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Context/Background: The future of Corona virus disease is still uncertain due to viral mutations. Immunization against COVID-19 has not yet been introduced for children aged 6-11 years. Parents are instrumental for the success of any immunization programme, being the chief decision makers for their wards. The study aims to assess the perceptions of parents regarding COVID 19 vaccination among children aged 6-11 years in an urban slum of Murshidabad and identify the factors influencing such perceptions among them. Methodology: A cross sectional study was conducted among 106 parents in a slum area of Murshidabad, West Bengal. Participants were interviewed using a validated WHO Vaccine Hesitancy Scale (VHS). Bivariate and multivariable analysis were done using Chi square test and binary logistic regression respectively. Results: Majority of the study subjects instead of parents were unlikely to vaccinate their children against COVID-19. The major concern centered around the safety (73.5%) of the vaccine. Higher level of education (p=0.003), previous history of COVID-19 infection in the family (p=0.004) and having a children aged between 6-8 years (p=0.006), influenced such perceptions, with the latter being the single most important predictor (AOR 4.126, P=0.007). Conclusions: The likelihood of parents to vaccinate their child was found to be low. This underscores the importance of an effective communication strategy when such programme will be rolled out. © 2023 National Journal of Community Medicine.
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The COVID-19 pandemic has affected healthcare in several ways. Some patients were unable to make it to appointments due to curfews, transportation restrictions, and stay-at-home directives, while less urgent procedures were postponed or cancelled. Others steered clear of hospitals out of fear of contracting an infection. With the use of a conversational artificial intelligence-based program, the Talking Health Care Bot (THCB) could be useful during the pandemic by allowing patients to receive supportive care without physically visiting a hospital. Therefore, the THCB will drastically and quickly change in-person care to patient consultation through the internet. To give patients free primary healthcare and to narrow the supply-demand gap for human healthcare professionals, this work created a conversational bot based on artificial intelligence and machine learning. The study proposes a revolutionary computer program that serves as a patient's personal virtual doctor. The program was carefully created and thoroughly trained to communicate with patients as if they were real people. Based on a serverless architecture, this application predicts the disease based on the symptoms of the patients. A Talking Healthcare chatbot confronts several challenges, but the user's accent is by far the most challenging. This study has then evaluated the proposed model by using one hundred different voices and symptoms, achieving an accuracy rate of 77%. © 2023 IEEE.
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The aim of this chapter is to show the complexity of identity development in a highly diverse world. The chapter begins with a discussion of difference and diversity, followed by an exploration of the concept of identity. It shows the role of education in the development of identity and some of the problems that may arise when identity development is neglected or obstructed. It briefly touches on educational programs that could support positive identity development and ends with the implications of identity in teacher education. © 2023 Elsevier Ltd. All rights reserved.
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Background: The rapid spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) globally has created unprecedented health care and economic crisis. The ever-in-creasing death toll highlights an urgent need for the development of specific antiviral to combat Novel Coronavirus Disease 2019 (COVID-19). Objective(s): In the present study, we aimed to identify potential SARS-CoV-2 papain-like protease inhibitors from regularly used spices. Method(s): A structure-based virtual screening (VS) of our in-house databank of 1152 compounds was employed to identify small molecule inhibitors of SARS-CoV-2 papain-like protease (PLpro), which are important protease for virus replication. The databank was built of the compounds from ten spices and two medicinal plants. Result(s): The top three potential hits that resulted from VS were myricetin (1) available in Alium cepa and Mentha piperita;alpha-hydroxyhydrocaffeic acid (2) available in M. Piperita;and luteolin (3) available in M. Piperita, Curcuma longa, A. cepa, and Trigonella foenum-graecum, which showed fair binding affinity to PLpro of SARS-CoV-2 compared to known SARS-CoV PLpro in-hibitors. The predicted Absorption, Distribution, Metabolism, and Excretion (ADME) properties of the selected hits showed that all are drug-like. The compounds bind to biologically critical regions of the target protein, indicating their potential to inhibit the functionality of this component. Conclusion(s): There are only a few reports available in the literature on the in-silico identification of PLpro inhibitors and most of them used homology modeling of protein. Here, we used the recently uploaded X-ray crystal structure of PLpro (PDB ID: 6WX4) with a well-defined active site. Our computational approach has resulted in the identification of effective inhibitors of SARS-CoV-2PL-pro. The reported edible spices may be useful against COVID-19 as a home remedy after an in--vitro study.Copyright © 2021 Bentham Science Publishers.
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Novel Coronavirus (COVID-19) is an infectious respiratory illness caused by the SARS-CoV-2 virus, which is a novel coronavirus first reported in the Wuhan district of China in December 2019. Its outbreak has caused the second biggest ever pandemic known to humankind with recorded death tallies close to 50 lakhs till date. The primary targets of infection and pathogenicity of the virus are the lung pneumocytes whose gradual destruction leads to acute respiratory distress. Increasing number of evidences have indicated that severe consequences from COVID-19 occur mostly in people predisposed with obesity, hypertension, diabetes, or other related comorbidities. This has initiated a collective quest among researchers and scientists to decipher the crosstalk between glycemic markers, viral proteins, and immune mediators/(modulators). Patients with hyperglycemia have elevated levels of proinflammatory cytokines that immediately suggest their susceptibility to the viral infection. However, concentration of ACE-2, the chief receptor for SARS-COV2 entry into host cells, has been found to be significantly repressed in individuals with impaired insulin sensitivity. Thus, the comorbidity puzzle has continued to intrigue scientists, and subsequently, effective management and therapy of diabetic patients with COVID-19 symptoms and vice versa has thrown a big challenge to the medical science. This chapter is a comprehensive report of the studies carried out so far to understand the disease susceptibility of diabetic patients to COVID-19, corresponding immune dysbiosis and more efficient management strategy for better prognosis of COVID-19-infected diabetic individuals. © 2023 Elsevier Inc. All rights reserved.
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This study examines the presence of contagion effect along with interdependency between the stock markets of Asian emerging economies like China, India, South Korea, Indonesia, Hong Kong, and Thailand that are caused due to COVID-19 pandemic. The study employs an adjusted correlation coefficient along with the DCC-MGARCH model to capture the contagion effect or interdependency between Shanghai Composite and other select stock markets. Mild enhancement of short-run volatility (DCCα1) is found to be significant under the DCC framework during COVID-19 period only, although long-run volatility is insignificant in both periods. Contagion effect can be slightly traced in BSE Sensex, KOSPI, and SET 100 while market co-movement remains same for Hang Seng and JKSE Composite and thus they are interdependent with Shanghai Composite. Interestingly, adjusted correlation coefficients between Shanghai Composite and other stock markets increased substantially during COVID-19 period indicating the presence of high contagion effect amongst the markets. Copyright © 2023 Inderscience Enterprises Ltd.
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As the outbreak of COVID-19 resulted in a wave of trade restrictions, it is worthwhile to study its impact on India and its trading partners. Accordingly, the study aims to examine the effect of the announcement of COVID-19 pandemic on the stock market returns of selected economies that are India's largest trading partners. By employing event study methodology the study finds that the stock markets displayed an immediate negative response to the announcement. Soon after, when the markets began to recover it was observed that within a month, the majority of the markets adjusted to the announcement and began to converge with normal returns. The results also revealed that different markets recovered at varying speeds contingent on the number of COVID cases. The study contributes to the existing literature on the response of stock markets to the outbreak of pandemic and disastrous events, besides the literature on market efficiency. Copyright © 2022 Inderscience Enterprises Ltd.
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Purpose: The closure of educational institutions in the COVID-19 pandemic has changed the global teaching and learning landscape. Face-to-face classroom activity has been shifted to online classroom activity. This study aims to investigate the effect of social media-based education on students' academic performance during the pandemic. Design/methodology/approach: This study analyzes the perceptions of 302 university-going students of Bangladesh using structural equation modeling. Findings: Results show that Facebook features, perceived usefulness and personal tutorial have a positive and significant relationship with the use of social media (USM). Furthermore, the USM has a positive and significant relationship with the academic performance of the university-going students of Bangladesh during the pandemic. Research limitations/implications: This research has considered the social media usage of university students during the pandemic for academic purposes. This study has not considered income group, technical literacy and device availability of the students. Therefore, the findings may not be generalized to all classes of society. Practical implications: This study validates that the USM can ensure good academic performance by engaging students through collaboration and attention. Originality/value: Diffusion of knowledge and interactive face-to-face learning procedures have faced a massive loss because of this COVID-19 pandemic. Easiness in the mode of teaching technique can be a precondition for its acceptance among the students. As the impact of social media on academic performance in this pandemic context has remained unexplained, this study is designed to focus on this emerging issue. © 2022, Emerald Publishing Limited.
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In the 5 “Dialectica” of “Confessions of a ‘Pandemicized’ Homo-Dialectica” Ranjan Ghosh focuses on the paradoxical changes that Covid-19 has made in what we assumed was our reality, our everyday world. “Social distancing, ” in the sense of being aloof, is now the “judge of your social amenability, ” and home, as distinguished from workplace, reemerges as “working from home.” “Contact” is not always positive. “Where, ” he asks, “is the community outside community, relation without relation, today?” Even hands, “from being the most neglected and ill-treated organ, [have] become the most hygienically active and fearsomely loved part of the body.” This altered, sometimes ironic, sometimes contradictory, often cruel “reality” is international, and thus we are brought together by a common invisible enemy. We are linked by a common suffering that is psychological since “it stems from being denied the essential sociality of human behavior and [the] physical if sociality is not practiced under restrictions and limits.” With an eye on the collection’s title, Ghost concludes that in “playing with realities we have realized, finally, what it means to go and stay ‘underground’.” © 2022 selection and editorial matter, Sidney Homan;individual chapters, the contributors.
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D-Glucose, in its normal form, is known to most of us. Interestingly, just by replacing an -OH group with a hydrogen, we get 2-deoxy-D-glucose (2-DG) which has excellent medicinal properties. An interesting observation related to glycolysis led to the use of 2-DG as an anticancer drug. Recently, there has been sufficient evidence to support the efficacy of 2-DG as an anti-Covid medication. © 2022, Indian Academy of Sciences.
Subject(s)
COVID-19 , Wine , Adult , Humans , COVID-19 Vaccines/adverse effects , COVID-19/prevention & control , Vaccination/adverse effectsABSTRACT
Background: The current COVID-19 pandemic is one of the greatest public health challenges. The spread of COVID-19 infection continues unabated despite vaccination. Adherence to COVID-19 appropriate behavior is critical to prevent COVID-19 infection. Aim and Objectives: To find out the pattern of COVID-19 appropriate behavior among vaccinated medical students and to estimate the incidence of COVID-19 infection after vaccination. Materials and Methods: A cross-sectional observational study using a questionnaire was carried out for a period of 3 months. The questionnaire was prepared based on the guidelines of Ministry of Health and Family Welfare Government of India. The data were collected using a pretested Google Form (online digital questionnaire) by means of a web-based survey. Results: About 96.5% of the participants wear face cover or mask while meeting someone or during visit to public places and 91.6% maintain respiratory hygiene, whereas 11.6% spit in the open, 16.1% travel unnecessarily, and 36.8% do not discourage crowd. There is significant (P < 0.05) increase in COVID-19 infection after vaccination. Conclusion: This study suggests that more emphasis should be given on sensitizing the medical students about the standard COVID appropriate behaviors because strict adherence to COVID-19 appropriate behavior is the key to the long-term management of this pandemic.
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In today's world of medical science, remote patient monitoring devices are becoming more important and a future need particularly in the present COVID-19 situation as individuals are preferred to be kept isolated. Patients would be benefited from a suitable monitoring system that measures their important medical parameters such as pulse rate, oxygen saturation or SpO2, body temperature, blood pressure, and Galvanized Skin Response (GSR). This system can increase the medical staff efficiency by drastically decreasing their duties in hospitals and the need to attend to them individually. Patients in their home isolation may utilize the device as well, and their vital indicators may be checked by doctors remotely. In this work, we are prototyping a powerefficient, wearable medical kit and a resource-aware fog network set up to handle the Internet of Things (IoT) data traffic. The idea behind the design is to process the critical medical sensors' data in the fog nodes which are deployed at the edge of the network. The data thus received, is used for a machine learning-based solution for personal health anomalies and COVID-19 infection risk analysis. © 2022 IEEE.