recent SARS-CoV-2 pandemic, public health experts have emphasized testing, tracking infected people, and tracing their contacts as an effective strategy to reduce the spread of the virus. Several diagnostic methods are reported for detecting the coronavirus in clinical, research, and public health laboratories. Some tests detect the infection directly by detecting the viral RNA and other tests detect the infection indirectly by detecting the host antibodies. A diagnostic test during the pandemic should help make an appropriate clinical decision in a short period of time. Recently reported diagnostic methods for SARS-CoV-2 have varying throughput, batching capacity, requirement of infrastructure setting, analytical performance, and turnaround times ranging from a few minutes to several hours. These factors should be considered while selecting a reliable and rapid diagnostic method to help make an appropriate decision and prompt public health interventions. This paper reviews recent SARS-CoV-2 diagnostic methods published in journals and reports released by regulatory agencies. We compared the analytical efficiency including limit of detection, sensitivity, specificity, and throughput. In addition, we also looked into ease of use, affordability, and availability of accessories. Finally, we discuss the limitations of the methods and provide our perspectives on priorities for future test development. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has both exposed and created deep rifts in society. It has thrust us into deep ethical thinking to help justify the difficult decisions many will be called upon to make and to protect from decisions that lack ethical underpinnings. This paper aims to highlight ethical issues in six different areas of life highlighting the enormity of the task we are faced with globally. In the context of COVID-19, we consider health inequity, dilemmas in triage and allocation of scarce resources, ethical issues associated with research, ethical considerations relating to tracing apps, and exit strategies such as immunity passports and COVID-19 vaccines. Finally, we consider environmental issues in light of COVID-19. The paper also offers some ethical reflection on these areas as many parts of the world contemplate the recovery phase. [ABSTRACT FROM AUTHOR]

Maree-Cawthorn et al. ([3]) further examine some of the policy challenges posed by the COVID-19 pandemic that affect the future of sustainability. The SARS-COV-2 coronavirus now globally known as COVID-19 has generated a multi-faceted response since it was recognized by the World Health Organization as a pandemic in January 2020. Focus on the wildlife reservoir of the coronavirus as the ultimate source and wildlife trade as a major issue may be myopic because the issue of where the pandemic originated is only the opening act in the complex issues surrounding COVID-19. [Extracted from the article]

COVID-19, caused by the novel coronavirus strain SARS-CoV-2 that emerged in late 2019, has resulted in a global pandemic. COVID-19 was initially believed to occur less frequently in children with relatively mild disease. However, severe disease and varied presentations have been reported in infected children, one of such being intussusception. There have only been three reported cases of intussusception in the pediatric population infected with COVID-19. In this paper, we will discuss the management and treatment of a novel fourth case of COVID-19-associated intussusception. This case is the first reported in the USA and suggests that COVID-19 may be implicated in the development of intussusception. Pediatricians should consider the possibility of intussusception when a child with COVID-19 presents with abdominal pain. [ABSTRACT FROM AUTHOR]

COVID-19 is now recognized as the one of the most tempting challenges and largest tragedy of the century after the Second World War (Gautam [1]). A novel respiratory disease has been reported in late December 2019 in Wuhan a city of the Hubei Province of China, and its now underlined by WHO (World Health Organization) as coronavirus disease-2019 (COVID-19) (WHO [6]; Gautam and Hens [3]). The purpose of this issue is to call for scientific original papers on the role that the environment could play in transmission, pathogenesis, and severity of COVID-19 and/or its related mortality. [Extracted from the article]

Copyright of Herz is the property of Springer Nature 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.)

The still ongoing pandemic of SARS-CoV-2 virus and COVID-19 disease, affecting the population worldwide, has demonstrated the need of more accurate methodologies for assessing, monitoring, and controlling an outbreak of such devastating proportions. Authoritative attempts have been made in traditional fields of medicine (epidemiology, virology, infectiology) to address these shortcomings, mainly by relying on mathematical and statistical modeling. However, here, we propose approaching the methodological work from a different, and to some extent alternative, standpoint. Applied systematically, the concepts and tools of statistical engineering and quality management, developed not only in healthcare settings, but also in other scientific contexts, can be very useful in assessing, monitoring, and controlling pandemic events. We propose a methodology based on a set of tools and techniques, formulas, graphs, and tables to support the decision-making concerning the management of a pandemic like COVID-19. This methodological body is hereby named Pandemetrics. This name intends to emphasize the peculiarity of our approach to measuring, and graphically presenting the unique context of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Contradictory results have been reported regarding effects of the SARS-CoV-2 upon human semen. A timely and up-to-date systematic review with meta-analysis appears necessary. This study aimed to deliver pooled prevalence (PP) of SARS-CoV-2 in semen and pooled semen parameters as compared with the uninfected. The relevant databases were scanned by two authors for observational studies reporting analysis of semen in COVID-19 patients. The SARS-CoV-2-infected were assigned to group A (exposed arm), whereas the uninfected to group B (unexposed arm). Newcastle–Ottawa Scale was used to address the risk of bias. PRISMA guidelines were adopted. In case of homogenous studies, fixed-effects model was followed, whereas for heterogenous studies random-effects model was used. Of 990 studies, 24 were eligible involving 1589 subjects (947 in group A and 642 in group B). The "comparability" domain was biased the most. SARS-CoV-2 RNA was detected in three studies among 8 individuals producing the PP of 1.76% (95% CI 0.72–3.21). Sperm concentration was reduced significantly (WMD = –16.23 [95% CI –25.56 to –6.89], as well as total sperm in ejaculate (WMD = –34.84 [95% CI − 43.51 to –26.17]) and sperm volume (WMD = − 0.48 [95% CI − 0.59 to − 0.36] in group A as compared with controls. There was a non-significant effect upon progressive motility and leukocyte presence in semen. SARS-CoV-2 RNA in semen among the infected individuals is detected infrequently. By this token, sexual transmission through semen is of low probability and little concern for public health. However, significant decrease in sperm volume, sperm concentration, and total sperm in ejaculate has been noted. The current data, though, are limited, and more studies with longer follow-up are needed to evaluate the further impact. [ABSTRACT FROM AUTHOR]

The global COVID-19 pandemic resulted in strict social distancing measures restricting close physical contact. Men (cis and trans) and other gender diverse people who have sex with men (MGDSM) are at higher risk of sexually transmitted infections (STIs) and may have experienced changes in sexual behavior during government restrictions on social and sexual contact. We aimed to examine self-reported sexual behavior of MGDSM during the first UK-wide lockdown to identify the characteristics of the individuals who might most require sexual health promotion and clinical support. In April–May 2020, we conducted an online survey of MGDSM, promoted on social media and Grindr. Our exploratory approach used descriptive analysis to identify self-reported changes in sexual behavior and performed regression analyses to identify correlates of casual sex during the lockdown. A total of 1429 respondents completed the survey: mean age 36 years, 84% White, 97% male or trans male, 98% assigned male sex at birth, 2% female or non-binary, 65% degree educated or higher. During the lockdown, 76% reported not having any casual sex partners. While the majority reported reduced casual sex, 3% reported an increase in casual sex with one person and 2% with three or more people (group sex). About 12% of the sample engaged in casual sex with only one person and 5% with four or more sexual partners during the lockdown. Reporting casual sex during lockdown was associated with: lower level of education OR = 2.37 [95% CI 1.40–4.01]; identifying as a member of an ethnic minority OR = 2.27[1.40–3.53]; daily usage of sexual networking apps OR = 2.24[1.54–3.25]; being less anxious about contracting SARS-CoV-2 through sex OR = 1.66[1.12–2.44]; using PrEP before lockdown OR = 1.75[1.20–2.56]; continuing to use PrEP OR = 2.79[1.76–4.57]; and testing for STIs during lockdown OR = 2.65[1.76–3.99]. A quarter of respondents remained sexually active with casual partners, indicating a need to provide STI screening services and health promotion targeted to groups most likely to have need over this period. Future research is required to better understand how to support sexual and gender minorities to manage sexual risk in the context of pandemic public health initiatives. [ABSTRACT FROM AUTHOR]

The novel coronavirus (SARS-CoV-2), or COVID-19, has emerged and spread at fast speed globally; the disease has become an unprecedented threat to public health worldwide. It is one of the greatest public health challenges in modern times, with no proven cure or vaccine. In this paper, our focus is on a fractional order approach to modeling and simulations of the novel COVID-19. We introduce a fractional type susceptible–exposed–infected–recovered (SEIR) model to gain insight into the ongoing pandemic. Our proposed model incorporates transmission rate, testing rates, and transition rate (from asymptomatic to symptomatic population groups) for a holistic study of the coronavirus disease. The impacts of these parameters on the dynamics of the solution profiles for the disease are simulated and discussed in detail. Furthermore, across all the different parameters, the effects of the fractional order derivative are also simulated and discussed in detail. Various simulations carried out enable us gain deep insights into the dynamics of the spread of COVID-19. The simulation results confirm that fractional calculus is an appropriate tool in modeling the spread of a complex infectious disease such as the novel COVID-19. In the absence of vaccine and treatment, our analysis strongly supports the significance reduction in the transmission rate as a valuable strategy to curb the spread of the virus. Our results suggest that tracing and moving testing up has an important benefit. It reduces the number of infected individuals in the general public and thereby reduces the spread of the pandemic. Once the infected individuals are identified and isolated, the interaction between susceptible and infected individuals diminishes and transmission reduces. Furthermore, aggressive testing is also highly recommended. [ABSTRACT FROM AUTHOR]

The 2019 outbreak of corona virus disease began from Wuhan (China), transforming into a leading pandemic, posing an immense threat to the global population. The WHO coined the term nCOVID-19 for the disease on 11th February, 2020 and the International Committee of Taxonomy of Viruses named it SARS-CoV-2, on account of its similarity with SARS-CoV-1 of 2003. The infection is associated with fever, cough, pneumonia, lung damage, and ARDS along with clinical implications of lung opacities. Brief understanding of the entry target of virus, i.e., ACE2 receptors has enabled numerous treatment options as discussed in this review. The manuscript provides a holistic picture of treatment options in COVID-19, such as non-specific anti-viral drugs, immunosuppressive agents, anti-inflammatory candidates, anti-HCV, nucleotide inhibitors, antibodies and anti-parasitic, RNA-dependent RNA polymerase inhibitors, anti-retroviral, vitamins and hormones, JAK inhibitors, and blood plasma therapy. The text targets to enlist the investigations conducted on all the above categories of drugs, with respect to the COVID-19 pandemic, to accelerate their significance in hindering the disease progression. The data collected primarily targets recently published articles and most recent records of clinical trials, focusing on the last 10-year database. The current review provides a comprehensive view on the critical need of finding a suitable treatment for the currently prevalent COVID-19 disease, and an opportunity for the researchers to investigate the varying possibilities to find and optimized treatment approach to mitigate and ameliorate the chaos created by the pandemic worldwide. [ABSTRACT FROM AUTHOR]

This article tests the hypothesis that all pandemics are inherently translational. We argue that translation and translation theory can be fruitfully used to understand and manage epidemics, as they help us explore concepts of infectivity and immunity in terms of cultural and biological resistance. After examining the linkage between translation and coronavirus disease from three different yet interlinked perspectives—cultural, medical, and biocultural—we make a case for a translational medical humanities framework for tackling the multifactorial crisis brought about by the SARS-CoV-2 infection. This innovative entanglement of perspectives has the merit of carving out a new space for translation research at the intersection of the sciences and the humanities, providing sustainable ways to conceptualize the production of science at times of crisis, and challenging conventional views of translation as a primarily linguistic and cultural phenomenon that traditionally does not engage with science. [ABSTRACT FROM AUTHOR]

Public access automated external defibrillators (AEDs) represent emergency medical devices that may be used by untrained lay-persons in a life-critical event. As such their usability must be confirmed through simulation testing. In 2020 the novel coronavirus caused a global pandemic. In order to reduce the spread of the virus, many restrictions such as social distancing and travel bans were enforced. Usability testing of AEDs is typically conducted in-person, but due to these restrictions, other usability solutions must be investigated. Two studies were conducted, each with 18 participants: (1) an in-person usability study of an AED conducted in an office space, and (2) a synchronous remote usability study of the same AED conducted using video conferencing software. Key metrics associated with AED use, such as time to turn on, time to place pads and time to deliver a shock, were assessed in both studies. There was no difference in time taken to turn the AED on in the in-person study compared to the remote study, but the time to place electrode pads and to deliver a shock were significantly lower in the in-person study than in the remote study. Overall, the results of this study indicate that remote user testing of public access defibrillators may be appropriate in formative usability studies for determining understanding of the user interface. [ABSTRACT FROM AUTHOR]

Low power microwave can effectively deactivate influenza type A virus through the nonthermal structure-resonant energy transfer effect, at a frequency matching the confined-acoustic dipolar mode frequency of the virus. Currently, aerosol is considered the major route for SARS-CoV-2 transmission. For the potential microwave-based sterilization, the microwave-resonant frequency of SARS-CoV-2 must be unraveled. Here we report a microwave absorption spectroscopy study of the SARS-CoV-2 and HCoV-229E viruses through devising a coplanar-waveguide-based sensor. Noticeable microwave absorption can be observed, while we identified the resonant frequencies of the 1st and 2nd dipolar modes of SARS-CoV-2 virus as 4 and 7.5 GHz respectively. We further found that the resonant frequencies are invariant to the virus titer, and we also studied the microwave absorption of HCoV-229E in weak acidity medium to simulate the common pH value in fluid secretion. Our results suggest the possible radiation frequency for the recently proposed microwave sterilization devices to inactivate SARS-CoV-2 virus through a nonthermal mechanism so as to control the disease transmission in the post-pandemic era. [ABSTRACT FROM AUTHOR]

In the COVID-19 pandemic, the coronavirus outbreak hit densely populated urban areas first and hardest; then, quickly spread into the suburbs due to the busy connections in public transport (Tabernese and Mervosh [44]). There is now mounting evidence that societal and environmental factors have largely contributed to the coronavirus disease 2019 pandemic (COVID-19). PEI infrastructure investor (July/August), pp 30-32 https://30kwe1si3or29z2y020bgbet-wpengine.netdna-ssl.com/wp-content/uploads/2018/03/what-in-the-world-is-infrastructure.pdf 18 Han J, He S. Urban flooding events pose risks of virus spread during the novel coronavirus (COVID-19) pandemic. [Extracted from the article]

The global pandemic caused by COVID-19 has resulted in major costs around the world, costs with dimensions in every aspect, from peoples' daily living to the global economy. As the pandemic progresses, the virus evolves, and more vaccines become available, and the 'battle against the virus' continues. As part of the battle, Wastewater-Based Epidemiology (WBE) technologies are being widely deployed in essential roles for SARS-CoV-2 detection and monitoring. While focusing on demonstrating the advantages of passive samplers as a tool in WBE, this review provides a holistic view of the current WBE applications in monitoring SARS-CoV-2 with the integration of the most up-to-date data. A novel scenario example based on a recent Nanjing (China) outbreak in July 2021 is used to illustrate the potential benefits of using passive samplers to monitor COVID-19 and to facilitate effective control of future major outbreaks. The presented contents and how the application of passive samplers indicates that this technology can be beneficial at different levels, varying from building to community to regional. Countries and regions that have the pandemic well under control or have low positive case occurrences have the potential to significantly benefit from deploying passive samplers as a measure to identify and suppress outbreaks. [ABSTRACT FROM AUTHOR]

With the COVID-19 pandemic, documenting whether health care workers (HCWs) are at increased risk of SARS-CoV-2 contamination and identifying risk factors is of major concern. In this multicenter prospective cohort study, HCWs from frontline departments were included in March and April 2020 and followed for 3 months. SARS-CoV-2 serology was performed at month 0 (M0), M1, and M3 and RT-PCR in case of symptoms. The primary outcome was laboratory-confirmed SARS-CoV-2 infection at M3. Risk factors of laboratory-confirmed SARS-CoV-2 infection at M3 were identified by multivariate logistic regression. Among 1062 HCWs (median [interquartile range] age, 33 [28–42] years; 758 [71.4%] women; 321 [30.2%] physicians), the cumulative incidence of SARS-CoV-2 infection at M3 was 14.6% (95% confidence interval [CI] [12.5; 16.9]). Risk factors were the working department specialty, with increased risk for intensive care units (odds ratio 1.80, 95% CI [0.38; 8.58]), emergency departments (3.91 [0.83; 18.43]) and infectious diseases departments (4.22 [0.92; 18.28]); current smoking was associated with reduced risk (0.36 [0.21; 0.63]). Age, sex, professional category, number of years of experience in the job or department, and public transportation use were not significantly associated with laboratory-confirmed SARS-CoV-2 infection at M3. The rate of SARS-CoV-2 infection in frontline HCWs was 14.6% at the end of the first COVID-19 wave in Paris and occurred mainly early. The study argues for an origin of professional in addition to private life contamination and therefore including HCWs in the first-line vaccination target population. It also highlights that smokers were at lower risk. Trial registration The study has been registered on ClinicalTrials.gov: NCT04304690 first registered on 11/03/2020. [ABSTRACT FROM AUTHOR]

Objective: To document and analyse demographic data, clinical presentation, possible interventions for early clinical detection and management of post-COVID-19 rhino-orbito-cerebral mucormycosis (ROCM). Method: 32 patients having history of SARS-CoV-2 infection with features of ROCM were observed in terms of their history, presenting features, clinical, microbiological examination, type of surgical intervention, surgical sites of involvement which were subsequently analyzed. Results: The mean (± S.D.) age of patients was 57 ± 13 years. All patients were diabetic. Mean (± S.D.) time of onset of ROCM symptoms, since onset of COVID-19 symptoms was 18 (± 4) days. 12.5% patients were fully vaccinated. 78.1% patients received steroid therapy; 28.1% received high flow nasal oxygen. 87.5% patients had blurring of vision, 65.62% headache, 59.37% cheek and eyelid swelling, 50% proptosis, 46.87% ophthalmoplegia, 40.62% ptosis, 40.62% loss of sensation over cheek, 25% orbital pain. Examination of specimen with KOH mount revealed Mucor spp. in all patients. 87.5% patients underwent endoscopic sinus surgery with debridement with/without orbital clearance; 56.25% maxillectomy; 25% orbital exenteration. 87.5% patients had paranasal sinus involvement, 43.75% orbit sparing orbital apex, 68.75% orbit with orbital apex. 81.25% patients had involvement of pterygopalatine fossa±infratemporal fossa. 50% patients had disease in Vidian canal and pterygoid wedge. 25% of patients had involvement of palate and 56.25% cheek and eyelid soft tissues. Conclusion: A judicious COVID treatment protocol, high index of suspicion, close monitoring of high-risk patients and early institution of treatment can prevent case severity and reduce mortality. [ABSTRACT FROM AUTHOR]

This study aims to analyze the role of cross-cultural country differences during a global pandemic. Based on country cultural dimensions and country economic indicators, the research proposes specific policies that might prove of value in order to manage and better respond to present and future critical events such as the 2020 SARS-CoV-2 outbreak. The methodology is based on multivariate analysis for the first set of countries and cross-country comparative analysis for the second set of countries. Research results reveal the critical role of the cultural dimensions individualism, power distance, masculinity, long-term orientation and indulgence, along with the country economic context in the magnitude of the consequences of a global pandemic within a country specific context. Based on these results, the study proposes policies adjusted to the countries specific cultural and economic frameworks in order to promote the most effective and efficient management of a critical event such as a global pandemic. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, has led to the rapid development of Coronavirus disease 2019 (COVID-19) pandemic. COVID-19 represents a fatal disease with a great global public health importance. This study aims to develop a three-parameter Weibull mathematical model using continuous functions to represent discrete COVID-19 data. Subsequently, the model was applied to quantitatively analyze the characteristics for the mortality of COVID-19, including the age, sex, the length of symptom time to hospitalization time (SH), hospitalization date to death time (HD) and symptom time to death time time (SD) and others. A three-parameter mathematical model was developed by combining the reported cases in the Data Repository from the Center for Systems Science and Engineering at Johns Hopkins University and applied to estimate and analyze the characteristics for mortality of COVID-19. We found that the scale parameters of males and females were 5.85 and 5.45, respectively. Probability density functions in both males and females were negative skewness. 5% of male patients died under the age of 43.28 (44.37 for females), 50% died under 69.55 (73.25 for females), and 95% died under 86.59 (92.78 for females). The peak age of male death was 67.45 years, while that of female death was 71.10 years. The peak and median values of SH, HD and SD in male death were correspondingly 1.17, 5.18 and 10.30 days, and 4.29, 11.36 and 16.33 days, while those in female death were 1.19, 5.80 and 12.08 days, and 4.60, 12.44 and 17.67 days, respectively. The peak age of probability density in male and female deaths was 69.55 and 73.25 years, while the high point age of their mortality risk was 77.51 and 81.73 years, respectively. The mathematical model can fit and simulate the impact of various factors on IFR. From the simulation results of the model, we can intuitively find the IFR, peak age, average age and other information of each age. In terms of time factors, the mortality rate of the most susceptible population is not the highest, and the distribution of male patients is different from the distribution of females. This means that Self-protection and self-recovery in females against SARS-CoV-2 virus might be better than those of males. Males were more likely to be infected, more likely to be admitted to the ICU and more likely to die of COVID-19. Moreover, the infection fatality ration (IFR) of COVID-19 population was intrinsically linked to the infection age. Public health measures to protect vulnerable sex and age groups might be a simple and effective way to reduce IFR. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated thoroughly via fitting epidemic models to the reported COVID-19 deaths. We downloaded the data for the 12 most-affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number ( R 0 (t) ) and infection attack rate. We develop a simple epidemic model and fitted it to reported COVID-19 deaths in 12 African countries using iterated filtering and allowing a flexible transmission rate. We observe high heterogeneity in the case-fatality rate across the countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were most affected, exhibiting a relatively higher R 0 (t) and infection attack rate. Thus, to effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns). [ABSTRACT FROM AUTHOR]

In pandemic crises such as the COVID-19 pandemic, individuals' behavior has a strong impact on epidemiological processes. Compliance with prevention guidelines, such as social distancing, is critical to avoid further spreading an infectious disease or to slow down its spread. However, some individuals also or instead engage in panic behavior, such as hoarding. We investigate how education prepares individuals to respond adequately by modelling the path from seeking information about COVID-19 to eventual behavior. Based on a sample of N = 1182 adult Americans, gathered at the pandemic's onset (March 2020), we conclude that science knowledge helps individuals convert information into coronavirus knowledge. This knowledge then helps individuals avoid panic behavior. Individuals lacking coronavirus knowledge and science knowledge still comply with prevention guidelines when they have a general trust in medicine. Individuals lacking knowledge still follow prevention guidelines when they trust in medicine. Facilitating science knowledge and trust in science through education and targeted public health messaging are likely to be of fundamental importance for bringing crises such as the COVID-19 pandemic under control. [ABSTRACT FROM AUTHOR]

This essay considers the factors that have contributed to very high COVID-19 mortality in longer-term care facilities (LTCFs). We compare the demographic characteristics of LTCF residents with those of community-dwelling older adults, and then we review the evidence regarding prevalence and infection fatality rates (IFRs), including links to frailty and some comorbidities. Finally, we discuss policy measures that could foster the physical and mental health and well-being of LTCF residents in the present context and in potential future pandemics. [ABSTRACT FROM AUTHOR]

The purpose of this survey is to explore changes in the management of COVID-19 during the first versus the second wave, with particular emphasis on therapies, antibiotic prescriptions, and elderly care. An internet-based questionnaire survey was distributed to European Society of Clinical Microbiology and Infectious Diseases (ESCMID) members. Therapeutic approach to patients with mild-to-moderate (PiO2/FiO2 200–350) and severe (PiO2/FiO2 < 200) COVID-19, antibiotic use, and reasons for excluding patients from the intensive care unit (ICU) were investigated. A total of 463 from 21 countries participated in the study. Most representatives were infectious disease specialists (68.3%). During the second wave of pandemic, physicians abandoned the use of hydroxychloroquine, lopinavir/ritonavir, and azithromycin in favor of dexamethasone, low-molecular weight heparin (LMWH), and remdesivir in mild-to-moderate COVID-19. In critically ill patients, we detected an increased use of high-dose steroids (51%) and a decrease in tocilizumab use. The use of antibiotics at hospital admission decreased but remained high in the second wave. Age was reported to be a main consideration for exclusion of patients from ICU care by 25% of responders; a third reported that elderly were not candidates for ICU admission in their center. The decision to exclude patients from ICU care was based on the individual decision of an intensivist in 59.6% of cases. The approach of physicians to COVID-19 changed over time following evidence accumulation and guidelines. Antibiotic use at hospital admission and decision to exclude patients from ICU care remain critical aspects that should be better investigated and harmonized among clinicians. [ABSTRACT FROM AUTHOR]

Background: The majority of pandemics are known to be a result of either bacteria or viruses out of which viruses seem to be an entity of growing concern due to the sheer number of yet unidentified and potentially threatening viruses, their ability to quickly evolve and transform, their ability to transfer and change from one host organism to another and the difficulty in creating safe vaccines on time. Main body: The present review attempts to bring forth the potential risks, prevention and its impact on the global society in terms of sociological and economic parameters. Taking hindsight from previously as well as ongoing current viral epidemics, this article aims to draw a concrete correlation between these viruses in terms of their origin, spread and attempts to compare how much they can affect the population. The study also assesses the worst-case scenarios and the amount of preparedness, required to fight against such pandemics and compares the required amount of preparedness to the current precautions and measures by different governments all across the world. Short conclusion: Learning from the current pandemic, we can implement certain measures to prevent the adverse effects of pandemics in the future and through severe preparedness can combat the challenges brought about by the pandemic. [ABSTRACT FROM AUTHOR]

Introduction: Female authors are underrepresented in cardiology journals, although prior work suggested improvement in reducing disparities over time. Early in the recent COVID-19 pandemic, female authorship continued to lag that of their male counterparts despite a surge in publications. The cumulative impact of the COVID-19 pandemic on authorship gender disparities remains unclear. We aimed to characterize gender disparities in COVID-19-related cardiology publications across the duration of the ongoing pandemic. Methods: We retrospectively analyzed COVID-19-related research articles published in the top 20 impact factor cardiology journals between March and June 2021. Gender representation data were extracted for any author, first authors, and senior authors. Results: We found that 841 articles were related to COVID-19, with a total of 5586 authors and an average of 42 articles per journal. Less than a third (29.9%) of the total authors from publications were women. Women represented a smaller proportion of first authors (21.3%) and senior authors (16.4%). Conclusions: Female authorship has continued to lag male authorship for the duration of the ongoing COVID-19 pandemic. The pandemic may have impeded progress in reducing gender disparities in academic cardiology publications. The low proportions of first and senior female authors may reflect the impact of the pandemic on women in cardiology in leadership domains. [ABSTRACT FROM AUTHOR]

Copyright of Cultural Studies of Science Education is the property of Springer Nature 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.)

Italian and Japanese public widely use balneotherapy. The population interest in balneotherapy in coronavirus disease-2019 (COVID-19) era should be investigated. Therefore, we aimed to exploit Google Trends analysis, as a measure of peoples' interest in balneotherapy, in two countries, Italy and Japan. In this infodemiology study, Google Trends was queried for the lay terms widely used by the Italian population to refer to the balneotherapy setting (terme + termale) and by the Japanese to refer to the bathing place and balneotherapy facilities (温泉 + スパ). The internet searches in 2020 were compared to overlapping time spans in 2016–2019 and were correlated with new confirmed cases/deaths. This study demonstrated that from February 23 to June 20, 2020, and from October 4 to December 26, 2020, the internet searches of the Italian words corresponding to balneotherapy were statistically significantly decreased; however, the internet searches were not significantly different in June 21 to October 3, 2020, compared to overlapping time spans in 2016–2019 in Italy. The study also showed that from March 15 to September 5, 2020, and from November 29 to December 26, 2020, the internet searches of the Japanese words corresponding to balneotherapy were statistically significantly decreased; however, the internet searches were significantly increased in September 13 to November 7, 2020, and were not significantly different in November 8 to 28, 2020, compared to overlapping time spans in 2016–2019 in Japan. There were significant negative correlations between the relative search volume and number of new cases (rho=−0.634; p<0.001)/deaths (rho=−0.856; p<0.001) in Italy and the number of new deaths (rho=−0.348; p=0.012) in Japan. Population interest in balneotherapy has changed in the COVID-19 era both in Italy and Japan. During the early stage of pandemic (March to June), the interest was lower. After this early stage, the interest showed a recovery in both countries. In Italy, the population interest reached to its prior levels in late June through early October, with a peak in August. In Japan, the recovery exceeded the prior 4-year levels in mid-September through early November. Then, both countries demonstrated a decline in interest: began in early October in Italy and late November in Japan. This information would allow us to understand/address the population response in the pandemic in respect of the balneotherapy and would guide the preparedness of healthcare providers and planners both in this pandemic and future similar situations. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the coronavirus disease 19 (COVID-19) pandemic, which is deeply affecting the whole world. In this new case for the scientific world, scientists are investigating the etiopathogenesis of viral infection-induced damage and have started to focus on the short and long-term immune system effects and alterations after SARS-CoV-2 infection. The case is here reported of a 53-year-old female patient with acute monoarthritis after SARS-CoV-2 infection, who responded adequately to 150 mg/day diclofenac treatment, and the available case reports are comprehensively reviewed. With the focus on arthritis after SARS-CoV2 infection, which emerges as a new pathological condition associated with COVID-19, it was aimed to examine the possible immunological mechanisms of post-COVID-19 arthritis based on the current data on SARS-CoV-2 and the known pathogenetic background of viral arthritis. [ABSTRACT FROM AUTHOR]

So-called digital tracking and tracing systems (DTTSs) have been proposed as a means to prevent the spread of SARS-CoV-2. There are ethical guidelines and evaluations of such systems available. As part of a research project, I will build on and critically evaluate the foundations of such guidelines. The goal is to provide both incremental improvements of the specific requirements for DTTSs and to present and discuss more fundamental challenge, the risk for indirect effects and slippery slopes. The nature of slippery slopes makes ethical guidelines more difficult since it requires a more complex analysis than, for example, using a checklist allows for. [ABSTRACT FROM AUTHOR]

Digital tracing technologies are heralded as an effective way of containing SARS-CoV-2 faster than it is spreading, thereby allowing the possibility of easing draconic measures of population-wide quarantine. But existing technological proposals risk addressing the wrong problem. The proper objective is not solely to maximise the ratio of people freed from quarantine but to also ensure that the composition of the freed group is fair. We identify several factors that pose a risk for fair group composition along with an analysis of general lessons for a philosophy of technology. Policymakers, epidemiologists, and developers can use these risk factors to benchmark proposal technologies, curb the pandemic, and keep public trust. [ABSTRACT FROM AUTHOR]

Design Special report. Study population This paper presented a report about the experience of the oral and maxillofacial surgeons (OMS) of Peking University School and Hospital of Stomatology, during the COVID-19 (SARS-CoV-2) pandemic. Data analysis The experience of that department formed the content of the report. Results In this study, the authors presented an informative description of experience of treating patients under a pandemic condition. The authors offer some methods of trying to protect oro-maxillofacial surgeons, using an algorithm of diagnosis and classifying the risk of contamination and the materials required in order to avoid it. Conclusions In conclusion, the authors suggest the use of the algorithm for patient admission during the COVID-19 outbreak. [ABSTRACT FROM AUTHOR]