ABSTRACT
The epidemiology of novel corona virus disease (COVID-19) is attributed by cough, fever, fatigue, headache, sore throat, gastrointestinal disorders, and pneumonia. The frequency of COVID-19 infection is accelerating at great speed globally, and till date, there is no specific vaccine or drug available for prevention or cure of the disease. Therefore, certain measures are required to check the outbreak of this pandemic immediately. Current chapter concerns with the development of certain probiotics including a single or mixed culture of live microorganisms that could maintain the intestinal or lung microbiota of humans. Besides being beneficial bacteria, probiotics also possess antiviral activity. The stimulation of the immune system through probiotics is one of the approaches that have been emphasized for fighting against the viral infections. The immunomodulatory activities of probiotics include the enhancement of the phagocytic receptors like CR1, CR3, FccRI, and FcaR;induction of APC-derived pro- and anti-inflammatory cytokines such as IL-10, IL-12, IL-17, TNF-α, and IFN-α against foreign antigens;and an increase in the microbicidal function of neutrophils. The most common probiotics include Lactobacillus, Bifidobacterium, Leuconostoc, Pediococcus, and Enterococcus. Lactobacillus and Bifidobacterium are widely used in yogurts and other dairy products. Probiotics exert antiviral activity by production of antiviral in inhibitory metabolites. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
ABSTRACT
Introduction: Covaxin and Covishield vaccines have been rapidly rolled out in India to curb the Coronavirus disease-19 (COVID-19) pandemic. The present study tested the effectiveness of COVID-19 vaccination in adults in North India. Effectiveness was tested by considering disease transmission and post-COVID outcomes in infected individuals. Materials and Methods: This study was conducted in the Department of Physiology at MGM College, Jaipur (Rajasthan, India), after approval from the Ethics Committee. Vaccinated and nonvaccinated groups were compared for disease transmission, hospitalization, and clinical outcomes. Researchers collected data using questionnaires circulated through Google forms. The association between attributes was tested using the Chi-squared test. The significance level was considered at 5%. Results: Vaccination significantly reduced disease transmission of COVID-19 (χ 2 = 4.51;P = 0.034). However, no significant differences were seen in the Reverse transcription polymerase chain reaction positivity, chest computed tomography findings, and hospitalization. Similarly, COVID-related symptoms and their severity did not differ significantly between the two groups. The proportion of vaccinated individuals increases with age (χ 2 = 41.68;P < 0.001). Youths and older adults were vaccinated once and twice, respectively (χ 2 = 41.77;P < 0.001). The severity of adverse effects postimmunization (AEFI) was similar in all age groups (χ 2 = 13.22;P < 0.21). Males and females were equally vaccinated (χ 2 = 1.13;P < 0.288). However, males took two doses compared to females (χ 2 = 6,57;P < 0.01). Adverse effects postimmunization were more severe in females than males (χ 2 = 13.10;P < 0.001). Researchers found no association between the number of vaccine doses and the severity of AEFIs (χ 2 = 16.42;P = 0.06). Conclusion: The present study concludes the beneficial effect of vaccination in reducing disease transmission. However, vaccination showed no effectiveness in mitigating other COVID-related outcomes. The following core competencies are addressed in this article: Medical knowledge, systems-based practice, practice-based learning, and improvement. © 2023 International Journal of Academic Medicine ;Published by Wolters Kluwer - Medknow.
ABSTRACT
Purpose: The current study employs a modified framework of the unified theory of acceptance and use of technology (UTAUT) to predict students' intention to adopt online learning in India. The moderating role of openness to change in influencing the proposed relationships is also assessed. Design/methodology/approach: A structured questionnaire was emailed to 650 students enrolled in various courses in public and private universities in India. In total 424 responses were considered for analysis using structural equation modeling (SEM). Moderation analysis was carried out with multi-group SEM and chi-square difference tests. Findings: The results reveal that there is a significant impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FS) and perceived security (PS) on students' intention to adopt online learning. Further, openness to change moderates the impact of PE, FS and PS on intention of students to opt for online learning. Originality/value: This study is one of the initial efforts to examine the factors affecting students' intention to adopt online learning at the onset of third wave of coronavirus disease 2019 (COVID-19) pandemic in India. Besides the factors of the UTAUT model, this study highlights the importance of PS and openness to change in influencing students' intention to opt for online learning. © 2023, Emerald Publishing Limited.
ABSTRACT
Introduction: Workload in oncology during a pandemic is expected to increase as manpower is shunted to other areas of need in combating the pandemic. This increased workload, coupled with the high care needs of cancer patients, can have negative effects on both healthcare providers and their patients. Method(s): This study aims to quantify the workload of medical oncologists compared to internal medicine physicians and general surgeons during the current COVID-19 pandemic, as well as the previous H1N1 pandemic in 2009. Result(s): Our data showed decrease in inpatient and outpatient workload across all three specialties, but the decrease was least in medical oncology (medical oncology -18.5% inpatient and -3.8% outpatient, internal medicine -5.7% inpatient and -24.4% outpatient, general surgery -17.6% inpatient, and -39.1% outpatient). The decrease in general surgery workload was statistically significant. The proportion of emergency department admissions to medical oncology increased during the COVID-19 pandemic. Furthermore, the study compared the workload during COVID-19 with the prior H1N1 pandemic in 2009 and showed a more drastic decrease in patient numbers across all three specialties during COVID-19. Discussion(s): We conclude that inpatient and outpatient workload in medical oncology remains high despite an ongoing COVID-19 pandemic. The inpatient medical oncology workload is largely contributed by the stable number of emergency department admissions, as patients who require urgent care will present to a healthcare facility, pandemic or not. Healthcare systems should maintain manpower in medical oncology to manage this vulnerable group of patients in light of the prolonged COVID-19 pandemic. Copyright © The Author(s) 2022.
ABSTRACT
The pathogenesis of the SARS-CoV-2 virus responsible for COVID-19 disease is ever unravelling. Researchers are continuously generating evidence regarding the mechanism of the infection and its complications. There is also an attempt to understand the role of various biomolecules in preventing or treating COVID-19 disease and its complications. Trials show that Vitamin D decreases the rate of admission in ICU. Vitamin C is known to exert the positive influence in decreasing the intensity of viral infections and severe sepsis. Vitamin B12 plays a pivotal role in gut microbiome management. Dietary supplementation of micronutrients with defined roles in immune function can streamline the balance of the body's immune reaction, lessening the incidence of infections and ICU hospital stay. The focus of this review is to apply our modern knowledge of vitamin D, B12 and C as micronutrients & facilitator of immune competence. We suggest that vitamins D, B12 and C may serve as attenuators to COVID-19 symptoms. Large randomized trials are required to confirm this hypothesis.
ABSTRACT
Background: ChAdOx1-S (vaccine A) and BBV152 (vaccine B) vaccines are currently at the forefront of India's fight against the pandemic. The present study tests the hypothesis that both vaccines are equally efficacious. Material(s) and Method(s): This cross-sectional study was conducted at MGM Hospital, Jaipur (Rajasthan, India). The study compared vaccine A and B recipients on post-vaccination events and COVID-19 related outcomes. Researchers collected data using questionnaires circulated through Google Forms. The association between attributes was tested using the chi-squared test. The significance level was considered at 5%. Result(s): The vaccines A and B recipients were age and gender-matched [p > 0.05]. The vaccines did not differ significantly in vaccine events and adverse events after immunization (p > 0.05). A comparison of COVID-19 related outcomes between the two vaccines revealed no significant differences (p > 0.05). However, the severity of symptoms was higher in vaccine B recipients than in vaccine A recipients [p = 0.027] . Conclusion(s): The present study concludes that vaccines A and B were similar in efficacy. The most crucial factor revealed by the survey is that the reporting of adverse events was significantly less, and awareness is needed. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
ABSTRACT
Student performance is most often hampered by mental health difficulties. Students' motivation, attention, and social ties can all be impacted by mental illness, all of which are key factors in their academic achievement. Due to the novel coronavirus pandemic, many institutions and colleges throughout the world have resorted to online learning. Despite widespread use of emergency remote learning (ERL) in higher education during the COVID-19 pandemic, little is known about the elements that influence student satisfaction and stress levels in this innovative learning environment in a crisis. Our research intends to provide a timely assessment of the COVID-19 pandemic's impact on college students' mental stress level employing machine learning algorithms to predict the stress faced by students based on their academic routines. Data collected through student surveys relating to a lot of factors such as time spent on studying, social media, health and fitness etc. provide a strong basis to determine students stress levels and via supervised machine learning algorithms predictions are done on the academic stress by analyzing the prime factors affecting the issue at hand. Various ML models such as Naive Bayes, Random Forest, Artificial Neural Networks (ANN) etc. have been employed and a comprehensive comparison is performed with the proposal of the most optimum algorithm for the prediction of stress level. Copyright © 2022, Anka Publishers. All rights reserved.
ABSTRACT
Bioversity International and the International Fund for Agricultural Development (IFAD) have recently published an operational framework to guide practitioners on ways to mainstream neglected and underutilized species (NUS) into projects and investment programs with the aim of supporting nutrition-sensitive agriculture and resilient food production systems. This chapter presents the key elements of this framework and offers reflections on its implementation following Bioversity International’s innovative holistic value-chain approach, which, through interdisciplinary, bottom-up and gender-sensitive interventions, aims at strengthening the resilience of livelihoods as a whole, with special attention given to women, youth, Indigenous Peoples and other marginalized members of society. Actions meant to increase the use of NUS to strengthen the resilience of communities in the face of the recent COVID-19 pandemic are also proposed. © 2022 selection and editorial matter, Stefano Padulosi, E.D. Israel Oliver King, Danny Hunter and M.S. Swaminathan.
ABSTRACT
One of the most remarkable changes in the academic Diaspora is the international creation of virtual platforms, which has given rise to a new edge system of learning. Covid-19 presents a unique and severe problem on every front. The nationwide shutdown by the administration aims to control the diffusion of Covid-19 at education institutions across the country. Many (local, national, and worldwide) institutions have implemented a reliable and beneficial contactless atmosphere for students and faculties to maintain the continuity of learning. As a result, teachers and students are greatly influenced by the new-age virtual teaching method adopted and implemented. The survey respondents were picked by a combination of online surveys and personality tests, and then the questionnaire they were given included both closed- and open-ended items. The numbers of university and secondary school portals have recently seen an upward trend. So, to better investigate the abilities of teachers and learners to identify the efficiency of dominating content delivery methods, a hybrid approach of the exploratory study was employed. Students and faculty, 140 each who have taken web-based learning at 25 Indian institutions, are sampled using a snowball sampling methodology. The results of the t-test demonstrated a considerable divergence in teaching-learning impressions between faculty and students on three manifests ($\mathrm{p} < 0.005$). Learners' responses differed from faculty responses, and statistically significant differences were found, such as scientific material can be taught effectively online, improved technocratic pedagogy is the core part of e-learning, reliance on computers/connectivity. © 2021 IEEE.
ABSTRACT
This research paper is based on a fieldwork project, undertaken by the group of volunteer students in collaboration with Indian Development for Human Care (IDHC society), India. Slums are a global phenomenon that may be witnessed in nearly any city on the planet. Children from low-income families who live in slums are deprived of numerous essential facilities that non-slum children enjoy in general, therefore they require special attention. We as a team started the research by understanding the work and establishing good relationships with the staff and students to comprehend the way of their working in a better way. We were introduced to the youngsters with whom we will be working for their better future. We started by teaching them basic English, mathematics, basic habits, personal hygiene;we decided to plant trees as a good environment is necessary for our well-being, in this research work we spread awareness in our neighborhood regarding planting trees and keeping the surroundings clean. Also, spread awareness regarding Covid-19 to underprivileged children. © The Electrochemical Society
ABSTRACT
Coronavirus, a lung infection disease 2019 (COVID-19), is a sickness that is happening because of a virus, which is now also known as SARS-CoV-2 (Acute Respiratory Syndrome Coronavirus-2 COVID) was initially found in the city of China, named Wuhan. WHO was reported about COVID-19 disease on December 31st, year 2019.On January 30th, 2020, the WHO declared this outbreak a health emergency on a global level. On March 11th, 2020, it was announced as a worldwide pandemic by the World Health Organization. Coronavirus can trigger a tract infection. It affects a human being's respiratory tract-both lower or upper or both. In this research, we have proposed a rapid detection system for noticing COVID 19 disease in its early stages by using images of radiography(chest). Our model differentiates between two types of images, standard (non-COVID) and COVID infected. Since the images used for the training part for COVID infection are limited, we have used the Data Augmentation technique. Data Augmentation is a phenomenon that expands the dimensions of a dataset by producing altered versions of these images. This approach has proved to increase the efficiency of the model. © 2021 IEEE.
ABSTRACT
Aim of this paper is to identify the key issues discussed among the people on Twitter using machine learning and NLP techniques regarding COVID-19. One of the most important way to produce these insights is Automatic Keyword Extraction. It is a method to obtain the most important words from the text by summarizing thus providing an insight into the whole context. Text Summarization is the process to condense the content without the loss of significant data. This paper applies a hybrid model of graph-based and topic modeling approaches to extract keywords from a large dataset of approximately 1 million tweets. © 2021 IEEE.
ABSTRACT
Introduction: Coronaviruses are significant pathogens of both human and animals and are globally distributed. Out of seven CoVs strains, the most lethal coronavirus strains being portrayed is SARS-CoV-2. It can cause bronchial asthma, and severe pneumonia and acute respiratory disease. Due to its contagion in infants, adults, and immunocompromised patients which further results in making this a deadly disease, thus there is an urgent need to develop effective and safe therapeutics against it. Materials and Methods: Meta-analysis of publicly available gene expression datasets belonging to SARS-CoV-2, SARS-CoV, MERS-CoV and HCoV-229E were carried out to identify the potential differentially expressed genes exclusively associated with SARS-CoV-2 and then a network model was developed to decipher significant drug targets, associated pathways and drug candidates which can be repurposed for this infection. Results: The COVID-19 infection mainly targets immune responses and regulatory processes. A novel role of Relaxin signaling pathway was identified in SARS-CoV-2 infection. Anti-inflammatory, anti-tumor, nutraceutical and anthelmintic agents were found to be good prospective candidates for repurposing against COVID-19. Conclusions: This theoretical study resulted in the identification of approved drug targets that may have the potential to be repurposed for COVID 19 treatment. © 2021 The Author(s).
ABSTRACT
Background: In the year 2020, the COVID-19 pandemic created havoc in people's lives across the entire world. The pandemic created fear and uncertainty, and Lockdowns were enforced for containment of the disease, impacting the general population's mental well-being as well. The dearth of studies on the subject, particularly on Children and adolescents, creates a vacuum of information which hinders the strategy formulation for effective handling of such issues. Aim: The research aimed to study the psychological impact of Lockdown on children & adolescents in tier 2 city of India. Methods: The study was conducted through online surveys in the city of Jaipur in Rajasthan state of India using the Snowball sampling technique. The Study group included children between the age of 6 to 16 years and assessment of the mental well-being of the participants were done using Short Mood &Feeling Questionnaire (SMFQ). Result: A total of 301 valid responses were received, from which 38 (12.22%) children scored high on SMFQ wherein female adolescents scored higher than males. A total of 10 out 21 children with a history of medical illness scored high on SMFQ and a total of 2 out of 4 children with a past history of psychiatric illness scored high on SMFQ. The data analysis revealed that most of the children struggled with feelings of restlessness, fatigue, unhappiness, and difficulty in concentration. Conclusion: Lockdown has affected mental well-being of both children and adolescents. The impact was observed equally in both groups wherein those with psychiatric history were affected more than others in the 6-11 years age group (Children) and those with medical history were affected more than others in the 11-16 years age group (Adolescents). Immediate attention is needed for alleviation of mental burnout in children and adolescents considering already inadequate interventions in the matter and the ongoing nature of the pandemic.
ABSTRACT
The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.
ABSTRACT
Introduction: COVID-19 has prevented many patients from accessing health care through traditional face-to-face clinic visits. Consequently, online consultations have gained popularity. Aim: To explore patient perceptions regarding virtual consultations. Methods: A voluntary online survey using a mix of quantitative and qualitative questions was administered to patients across selected cities in India using a social media platform. Responses were used to explore the characteristics of users, perceived advantages and disadvantages of online consultations and patient satisfaction. Results: There were 679 respondents (M 52.4%: F 47.6%) that had consulted doctors online;91.8% were from 8 major metro cities. Interestingly, over 80% had never sought online consultation before the COVID-19 pandemic. 46% consultations were via videocalls, 26% through WhatsApp and 21% via telephone calls. The main advantages of online consultations cited by patients included a lower risk of infection (78.8%), reduced waiting time (56.8%) and travel time (58.3%). The main disadvantages included a lack of physical examination (73.4%), a perception that this was not as satisfying as a face-to face consultation (37.9%) and difficulty in communication (24.5%). 78.6% patients rated their online consultations as either good or very good. However, given the choice, almost two-thirds felt they would still prefer face-face consultations. Conclusion: High levels of satisfaction from this survey suggests that teleconsultation has the potential to become a complementary method to access clinical care even after restrictions from the pandemic cease. The disadvantages of online consultations could be mitigated through evolving technologies such as digital stethoscopes and improvement in communication tools. © 2021, Indian Association of Preventive and Social Medicine. All rights reserved.