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1.
Frontiers of COVID-19: Scientific and Clinical Aspects of the Novel Coronavirus 2019 ; : 471-486, 2022.
Article in English | Scopus | ID: covidwho-20241346

ABSTRACT

In the last 20 years, the world has been threatened with coronavirus (CoV) pandemic threats from severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002, Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 and finally COVID-19 due to SARS-CoV-2 in 2019. These viruses posed serious global pandemic threats, with estimated case fatality rates of 15% for SARS-CoV, 34% for MERS-CoV, and 1-3% for SARS-CoV-2. With the current pandemic still far from over there is an urgent need to find new drug treatments for COVID-19. We can assume that this will not be the last coronavirus to threaten humanity, so we need better tools to identify drugs active against past but also future coronavirus threats. In this Chapter we describe in silico computer modeling and screening approaches that can rapidly identify drugs from existing drug libraries that could be repurposed to treat COVID-19 infections. We also describe how this computational screening pipeline can be expanded in the future to identify drugs with broad spectrum activity against a wide diversity of coronaviruses. A significant concern is that the protection against CoVs provided by single drugs protection may be short-lived because viruses rapidly mutate to develop drug resistance. We know from other viruses such as HIV that drugs hitting multiple targets within the virus provide better protection against the development of resistance. This Chapter describes the current state of development of in silico CoV drug repurposing, the challenges and pitfalls of these approaches, and our predictions of how these methods could be used to develop drugs for future pandemics before they occur. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

2.
Frontiers in Nanotechnology ; 4, 2022.
Article in English | Web of Science | ID: covidwho-20230882

ABSTRACT

Despite ongoing public health measures and increasing vaccination rates, deaths and disease severity caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its new emergent variants continue to threaten the health of people around the world. Therefore, there is an urgent need to develop novel strategies for research, diagnosis, treatment, and government policies to combat the variant strains of SARS-CoV-2. Since the state-of-the-art COVID-19 pandemic, the role of selenium in dealing with COVID-19 disease has been widely discussed due to its importance as an essential micronutrient. This review aims at providing all antiviral activities of nanoselenium (Nano-Se) ever explored using different methods in the literature. We systematically summarize the studied antiviral activities of Nano-Se required to project it as an efficient antiviral system as a function of shape, size, and synthesis method. The outcomes of this article not only introduce Nano-Se to the scientific community but also motivate scholars to adopt Nano-Se to tackle any serious virus such as mutated SARS-CoV-2 to achieve an effective antiviral activity in a desired manner.

3.
Indian Journal of Community Health ; 34(4):516-520, 2022.
Article in English | Web of Science | ID: covidwho-2326343

ABSTRACT

Background: Vaccines are considered as the one of the main pillars in halting and ending the presently on-going coronavirus disease (COVID-19 disease) pandemic which has spread globally since it was first detected in Wuhan, China in December 2019. In the absence of specific therapy, infection prevention practices and mass vaccination remains the mainstay in controlling the disease. Objectives: Objective of the study was to assess COVID-19 vaccination status, socio-demographic and clinical profile among healthcare workers diagnosed with COVID-19. Methodology: A cross-sectional survey from 1st March 2021 to 30th June 2021 among healthcare workers who were diagnosed with COVID-19 in a tertiary care institute of Uttarakhand, India was conducted, and universal sampling was used. Institutional Ethics Committee approved this study. Results: Total 662 healthcare workers were diagnosed with COVID-19. 429 (64.8%) of these COVID-19 diagnosed healthcare workers had received either single (129,30%) or both dose (300,70%) of COVID-19 vaccine while remaining 233 (35.2%) belonged to non-vaccinated group. History of exposure to COVID-19 positive patients was higher in vaccinated (66.4%) than in non-vaccinated group (55%) (p = 0.004). Hospitalisation was found to be higher among non-vaccinated (5.6%) than vaccinated group (2.3%) (p = 0.029). Conclusions: This study concludes that being vaccinated against COVID-19 disease provides protection against severe infection and reduces the need for hospitalization.

4.
Indian Journal of Community Health ; 35(1):109-116, 2023.
Article in English | Web of Science | ID: covidwho-2325652

ABSTRACT

Background: Lockdown measures are being implemented in several parts of the world to control the spread of novel coronavirus. This unprecedented crisis has significantly affected the lives of people in different ways.Aim: To understand the experiences and vulnerability to mental health problems during lockdown among the Indian population during COVID-19 pandemic.Materials and Methods: A cross-sectional study was conducted using an online survey form circulated through various social media platforms from April 12 to May 3, 2020 containing self-reported questionnaires to collect lockdown related experiences and scales to assess anxiety (GAD-7) and depression (PHQ-9). A convenience sampling method was used.Results: 442 valid responses were received from different states of India. Statistical analysis revealed that one-third of the respondents suffered from some form of anxiety and depression during a lockdown. Less than 10% of them had severe levels of symptoms. The majority were males aged 18-45 years and private sector employees. Delivering essential services was involved with significant anxiety and depression. Availability of food and daily essentials was the most common problem. Difficulty in availing medicines and financial crisis were significant predictors of anxiety and depression. Worsening of interpersonal relationships was associated with higher levels of anxiety and depression.Conclusions: The study concluded that experiences during the lockdown and associated psychological outcomes are important factors to consider and appropriate preventive measures to be taken in case of any future lockdowns.

5.
Indian Journal of Community Health ; 34(4):535-541, 2022.
Article in English | Web of Science | ID: covidwho-2324752

ABSTRACT

Background: India saw one of the stringent lockdowns during the COVID-19 pandemic. In the wake of this period, the normal functioning of medical services was affected. People were reluctant to seek medical attention and notification of Tuberculosis dipped. The aim of the study was to estimate the proportion of non-adherence to anti-tubercular treatment and to identify the factors affecting the non-adherence to treatment. Methods: A retrospective community-based study was conducted among 284 tuberculosis patients. They were interviewed using a pre-designed questionnaire consisting of WHO dimensions of non-adherence and lockdown related questions. Results: The proportion of non-adherence to treatment was found to be 5.3%. Factors like chronic diseases, depression, without knowledge on how the disease is transmitted and that medication can be discontinued once the symptoms subsided, alcohol consumption, and trouble accessing medicine were found to be the determining factors in non-adherence to the treatment. Conclusions: Non-adherence to anti-tuberculosis treatment in our study was low but the various dimensions of adherence along with lockdown related factors had significant impact on it. To further minimize non-adherence during emergency like the lockdown due to COVID-19 pandemic, corrective measures must be explored and implemented.

6.
Georgian Med News ; (336): 100-103, 2023 Mar.
Article in English | MEDLINE | ID: covidwho-2319362

ABSTRACT

The goal of the current study is to comprehend the factors that influence a decision to use telemedicine for healthcare. India saw a massive surge in the use of telemedicine services in the year 2020-21, with teleconsultations increasing by almost 300%. Lockdowns and Covid-19 limitations sped up the introduction of telemedicine services. The advantages of telemedicine healthcare services, however, have not yet reached the vast majority of the population. A pilot survey is done, and a study framework is suggested, to better understand the factors that influence people's decisions to use telemedicine healthcare services. The following variables are taken into account for the study: personal norms, telemedicine use expectation, knowledge, telemedicine usage, initial satisfaction, and covid phobia -19 (CP-19). The suggested framework is then put to the test using SEM (Structural equation modelling), and a good model fit was found. Policymakers and marketers can use the findings to increase the acceptance of telemedicine healthcare services among the general public in order to promote convenience, accessibility, and healthy living.


Subject(s)
COVID-19 , Telemedicine , Humans , COVID-19/epidemiology , SARS-CoV-2 , Intention , Pandemics , Communicable Disease Control
7.
International Journal of E-Adoption ; 14(3):15-15, 2022.
Article in English | Web of Science | ID: covidwho-2311000
8.
6th Australasia and South-East Asia Structural Engineering and Construction Conference, ASEA-SEC-06 2022 ; 9, 2022.
Article in English | Scopus | ID: covidwho-2303860

ABSTRACT

According to World Energy Outlook 2020, investment of near about USD 1.2 Trillion is required every year to meet global energy demand for the period of 2020-30. Out of this, substantial portion of investment is expected in the hydrocarbon industry. Like many other industries, hydrocarbon industry is hit hard by Covid-19 pandemic with decrease in demand though recovery in demand picked up gradually from the latter half of year 2021. Timely execution of Large Hydrocarbon (LHC) projects within budgeted estimates is necessary to keep the faith of investors in this sector and to attract further investment. The LHC projects are more complex in nature due to various stakeholders' involvement, which may typically involve process technology licensors, owners, project management consultants, contractors, government agencies etc. The purpose of this study is to find out the Critical Success Factors (CSFs) for LHC projects. The study commenced with comprehensive literature review for identification of reported CSFs for various industries. Thereafter, data collected from expert interviews and questionnaire survey are analyzed to find out CSFs for LHC projects. The study provides a list of CSFs which may be referred as guiding tool by industry practitioners and may help in reducing the schedule and cost overruns. © 2022 ISEC Press.

9.
Journal of Molecular Liquids ; 381, 2023.
Article in English | Scopus | ID: covidwho-2302026

ABSTRACT

Researchers are exploring the eutectic mixture because of their obvious great potential in various disciplines. Herein, authors have presented the DFT calculations, molecular docking and QSAR results for designed eutectic mixtures (EMs) using thiourea and resorcinol on taking different equivalent ratio. Authors have used Jakob et al. method to determine the melting temperature of the systems or EMs theoretically. Thermodynamic parameteres such as the free energy, enthalpy, and other energy of the EMs at room temperature are determined through DFT calculations using Gaussian. Authors have also calculated the physiochemical descriptors of various eutectic mixture based on DFT calculations. Further, molecular docking of the designed EMs is carried out to investigate their biological potential for inhibition of the Mpro of SARS-CoV-2. © 2023 Elsevier B.V.

10.
4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022 ; : 265-270, 2022.
Article in English | Scopus | ID: covidwho-2299439

ABSTRACT

Machine Learning, a part of artificial intelligence which is applied in numerous health-related sector which includes the development of innovative medical procedures, the treatment of chronic diseases and the management of medical data. If a patient can recognize the disease at an early stage from the ease of home, they can start their medication sooner and consult a doctor accordingly for their treatment. This paper attempts to detect various diseases in the healthcare field such as Covid-19 and Pneumonia using Image processing technique with the help of Convolutional Neural Network, and other diseases such as Heart Disease and Diabetes using Random Forest, XGBoost, Support Vector Machine and K-Nearest Neighbour Classifiers. © 2022 IEEE.

11.
Letters in Applied NanoBioScience ; 12(4), 2023.
Article in English | Scopus | ID: covidwho-2291428

ABSTRACT

One of the biggest healthcare threats of this century is COVID – 19, undoubtedly. It has caused millions of deaths and raised alerts in the healthcare domain. This study focuses on the importance of 10 native Indian plant species and the phytochemicals obtained from them as a potential inhibitor to the Main protease enzyme of SARS CoV-2. About 26 phytochemicals were shortlisted for the same from the selected plants. Molecular docking was used to analyze the binding affinity of the phytochemicals in the active pocket of the Main protease enzyme to assess their effectiveness. The docking scores resulted in the selection of four compounds being more favorable than the native inhibitor N3, namely Quercetin, Withaferin A, Sominone, and Nimbin, with their binding energies being-8.42,-9.21,-9.95,-8.88 kcal/mol respectively. Furthermore, these four were further analyzed for their bioavailability scores. The studies showed that Sominone, Withaferin A are more potent inhibitors to Mpro of the SARS CoV-2 in all four. Thus further in Vitro studies can be done accordingly for the same. © 2022 by the authors.

12.
Review of Diabetic Studies ; 18(4):187-196, 2022.
Article in English | EMBASE | ID: covidwho-2248561

ABSTRACT

In the era of post-covid-19, new trends have emerged in healthcare services and healthcare access. Diabetic patients are more concerned about their health care services as social awareness is increased. This study aims to investigate the role of diabetic emotional burden and healthcare services as a moderator in the relationship between interpersonal distress, physician & nurse distress, and access to healthcare. The population of this study was the patients with diabetes in different public and private hospitals from Kerala state of India. The study concludes diabetic emotional burden and health care services positively moderate the relationship between interpersonal distress and access to healthcare. This research is a contribution to knowledge as no study earlier was conducted to discuss this gap in the literature. This study has practical and theoretical implications concerned to improve the access to the healthcare system for diabetic patients in Kerala and the rest of the world.Copyright © 2022, Lab and Life Press. All rights reserved.

13.
1st International Conference on Advanced Communication and Intelligent Systems, ICACIS 2022 ; 1749 CCIS:563-575, 2023.
Article in English | Scopus | ID: covidwho-2272548

ABSTRACT

The COVID-19 Pandemic is considered as the worst situation for human beings;it affected people's lives worldwide. Due to this pandemic, the respective government authority announced the lockdown to break the coronavirus chain. The lockdown impacted people's mental health, leading to many psychological issues as well as hampered students' academics. In this chapter we have studied the impacts on students' academics due to lockdown effect. The data has been collected via a google form questionnaire circulated to various educational institutes. Further, we have developed a novel machine learning classifier model called Naïve Bayes-Support Vector Machine for analyzing the data, which utilizes the properties of both classifiers by using a deep learning framework. We have used natural language processing (TextBlob, Stanza and Vader) libraries to label the dataset and applied in the proposed NBSVM method and other machine learning models and classified the sentiments into two categories (Positive vs Negative). We also applied the natural language processing libraries used a topic-modelling technique called Latent Dirichlet Allocation to know the essential topics words of both classes from students' feedback data. The study revealed 83% and 86% accuracy for unigram and bigram, respectively, whereas the precision was 79% and recall 81%. According to NLP libraries' result, approximately 71% of the feedback's sentiment is negative, and only 16% of feedbacks are positive. The proposed model shown that (Naïve Bayes-Support Vector Machine) outperforms the other variants of the Naïve Bayes and support vector machine. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

14.
Tropical Journal of Natural Product Research ; 7(1):2093-2103, 2023.
Article in English | EMBASE | ID: covidwho-2272323

ABSTRACT

The emergence of new pathogenic viruses and the constant outbreak of viral diseases have created an upsurge in novel antiviral agents. Marine natural products are the most unexplored reservoir of novel, biologically active, chemically diverse compounds. A systematic literature review was conducted using PRISMA guidelines, accessing four major databases;PubMed, Science Direct, Scopus, and Google Scholar. Numerous studies supported the robust antiviral activity of marine resources against drug-resistant viruses such as SARS, Ebola, Influenza, and HIV. However, adequate research on marine resources for developing anti-covid therapy is lacking. The aim of the review was to explore the marine resources and their compounds that could lead to developing an effective antiviral drug. We also highlighted the current status of novel compounds against different species of corona family and discussed the future prospects of marine resources against COVID-19 management.Copyright © 2023 the authors.

15.
Phytochemical Genomics: Plant Metabolomics and Medicinal Plant Genomics ; : 85-108, 2023.
Article in English | Scopus | ID: covidwho-2265829

ABSTRACT

Over the past centuries, the "chemodiversity” of the kingdom plantae has gained utmost importance in securing mankind's future and overall well-being of people across the globe. In this context, phytochemicals with distinct stereochemical profiles have been particularly intriguing because of their indispensable roles in various clinical and industrial applications. The phytochemicals are broadly classified into primary and secondary/specialized metabolites. While the proteins, amino acids, chlorophyll, and purines/pyrimidine of nucleic acids are considered as primary metabolites, the remaining phytochemicals, namely, alkaloids, flavonoids, terpenes, steroids, curcumins, and phenolics, are regarded as specialized plant metabolites. In recent times, these high-valued phytochemicals are being extracted from the wasted fruits and vegetables, aiding in the sustainable crop management and cultural economy practices. Historically, these bioactive phytoconstituents have been widely used as a therapeutic agent in different ethnopharmacological cultures. With the advent of novel research technologies, these metabolites are now being screened extensively against both acute and chronic disorders like SARS-CoV-2, cancers, human immunodeficiency virus (HIV), coronary heart disease, multidrug-resistant microbial infections, diabetic conditions, and neural complications as well. Phytochemicals exhibit this wide range of biological activities via their cytotoxic, free radical scavenging, nutraceutical, and apoptotic properties by interfering with the cellular metabolic and signaling pathways. Besides, phytochemicals are widely recognized as flavoring agents and cosmeceuticals due to their antioxidant, stabilizing, emulsifying, chelating, and aromatic properties. The present chapter highlights the multifaceted role of phytochemicals in therapeutic, food/flavoring, and cosmetic industries. It further discusses the current research trends in phytochemical science, including their relevance in circular economy and future approaches for human benefit. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

16.
Indian Journal of Psychiatry ; 65(Supplement 1):S114, 2023.
Article in English | EMBASE | ID: covidwho-2261684

ABSTRACT

Background-The COVID-19 pandemic, has been continuing for more than 2 years and more than 285 million cases of infection and 5.4 million deaths have been reported worldwide . In post COVID-19 conditions, general fatigue and post-exertional malaise are most common somatic sequelae It has been reported that some patients with COVID develop chronic fatigue syndrome . Hence, the present study has been conducted to investigate the presence of post covid somatic symptoms , their frequency, severity and prevalance of chronic fatigue syndrome in post-COVID-19 patients. METHODS-cross sectional study in the form of an online survey. total of 400 response were finally included after inclusion and exclusion criteria RESULTS: mean age was 36.1+/-7.7 years. the prevalence of CFS to be 12% of our study sample. The most frequent symptom among the patients who met the criteria of CFS was muscle pain (52.1%) followed by postexertional malaise lasting more than 24 hours (47.9%). Less common symptoms were unrefreshing sleep, impaired memory and sore throat CONCLUSION(S): the prevalence of chronic fatigue syndrome among the recovered COVID-19 patients was 12% and these patients show moderate to severe symptoms like fatigue, impaired memory, sore throat, tender lymph nodes, muscle pain, pain in several joints, new pattern of headache, unrefreshing sleep and postexertional malaise lasting more than 24 hours.

17.
Novel Research in Microbiology Journal ; 6(4):1670-1681, 2022.
Article in English | Scopus | ID: covidwho-2261614

ABSTRACT

Recently, and after its emergence in Wuhan, China, the COVID-19 infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread in almost every country in the world. This infection has appeared as a subject of intensive debate and concern among most of the government's public health systems, researchers, and policymakers. The severity of this zoonotic disease upshot a pandemic situation, which has a long-term impact on the personal, behavioral, social, and economic, as well as on the political and state affairs. Variations in COVID-19 severity made the situation more critical to elucidate the genomics, and genetic pathways linked to susceptibility and transmission of SARS-Cov-2 infection. The current study aimed to shed some light on SARS-Cov-2 infection and COVID-19 introduction, as well as the evolutionary history, structure, pathophysiology, genetic modulation, diagnosis, and treatment, in order to provide insight into pandemic flinch, its emergence, and progression around the world. The current study also provides a summary of the near future possibility of developing the appropriate medication for COVID-19 treatment and management through the identification of new therapeutic target molecules, including vaccine development and appropriate preventive and control measures. © 2022, Egyptian Association for Medical Mycologists (EAMM). All rights reserved.

18.
Learning, Media and Technology ; 2023.
Article in English | Scopus | ID: covidwho-2260650

ABSTRACT

During the COVID-19 pandemic, most Indian schools were closed for nearly two years, despite extensive evidence showing most children could not access online learning. In our interviews with those affected by school closures in North India, teachers and parents who could access online learning described it as ‘the only option'. This aligns with the dominant framing of EdTech, both nationally and globally, as a positive and inevitable feature of learning futures. However, parents who could not access online learning stressed that it was not an option for them and called for in-person learning to resume. Although several alternatives to online learning were available, and all interviewees described some of these, for many this did not dislodge the idea that online learning was ‘the only option'. This marginalisation of alternatives is a form of ‘technological inevitabilism' that facilitated a lack of urgency in reopening schools and a widening of education inequities. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

19.
11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022 ; : 1199-1203, 2022.
Article in English | Scopus | ID: covidwho-2281688

ABSTRACT

Mental Health Issues are a hidden pandemic which will emerge in the upcoming years. As the world witnessed COVID-19 pandemic and went into lockdown, the cases of Depression, Anxiety and Stress skyrocketed than ever before. This has given rise to the need for exploring the interdisciplinary field of Artficial Intelligence and Psychometry. In this paper, we propose compare various machine learning and ensemble learning methods, on the survey dataset comprising of the DASS-42 Psychometric Test Results and Demographic information. Random Forest, Decision Tree, Support Vector Machine (SVM), AdaBoost, CatBoost, and Extreme Gradient Boosting (XGBoost) are used to classify the level of Depression, Anxiety and Stress into normal, mild, moderate, severe and extremely severe categories. In our experiments on the dataset, Support Vector Machine outperformed and reached a final F1-measure of 94%, 95% and 91% in the prediction of Depression, Anxiety and Stress, respectively. © 2022 IEEE.

20.
Indian Journal of Public Health Research and Development ; 14(2):307-313, 2023.
Article in English | EMBASE | ID: covidwho-2281668

ABSTRACT

A total of 77 literatures till November 2020 were screened regarding various interventions to treat COVID-19 patients, among which 16 and 15 studies fulfilling predefined exclusion and inclusion criteria were subjected to Pairwise and Network meta-analysis respectively. In Pairwise meta-analysis, the recovery rate of treatment with Lopinavir/Ritonavir versus other antiviral (OR= 0. 0381, CI= 0.0021-0.6870), placebo (OR= 0.6592, CI= 0.4207-1. 0329), Remdesivir (OR= 0.5286, CI= 0.3915-0.7137) and standard care (OR= 0.9787, CI= 0.8523-1.1238) in fixed and random effect model with 95% confidence limit found statistically significant protection than those of all other treatment. In Network meta-analysis, recovery estimates sizes of treatment, in reference with other antivirals 1.0000 (0.9917, 1.0000) shows less risk with treatment Standard care 0.7811 (0.6696, 0.8417), Remdesivir 0.7717 (0.6491, 0.8144), Lopinavir/ Ritonavir 0.7801 (0.6701, 0.8473), Placebo 0.7219 (0.6178, 0.7836).Copyright © 2023, Institute of Medico-legal Publication. All rights reserved.

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