Impact of Emerging COVID-19 variants on psychosocial health: A Systematic Review (preprint)

Background: The COVID-19 pandemic has had significant psychological effects on individuals and communities around the world. Studies have found that the prevalence of anxiety and depression symptoms increased significantly during the pandemic. The goal of the study is to understand how the emerging new virus variants keep the world in a state of fear and the ways in which mental health measures can be implemented and adopted to alleviate anxiety. Methods: A broad search for observational studies were carried out in Pubmed, Google Scholar, Clinical Key, and World Medical Library. Studies that reported and/or related the existence of anxiety generated by suffering or not from diseases caused by the new emerging Covid-19 viruses and that for which the full text of the article was accessible were included in the study while systematic review and meta-analysis and studies in groups were excluded. Results: 22 studies were included in the review. The deleterious psychosocial effects were the restructuring of life, establishment of unhealthy habits, emergence of "corona phobia", fear and stigma of being afflicted with the disease and spreading it to loved ones, and lack of contact with others. Increased rates of depression and anxiety were also seen. The circulating variants responsible for these main psychosocial repercussions were: Epsilon, Zeta, Eta, Iota, Kappa, Alpha, Beta, Gamma, and Delta. Social support was found to be protective. Conclusion: Hence interventions targeted at promoting mental health should be considered a public health priority.

Enhance-Net: An Approach to Boost the Performance of Deep Learning Model Based on Real-Time Medical Images

Real-time medical image classification is a complex problem in the world. Using IoT technology in medical applications assures that the healthcare sectors improve the quality of treatment while lowering costs via automation and resource optimization. Deep learning is critical in categorizing medical images, which is accomplished by artificial intelligence. Deep learning algorithms allow radiologists and orthopaedic surgeons to make their life easier by providing them with quicker and more accurate findings in real time. Despite this, the classic deep learning technique has hit its performance limits. For these reasons, in this research, we examine alternative enhancement strategies to raise the performance of deep neural networks to provide an optimal solution known as Enhance-Net. It is possible to classify the experiment into six distinct stages. Champion-Net was chosen as a deep learning model from a pool of benchmark deep learning models (EfficientNet: B0, MobileNet, ResNet-18, and VGG-19). This stage helps choose the optimal model. In the second step, Champion-Net was tested with various resolutions. This stage helps conclude dataset resolution and improves Champion-Net performance. The next stage extracts green channel data. In the fourth step, Champion-Net combines with image enhancement algorithms CLAHE, HEF, and UM. This phase serves to improve Enhance-performance. The next stage compares the Enhance-Net findings to the lightness order error (LoE). In Enhance-Net models, the current study combines image enhancement and green channel with Champion-Net. In the final step, radiologists and orthopaedic surgeons use the trained model for real-time medical image prediction. The study effort uses the musculoskeletal radiograph-bone classification (MURA-BC) dataset. Classification accuracy of Enhance-Net was determined for the train and test datasets. These models obtained 98.02 percent, 94.79 percent, and 94.61 percent accuracy, respectively. The 96.74% accuracy was achieved during real-time testing with the unseen dataset.

Learning impact of recent ICT advances based on virtual reality IoT sensors in a metaverse environment

Avatars of real individuals can be found all around the Metaverse. It has been nicknamed the "next big bang” for the Indian EdTech market, which some experts predict will reach $30 billion by 2032. Technology permeates 21st-century education, whether it is through academic programming, hands-on technical instruction, or concepts taught in classrooms and institutions. Virtual reality in the Indian educational system is still a topic of study. There isn't much research on virtual reality in education. Since women are now actively functioning as leaders and outperforming men in many spheres of life worldwide, women's empowerment is India's most powerful tool for growth. The lady governors and the countries led by these incredible women are bearing the load and pushing on alone in the struggle wherever it is needed, while the entire world holds its breath and prays every day for an unbelievable escape from the COVID-19 pandemic. Various non-governmental organizations (NGOs) seek to improve women's lives and provide them with self-sufficiency training. The government is likewise concerned about this issue and has established a number of programs to assist women. Information and communication technology (ICT) is significant in this context. ICT has improved the security, knowledge, education, employability, confidence, and popularity of women. The significance of ICT for the empowerment of women is highlighted in this study. To illuminate the various facets of ICT's impact on society, various examples have been addressed. Because of ICT, new generations of women all over the globe have defied all expectations and proven themselves in every aspect of life, even the most complicated and time-consuming realm of enterprise. In this regard, ICT may possibly become a magic wand for improving women's current situations. In this research, the eight factors that influence how ICT affects rural women's empowerment were found.

COVIDPRO-NET: a prognostic tool to detect COVID 19 patients from lung X-ray and CT images using transfer learning and Q-deformed entropy

The humankind had faced several pandemic outbreaks, and coronavirus illness (COVID-19) caused by severe, acute respiratory syndrome coronavirus 2, is designated an emergency by the World Health Organization (WHO). Recognition of COVID-19 is a challenging task. The most commonly used methods are X-ray and CT scans images to inspect COVID-19 patients. It requires specialised medical professionals to report each patient's health manually. It is found that COVID-19 shows considerable similarity to pneumonia lung disease. Thus, knowledge learned from a model to diagnose pneumonia can be translated to identify COVID-19. Transfer learning method offers a drastic performance when compared with results from conventional classification. In this study, Image pre-processing is done to alleviate intensity variations between medical images. These processed images undergo a feature extraction which is accomplished using Q-deformed entropy and deep learning extraction. The feature extraction techniques are employed to remove abnormal markers from images, noise impedance from tissues and lesions. The traits acquired are integrated to differentiate between COVID-19, pneumonia and healthy cases. The primary aim of this model is to produce an image processing tool for medical professionals. The model results to inspect how a healthy or COVID-19 individual outperforms conventional models. The maximum accuracy of the collected data set is 99.68%. [ FROM AUTHOR] Copyright of Journal of Experimental & Theoretical Artificial Intelligence is the property of Taylor & Francis Ltd 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 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 . (Copyright applies to all s.)

Covid-19 vaccination program for children: An electronic assessment of symptoms.

BACKGROUND: The evolution of COVID-19 vaccinations, which are mostly seen as crucial to curb the epidemic, is a result of remarkable and ground-breaking researches by scientists around the world. The main goal of this study was to identify the significant adverse reactions of these vaccines, specifically in Homo sapiens. METHODS: In this research, a trial version of Qualtrics CoreXM software was used, and 18 questionnaires were prototyped as part of an online survey that was done in the northern part of India. RESULTS: The dataset included survey responses from 286 vaccinated (Corbevax) respondents' samples detailing their demographics, daily activities, type of gastronomic preferences, and any prior illnesses. The data were collected between March 24, 2022, and April 26, 2022. After analysis, 70.98% of respondents who took the first dose of the medication experienced side effects, while 50.62% of respondents who took the second dose of the medication stated the same. The major side effects reported were injection site pain, fever, tiredness, body ache, headache, etc. Conclusion: After conducting a poll on children (aged 12-18) who had received the COVID-19 vaccination, we concluded that immunizations rarely cause moderate side effects that are manageable.

Outcome of COVID-19 in Kidney Transplant Patients from Eastern India: A Single Center Study.

Introduction: COVID-19 in kidney transplant recipients (KTR) had been associated with high incidence of acute kidney injury and higher mortality. Management of these patients is still evolving. Methods: A retrospective observational study was done that included all KTR aged ≥18 years and ≤65 years who had COVID-19 diagnosis via RTPCR test between 1 June 2020 and 30 May 2021. Severity of COVID-19 was determined as per the guidelines given by Government of India. Acute kidney injury was defined according to KDIGO guideline. Data was collected and analyzed using SPSS version 16.0 (Chicago, SPSS Inc.). Results: Out of 34 patients, 29 were men. Median age of patients was 39.9 years and median time since transplantation was 34 months. Presenting symptoms were fever (100%), cough (79.4%), gastrointestinal symptoms (23.5%), and dysgeusia/anosmia (23.5%). COVID-19 was severe in 17.6%, moderately severe in 32.4%, and mild in 50% of patients. Time since transplantation, duration of symptoms, hospital stay and inflammatory markers like CRP, LDH, ferritin and d-dimer were significantly associated with disease severity (P < 0.05). Steroids were increased in 55%, antiproliferative agents stopped in 97%, and calcineurin inhibitors stopped in 26% of patients. 70.6% of the patients were managed in home isolation. Acute kidney injury occurred in 58.8% cases. 75% of the AKI patients recovered by 28 days after discharge. Conclusion: Our study showed that outcome of COVID-19 in kidney transplant patients was reasonably good.

Longitudinal comparisons of mental health, burnout and well-being in patient-facing, non-patient-facing healthcare professionals and non-healthcare professionals during the COVID-19 pandemic: findings from the CoPE-HCP study.

BACKGROUND: The COVID-19 pandemic may disproportionately affect the mental health of healthcare professionals (HCPs), especially patient-facing HCPs. AIMS: To longitudinally examine mental health in HCPs versus non-HCPs, and patient-facing HCPs versus non-patient-facing HCPs. METHOD: Online surveys were distributed to a cohort at three phases (baseline, July to September 2020; phase 2, 6 weeks post-baseline; phase 3, 4 months post-baseline). Each survey contained validated assessments for depression, anxiety, insomnia, burnout and well-being. For each outcome, we conducted mixed-effects logistic regression models (adjusted for a priori confounders) comparing the risk in different groups at each phase. RESULTS: A total of 1574 HCPs and 147 non-HCPs completed the baseline survey. Although there were generally higher rates of various probable mental health issues among HCPs versus non-HCPs at each phase, there was no significant difference, except that HCPs had 2.5-fold increased risk of burnout at phase 2 (emotional exhaustion: odds ratio 2.50, 95% CI 1.15-5.46, P = 0.021), which increased at phase 3 (emotional exhaustion: odds ratio 3.32, 95% CI 1.40-7.87, P = 0.006; depersonalisation: odds ratio 3.29, 95% CI 1.12-9.71, P = 0.031). At baseline, patient-facing HCPs (versus non-patient-facing HCPs) had a five-fold increased risk of depersonalisation (odds ratio 5.02, 95% CI 1.65-15.26, P = 0.004), with no significant difference in the risk for other outcomes. The difference in depersonalisation reduced over time, but patient-facing HCPs still had a 2.7-fold increased risk of emotional exhaustion (odds ratio 2.74, 95% CI 1.28-5.85, P = 0.009) by phase 3. CONCLUSIONS: The COVID-19 pandemic had a huge impact on the mental health and well-being of both HCPs and non-HCPs, but there is disproportionately higher burnout among HCPs, particularly patient-facing HCPs.

Digital Inequalities in Cancer Care Delivery in India: An Overview of the Current Landscape and Recommendations for Large-Scale Adoption.

Introduction: COVID-19 pandemic has caused major disruptions to delivery of various cancer care services as efforts were put to control the outbreak of the pandemic. Although the pandemic has highlighted the inadequacies of the system but has also led to emergence of a new cancer care delivery model which relies heavily on digital mediums. Digital health is not only restricted to virtual dissemination of information and consultation but has provided additional benefits ranging from support to cancer screening, early and more accurate diagnosis to increasing access to specialized care. This paper evaluates the challenges in the adoption of digital technologies to deliver cancer care services and provides recommendation for large-scale adoption in the Indian healthcare context. Methods: We performed a search of PubMed and Google Scholar for numerous terms related to adoption of digital health technologies for cancer care during pandemic. We also analyze various socio-ecological challenges-from individual to community, provider and systematic level-for digital adoption of cancer care service which have existed prior to pandemic and lead to digital inequalities. Results: Despite encouraging benefits accruing from the adoption of digital health key challenges remain for large scale adoption. With respect to user the socio-economic characteristics such as age, literacy and socio-cultural norms are the major barriers. The key challenges faced by providers include regulatory issues, data security and the inconvenience associated with transition to a new system. Policy Summary: For equitable digital healthcare, the need is to have a participatory approach of all stakeholders and urgently addressing the digital divide adequately. Sharing of health data of public and private hospitals, within the framework of the Indian regulations and Data Protection Act, is critical to the development of digital health in India and it can go a long way in better forecasting and managing cancer burden.

The role of herbal plants in the inhibition of SARS-CoV-2 main protease: A computational approach

COVID-19 has quickly spread across the globe, becoming a pandemic. This disease has a variable impact in different countries depending on their cultural norms, mitigation efforts and health infrastructure. This study aims to assess the herbal plants in the pursuit of potential SARS-CoV-2 Mpro inhibitors using in silico approaches. We have considered 16 extracted compounds of 10 different species of these plants. In order to explain their inhibition properties and chemical reactivity pattern, we have performed the density functional theory based calculations of frontier molecular orbitals, molecular electrostatic potential surface and chemical reactivity descriptors. Our calculated lipophilicity, aqueous solubility and binding affinity of the extracted compounds suggest that the inhibition potentials in the order;harsingar > aloe vera > giloy > turmeric > neem > ginger > red onion > tulsi > cannabis > black pepper. On comparing the binding affinity with hydroxychloroquine, we note that the inhibition potentials of the extracts of harsingar, aloe vera and giloy are very promising. In order to validate this, we have also performed MD simulation and MM-PBSA binding free energy analysis. Therefore, we believe that these findings will open further possibilities and accelerate the works towards finding an antidote for this malady.

Characterization of aerosol plumes from singing and playing wind instruments associated with the risk of airborne virus transmission.

The exhalation of aerosols during musical performances or rehearsals posed a risk of airborne virus transmission in the COVID-19 pandemic. Previous research studied aerosol plumes by only focusing on one risk factor, either the source strength or convective transport capability. Furthermore, the source strength was characterized by the aerosol concentration and ignored the airflow rate needed for risk analysis in actual musical performances. This study characterizes aerosol plumes that account for both the source strength and convective transport capability by conducting experiments with 18 human subjects. The source strength was characterized by the source aerosol emission rate, defined as the source aerosol concentration multiplied by the source airflow rate (brass 383 particle/s, singing 408 particle/s, and woodwind 480 particle/s). The convective transport capability was characterized by the plume influence distance, defined as the sum of the horizontal jet length and horizontal instrument length (brass 0.6 m, singing 0.6 m and woodwind 0.8 m). Results indicate that woodwind instruments produced the highest risk with approximately 20% higher source aerosol emission rates and 30% higher plume influence distances compared with the average of the same risk indicators for singing and brass instruments. Interestingly, the clarinet performance produced moderate source aerosol concentrations at the instrument's bell, but had the highest source aerosol emission rates due to high source airflow rates. Flute performance generated plumes with the lowest source aerosol emission rates but the highest plume influence distances due to the highest source airflow rate. Notably, these comprehensive results show that the source airflow is a critical component of the risk of airborne disease transmission. The effectiveness of masking and bell covering in reducing aerosol transmission is due to the mitigation of both source aerosol concentrations and plume influence distances. This study also found a musician who generated approximately five times more source aerosol concentrations than those of the other musicians who played the same instrument. Despite voice and brass instruments producing measurably lower average risk, it is possible to have an individual musician produce aerosol plumes with high source strength, resulting in enhanced transmission risk; however, our sample size was too small to make generalizable conclusions regarding the broad musician population.

Measurements and Simulations of Aerosol Released while Singing and Playing Wind Instruments.

Outbreaks from choir performances, such as the Skagit Valley Choir, showed that singing brings potential risk of COVID-19 infection. There is less known about the risks of airborne infection from other musical performances, such as playing wind instruments or performing theater. In addition, it is important to understand methods that can be used to reduce infection risk. In this study, we used a variety of methods, including flow visualization, aerosol and CO2 measurements, and computational fluid dynamics (CFD) modeling to understand the different components that can lead to transmission risk from musical performance and risk mitigation. This study was possible because of a partnership across academic departments and institutions and collaboration with the National Federation of State High School Associations and the College Band Directors National Association. The interdisciplinary team enabled us to understand the various aspects of aerosol transmission risk from musical performance and to quickly implement strategies in music classrooms during the COVID-19 pandemic. We found that plumes from musical performance were highly directional, unsteady and varied considerably in time and space. Aerosol number concentration measured at the bell of the clarinet was comparable to that of singing. Face and bell masks attenuated plume velocities and lengths and decreased aerosol concentrations measured in front of the masks. CFD modeling showed differences between indoor and outdoor environments and that the lowest risk of airborne COVID-19 infection occurred at less than 30 min of exposure indoors and less than 60 min outdoors.

Signaling Pathway Reporter Screen with SARS-CoV-2 Proteins Identifies nsp5 as a Repressor of p53 Activity.

The dysregulation of host signaling pathways plays a critical role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and viral pathogenesis. While a number of viral proteins that can block type I IFN signaling have been identified, a comprehensive analysis of SARS-CoV-2 proteins in the regulation of other signaling pathways that can be critical for viral infection and its pathophysiology is still lacking. Here, we screened the effect of 21 SARS-CoV-2 proteins on 10 different host signaling pathways, namely, Wnt, p53, TGFß, c-Myc, Hypoxia, Hippo, AP-1, Notch, Oct4/Sox2, and NF-κB, using a luciferase reporter assay. As a result, we identified several SARS-CoV-2 proteins that could act as activators or inhibitors for distinct signaling pathways in the context of overexpression in HEK293T cells. We also provided evidence for p53 being an intrinsic host restriction factor of SARS-CoV-2. We found that the overexpression of p53 is capable of reducing virus production, while the main viral protease nsp5 can repress the transcriptional activity of p53, which depends on the protease function of nsp5. Taken together, our results provide a foundation for future studies, which can explore how the dysregulation of specific signaling pathways by SARS-CoV-2 proteins can control viral infection and pathogenesis.

Silent Hypoxia in Coronavirus disease-2019: Is it more dangerous? -A retrospective cohort study.

Background: Hypoxia in patients with COVID-19 is one of the strongest predictors of mortality. Silent hypoxia is characterised by the presence of hypoxia without dyspnoea. Silent hypoxia has been shown to affect the outcome in previous studies. Methods: This was a retrospective study of a cohort of patients with SARS-CoV-2 infection who were hypoxic at presentation. Clinical, laboratory and treatment parameters in patients with silent hypoxia and dyspnoeic hypoxia were compared. Multivariate logistic regression models were fitted to identify the factors predicting mortality. Results: Among 2080 patients with COVID-19 admitted to our hospital, 811 patients were hypoxic with SpO2 <94% at the time of presentation. Among them, 174 (21.45%) did not have dyspnoea since the onset of COVID-19 symptoms. Further, 5.2% of patients were completely asymptomatic for COVID-19 and were found to be hypoxic only on pulse oximetry. The case fatality rate in patients with silent hypoxia was 45.4% as compared to 40.03% in dyspnoeic hypoxic patients (P = 0.202). The odds ratio of death was 1.1 (95% CI: 0.41-2.97) in the patients with silent hypoxia after adjusting for baseline characteristics, laboratory parameters, treatment and in-hospital complications, which did not reach statistical significance (P = 0.851). Conclusion: Silent hypoxia may be the only presenting feature of COVID-19. As the case fatality rate is comparable between silent and dyspnoeic hypoxia, it should be recognised early and treated as aggressively. Because home isolation is recommended in patients with COVID-19, it is essential to use pulse oximetry in the home setting to identify these patients.

Long-term ecological research and the COVID-19 anthropause: A window to understanding social-ecological disturbance.

The period of disrupted human activity caused by the COVID-19 pandemic, coined the "anthropause," altered the nature of interactions between humans and ecosystems. It is uncertain how the anthropause has changed ecosystem states, functions, and feedback to human systems through shifts in ecosystem services. Here, we used an existing disturbance framework to propose new investigation pathways for coordinated studies of distributed, long-term social-ecological research to capture effects of the anthropause. Although it is still too early to comprehensively evaluate effects due to pandemic-related delays in data availability and ecological response lags, we detail three case studies that show how long-term data can be used to document and interpret changes in air and water quality and wildlife populations and behavior coinciding with the anthropause. These early findings may guide interpretations of effects of the anthropause as it interacts with other ongoing environmental changes in the future, particularly highlighting the importance of long-term data in separating disturbance impacts from natural variation and long-term trends. Effects of this global disturbance have local to global effects on ecosystems with feedback to social systems that may be detectable at spatial scales captured by nationally to globally distributed research networks.

Multisystem Inflammatory Syndrome in Adults or Hemophagocytic Lymphohistiocytosis: A Clinical Conundrum in Fully Vaccinated Adults With Breakthrough COVID-19 Infections.

Hyperinflammatory syndrome with breakthrough coronavirus disease 2019 (COVID-19) infection in a fully vaccinated patient is not a common finding. To the best of our knowledge, this is the first such case of a patient who received the Spikevax/Moderna (elasomeran mRNA-1273) vaccine. The patient exhibited clinical characteristics consistent with both multisystem inflammatory syndrome in adults (MIS-A) and hemophagocytic lymphohistiocytosis (HLH), thus posing a diagnostic challenge. Multi-inflammatory syndrome in COVID-19 patients is frequently seen in the pediatric population, but it is a rare entity in adults especially after receiving COVID-19 vaccination. The pathophysiology of MIS-A is not completely understood yet, but it is believed that this likely occurs due to antibody-mediated immune dysregulation. There is a possibility of enhanced serologic response in patients like ours who are vaccinated and have breakthrough COVID-19 infection, thus paving the way for overwhelming antibody-mediated immune activation. There is a significant overlap between symptoms of MIS-A and other hyperinflammatory syndromes such as HLH; hence, a high degree of clinical suspicion and thorough diagnostic workup is required to explore all differentials. Our case raises concerns regarding the lack of clear algorithms and guidelines to diagnose and manage MIS-A in adults post-COVID-19 vaccination.

India's food system in the time of COVID-19

India's complete lockdown has caused unnecessary disruptions in the food supply chain, with the scarcity of labour making it even worse. A sharp decline in demand is imminent with the financial sector being in a freeze and incomes having shrunk for everyone, except for the small salaried class. Consumer sentiment and business outlook on recovery are bleak. While ensuring the free movement of essential goods and availability and safety of labour can mitigate the immediate disruptions in the supply chain, unclogging the financial sector and restoring optimism in the market will take time and heroic efforts from the government.

Outcomes by time to definitive chemoradiation treatment for patients with muscle-invasive bladder cancer.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has raised concerns about delaying treatment for localized cancer and its impact on long-term outcomes. OBJECTIVE: We aimed to investigate the impact of time to chemoradiation (CRT) on recurrence and survival outcomes for patients with muscle-invasive bladder cancer (MIBC). METHODS: In the national Veterans Affairs' database, we identified patients with urothelial histology, MIBC (T2-4a/N0-3/M0) diagnosed between 2000 to 2018 and treated with definitive CRT. Time to treatment was defined as the number of days between date of diagnosis and start date of CRT. The cohort was stratified into < 90 (early) or ≥ 90 days (delayed) groups. Endpoints of locoregional failure (LRF), distant failure (DF), overall survival (OS), and bladder cancer-specific survival (BCS) were evaluated in multivariable Cox and Fine-Gray models. RESULTS: 305 patients with MIBC underwent CRT - 190 (62.3%) received early CRT, 115 (37.7%) received delayed CRT. Multivariable analysis (including success of transurethral resection of bladder tumor and type of chemotherapy) revealed no difference in recurrence between groups - LRF HR 1.12 (95%CI 0.76-1.67, P = 0.56) and DF HR 1.03 (95%CI 0.70-1.53, P = 0.88). Similarly, there were no differences in survival outcomes. The lack of association was maintained at both earlier and later time cutoffs (60-120 days). CONCLUSIONS: Our findings suggest that a short-term delay in definitive therapy may not affect long-term outcomes for patients with MIBC undergoing CRT. This study does not endorse delays in therapy, but rather provides information to aid patients and clinicians navigate the unique challenges of MIBC care in both pandemic and non-pandemic times.

Glycolytic inhibitor 2-deoxy-d-glucose attenuates SARS-CoV-2 multiplication in host cells and weakens the infective potential of progeny virions.

AIMS: Virus-infected host cells switch their metabolism to a more glycolytic phenotype, required for new virion synthesis and packaging. Therefore, we investigated the effect and mechanistic action of glycolytic inhibitor 2-Deoxy-d-glucose (2-DG) on virus multiplication in host cells following SARS-CoV-2 infection. MAIN METHODS: SARS-CoV-2 induced change in glycolysis was examined in Vero E6 cells. Effect of 2-DG on virus multiplication was evaluated by RT-PCR (N and RdRp genes) analysis, protein expression analysis of Nucleocapsid (N) and Spike (S) proteins and visual indication of cytopathy effect (CPE), The mass spectrometry analysis was performed to examine the 2-DG induced change in glycosylation status of receptor binding domain (RBD) in SARS-CoV-2 spike protein. KEY FINDINGS: We observed SARS-COV-2 infection induced increased glucose influx and glycolysis, resulting in selectively high accumulation of the fluorescent glucose analog, 2-NBDG in Vero E6 cells. 2-DG inhibited glycolysis, reduced virus multiplication and alleviated cells from virus-induced cytopathic effect (CPE) in SARS-CoV-2 infected cells. The progeny virions produced from 2-DG treated cells were found unglycosylated at crucial N-glycosites (N331 and N343) of the receptor-binding domain (RBD) in the spike protein, resulting in production of defective progeny virions with compromised infective potential. SIGNIFICANCE: The mechanistic study revealed that the inhibition of SARS-COV-2 multiplication is attributed to 2-DG induced glycolysis inhibition and possibly un-glycosylation of the spike protein, also. Therefore, based on its previous human trials in different types of Cancer and Herpes patients, it could be a potential molecule to study in COVID-19 patients.