Evidence-based anti-viral and immunomodulatory potential of Black cumin (Nigella sativaL.) in COVID-19

Currently, the whole world is facing a life-threatening novel coronavirus 2019 (COVID-19) pandemic. Natural products are well-known for their potential role against viral disease, and some anti-viral agents have been developed to combat these diseases. Herein, the authors investigated the possible effects of this Holy plant Nigella sativaL. (NS), against coronavirus, using evidence-based and mechanistic approaches to conclude the immune-boosting and alleviation of respiratory systemeffects of NS. The pharmacological studies established a prominent role in treating various respiratory, immune systems, cardiovascular, skin, and gastrointestinal disorders. Literature supported the significant anti-viral role and showed an inhibitory role for NS against MHV-A59 CoV (mouse-hepatitis virus–A59) infected Hela, i.e., HeLaCEACAM1a (HeLa-epithelial carcinoembryonic antigen-related cell adhesion molecule 1a) cell. NS is a safe herbal product or dietary supplement and could be an effective and affordable community adjuvant treatment for coronavirus in the current scenario.

A Language-independent Network to Analyze the Impact of COVID-19 on the World via Sentiment Analysis

Towards the end of 2019, Wuhan experienced an outbreak of novel coronavirus, which soon spread worldwide, resulting in a deadly pandemic that infected millions of people around the globe. The public health agencies followed many strategies to counter the fatal virus. However, the virus severely affected the lives of the people. In this paper, we study the sentiments of people from the top five worst affected countries by the virus, namely the USA, Brazil, India, Russia, and South Africa. We propose a deep language-independent Multilevel Attention-based Conv-BiGRU network (MACBiG-Net) , which includes embedding layer, word-level encoded attention, and sentence-level encoded attention mechanisms to extract the positive, negative, and neutral sentiments. The network captures the subtle cues in a document by focusing on the local characteristics of text along with the past and future context information for the sentiment classification. We further develop a COVID-19 Sentiment Dataset by crawling the tweets from Twitter and applying topic modeling to extract the hidden thematic structure of the document. The classification results demonstrate that the proposed model achieves an accuracy of 85%, which is higher than other well-known algorithms for sentiment classification. The findings show that the topics which evoked positive sentiments were related to frontline workers, entertainment, motivation, and spending quality time with family. The negative sentiments were related to socio-economic factors like racial injustice, unemployment rates, fake news, and deaths. Finally, this study provides feedback to the government and health professionals to handle future outbreaks and highlight future research directions for scientists and researchers.

Exploring the Need of Social Change Leadership Concerning Health Communication and Health Disparities During the COVID-19 Pandemic

In March of 2020, the United States activated nationwide pandemic response protocols due to the swift spread of Novel Coronavirus Disease 2019, also known as COVID-19. Amidst the domestic response, urgency surrounded the need to build collective awareness of the signs, symptoms, and preventive measures of the virus. As the virus spread and historically marginalized communities were disproportionately impacted with rates of infection, the need to explore the presence of disparities in health communication, health education, and personal health literacy surfaced. The research contained within this study examines the root cause of the gap in health literacy for communities of color and presents actionable next steps to increase positive healthcare outcomes for all.

Current understanding of an Emerging Coronavirus using in silico approach: Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2)

Novel coronavirus (nCoV) namely “SARS-CoV-2” is being found responsible for current PANDEMIC commenced from Wuhan (China) since December 2019 and has been described with epidemiological linkage to China in about 221 countries and territories until now. In this study we have characterized the genetic lineage of SARS-CoV-2 and report the recombination within the genus and subgenus of coronaviruses. Phylogenetic relationship of thirty nine coronaviruses belonging to its four genera and five subgenera was analyzed by using the Neighbor-joining method using MEGA 6.0. Phylogenetic trees of full length genome, various proteins (spike, envelope, membrane and nucleocapsid) nucleotide sequences were constructed separately. Putative recombination was probed via RDP4. Our analysis describes that the “SARS-CoV-2” although shows great similarity to Bat-SARS-CoVs sequences through whole genome (giving sequence similarity 89%), exhibits conflicting grouping with the Bat-SARS-like coronavirus sequences (MG772933 and MG772934). Furthermore, seven recombination events were observed in SARS-CoV-2 (NC_045512) by RDP4. But not a single recombination event fulfills the high level of certainty. Recombination mostly housed in spike protein genes than rest of the genome indicating breakpoint cluster arises beyond the 95% and 99% breakpoint density intervals. Genetic similarity levels observed among “SARS-CoV-2” and Bat-SARS-CoVs advocated that the latter did not exhibit the specific variant that cause outbreak in humans, proposing a suggestion that “SARS-CoV-2” has originated possibly from bats. These genomic features and their probable association with virus characteristics along with virulence in humans require further consideration.

Online Synchronous Teaching during a Pandemic

As the novel Coronavirus (COVID-19) spread rapidly across the globe, most educational institutions tried to address major challenges of engaging students in a productive way and disseminating knowledge through online learning. Given this consideration, the present study qualitatively explores the observations and experiences of a private university and giant strides taken by the institution in adapting and delivering value to all the stakeholders through educational transformation during the pandemic. The data was collected using observations and in depth interviews. The findings of the study revealed that the university went through certain structural changes and modified teaching pedagogy for virtual delivery like providing support and training to the faculty before shifting completely to online mode and delivering the sessions online in both synchronous and asynchronous mode. The results of the study are likely to help transform and address the major challenges of engaging students in a productive way and disseminating knowledge through online learning during a pandemic.

Review of Coronavirus disease- 2019 (COVID-19) in Iraq

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) or 2019 novel coronavirus (2019-nCoV) is quickly spreading to the rest of the world, from its origin in Wuhan, Hubei Province, China. And becoming a global pandemic that affects the world's most powerful countries. The goal of this review is to assist scientists, researchers, and others in responding to the current Coronavirus disease (covid-19) is a worldwide public health contingency state. This review discusses current evidence based on recently published studies which is related to the origin of the virus, epidemiology, transmission, diagnosis, treatment, and all studies in Iraq for the effect of covid-19 diseases, as well as provide a reference for future researchers. The findings of this review show significant differences across gender, age group, area of residence, environmental agents (temperature, humidity), and people with chronic diseases (hypertension, diabetes mellitus, heart disease, respiratory disorders, and immunocompromised disease). To control the pandemic, information about COVID-19 was disseminated to people, including wearing a face mask and using a social distancing strategy as an effective tool for controlling COVID-19. More education and progress are required to convince the public that the vaccine is both effective and safe.

What are the risk factors of hospital length of stay in the novel coronavirus pneumonia (COVID-19) patients? A survival analysis in southwest China

Background The global epidemic of novel coronavirus pneumonia (COVID-19) has resulted in substantial healthcare resource consumption. Since patients’ hospital length of stay (LoS) is at stake in the process, an investigation of COVID-19 patients’ LoS and its risk factors becomes urgent for a better understanding of regional capabilities to cope with COVID-19 outbreaks. Methods First, we obtained retrospective data of confirmed COVID-19 patients in Sichuan province via National Notifiable Diseases Reporting System (NNDRS) and field surveys, including their demographic, epidemiological, clinical characteristics and LoS. Then we estimated the relationship between LoS and the possibly determinant factors, including demographic characteristics of confirmed patients, individual treatment behavior, local medical resources and hospital grade. The Kaplan-Meier method and the Cox Proportional Hazards Model were applied for single factor and multi-factor survival analysis. Results From January 16, 2020 to March 4, 2020, 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment, including 271 (50%) patients aged ≥ 45, 285 (53%) males, and 450 patients (84%) with mild symptoms. The median LoS was 19 (interquartile range (IQR): 14–23, range: 3–41) days. Univariate analysis showed that age and clinical grade were strongly related to LoS (P<0.01). Adjusted multivariate analysis showed that the longer LoS was associated with those aged ≥ 45 (Hazard ratio (HR): 0.74, 95% confidence interval (CI): 0.60–0.91), admission to provincial hospital (HR: 0.73, 95% CI: 0.54–0.99), and severe illness (HR: 0.66, 95% CI: 0.48–0.90). By contrast, the shorter LoS was linked with residential areas with more than 5.5 healthcare workers per 1,000 population (HR: 1.32, 95% CI: 1.05–1.65). Neither gender factor nor time interval from illness onset to diagnosis showed significant impact on LoS. Conclusions Understanding COVID-19 patients’ hospital LoS and its risk factors is critical for governments’ efficient allocation of resources in respective regions. In areas with older and more vulnerable population and in want of primary medical resources, early reserving and strengthening of the construction of multi-level medical institutions are strongly suggested to cope with COVID-19 outbreaks.

Management of Patients with Left Ventricular Assist Device during the COVID-19 Pandemic

The novel coronavirus disease 2019 (COVID-19) is an infectious disease with multi-organ involvement, including the cardiovascular system. The disease may cause several cardiovascular complications, and may increase morbidity and mortality among patients with background cardiovascular disease. Patients with advanced heart failure are often treated with left ventricular assist device (LVAD), and represent a unique population mandating multi-disciplinary approach. Several aspects of COVID-19 should be taken into account in LVAD implants, including right ventricular involvement, hemodynamic alterations, thromboembolic and haemorrhagic complications, and the psychological effects of social isolation. Patients with VAD and suspected COVID-19 should be transferred to specialized centers for better management of complications. Here, we review the implications of COVID-19 pandemic on LVAD patients with our recommendations for appropriate management.

The contribution of reduced COVID-19 test time in controlling the spread of the disease: A simulation-based approach

The novel coronavirus COVID-19 has known a large spread over the globe threatening human health. Recommendations from WHO and specialists insist on testing on a mass scale. However, health systems do not have enough resources. The current process requires the isolation of testees in the hospitals’ isolation rooms for several hours until the test results are revealed, limiting hospitals’ capacities to test large numbers of cases. The aim of this paper was to estimate the impact of reducing the COVID-19 test time on controlling the pandemic spread, through increasing hospitals’ capacities to test on a mass scale. First, a discrete-event simulation was used to model and simulate the COVID-19 testing process in Morocco. Second, a mathematical model was developed to demonstrate the effect of accurate identification of infected cases on controlling the disease’s spread. Simulation results showed that hospitals’ testing capacities could be increased six times if the test duration fell from 10 hours to 10 minutes. The reduction of test time would increase testing capacities, which help to identify all the infected cases. In contrast, the simulation results indicated that if the infected population is not accurately identified and no precautionary measures are taken, the virus will continue to spread until it reaches the total population. Reducing test time is a vital component of the response to the COVID-19 pandemic. It is essential for the effective implementation of policies to contain the virus.

Social and Cognitive Psychology Theories in Understanding COVID-19 as the Pandemic of Blame

When faced with adverse circumstances, there may be a tendency for individuals, agencies, and governments to search for a target to assign blame. Our focus will be on the novel coronavirus (COVID-19) outbreak, where racial groups, political parties, countries, and minorities have been blamed for spreading, producing or creating the virus. Blame—here defined as attributing causality, responsibility, intent, or foresight to someone/something for a fault or wrong—has already begun to damage modern society and medical practice in the context of the COVID-19 outbreak. Evidence from past and current pandemics suggest that this tendency to seek blame affects international relations, promotes unwarranted devaluation of health professionals, and prompts a spike of racism and discrimination. By drawing on social and cognitive psychology theories, we provide a framework that helps to understand (1) the effect of blame in pandemics, (2) when people blame, whom they blame, and (3) how blame detrimentally affects the COVID-19 response. Ultimately, we provide a path to inform health messaging to reduce blaming tendencies, based on social psychological principles for health communication.