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Background: The World Health Organization (WHO) designated SARS-CoV-2 infection as coronavirus disease 2019 (Covid-19).Due to the government implication of Covid-19 specific guideline of using mask, there could be a significant decrease in the allergic rhinitis. Objective(s): Present study aims to analyze the changes in the trends of nasal allergies from hilly regions of Himachal Pradesh following Covid-19 pandemic. Method(s): The prospective data obtained from January 2022 to November 2022 was compared from the retrospective data available between January 2019 to November 2019. Prospectively, a total of 596 patients were included in the study. All these patients underwent Skin prick tests for common allergens. All these patients also underwent testing for total IgE levels in biochemistry lab of the hospital by chemiluminescence method.The results were compared with retrospective dataof 728 age sex match patients. Result(s): A significant difference in the allergen sensitivity was observed. The number of patients who were sensitized during Covid was comparatively less than those during Pre covid period.Dust mite, Cockroach, Peanut and Wheat revealed a non-significant odds ratio indicating that they were not true predictors for sensitization and non-sensitization. Whereas Grass pollen, Mould mix and Pine mix revealed a significant odds ratio. Usage of mask found to have an impact on improvement in symptoms. Majority of the patients who did not use mask had no improvement in symptoms. Majority of the patients had high IgE levels in pre covid period whereas it was normal for majority of them during covid. Conclusion(s): In our study, allergic rhinitis incidence decreased throughout the pandemic period. After pandemic, there was a noticeably decreased level of sensitivity to grass pollen, mould, and pine mix. Use of face masks lead to significant decrease in symptoms of allergic rhinitis.Copyright © 2022, Anka Publishers. All rights reserved.
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In this paper, we present a minimally-supervised approach to identify human needs expressed in tweets. Taking inspiration from Frustration-Aggression theory, we trained RoBERTa model to classify tweets expressing frustration which serves as an indicator of unmet needs. Although the notion of frustration is highly subjective and complex, the findings support the use of pretrained language model in identifying tweets with unmet needs. Our study reveals the major causes behind feeling frustrated during the lockdown and the second wave of the COVID-19 pandemic in India. Our proposed approach can be useful in timely identification and prioritization of emerging human needs in the event of a crisis. © 2022 Association for Computational Linguistics.
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With the COVID-19 pandemic outbreak, most countries have limited their grain exports, which has resulted in acute food shortages and price escalation in many countries. An increase in agriculture production is important to control price escalation and reduce the number of people suffering from acute hunger. But crop loss due to pests and plant diseases has also been rising worldwide, inspite of various smart agriculture solutions to control the damage. Out of several approaches, computer vision-based food security systems have shown promising performance, and some pilot projects have also been successfully implemented to issue advisories to farmers based on image-based farm condition monitoring. Several image processing, machine learning, and deep learning techniques have been proposed by researchers for automatic disease detection and identification. Although recent deep learning solutions are quite promising, most of them are either inspired by ILSVRC architectures with high memory and computational requirements, or light convolutional neural network (CNN) based models that have a limited degree of generalization. Thus, building a lightweight and compact CNN based model is a challenging task. In this paper, a transformer-based automatic disease detection model “PlantViT" has been proposed, which is a hybrid model of a CNN and a Vision Transformer. The aim is to identify plant diseases from images of leaves by developing a Vision Transformer-based deep learning technique. The model takes the capabilities of CNNs and the Vision Transformer. The Vision Transformer is based on a multi-head attention module. The experiment has been evaluated on two large-scale open-source plant disease detection datasets: PlantVillage and Embrapa. Experimental results show that the proposed model can achieve 98.61% and 87.87% accuracy on the PlantVillage and Embrapa datasets, respectively. The PlantViT can obtain significant improvement over the current state-of-the-art methods in plant disease detection. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Cooking has played an essential role in the growth of culture and civilization for the past 1.8 million years. However, the lockdown in various countries, including Germany, has prompted people to improve their health and well-being due to the coronavirus pandemic. While doing this, searching for recipes becomes one of the popular and essential activities as it allows people worldwide to prepare dishes from various countries. But finding recipes on the internet is like searching in the wild with thousands of recipes available for a single dish. Traditional recipes are essential in a human being’s life. However, for students away from home or working young people who have little time to cook, many recipes have been forgotten for a long time. Therefore, MISOhungry gives solutions to both the user groups through this platform. The recipes provided are by scraping data from online food blogs to create recipes complete with ingredients nutritional information. On the same site, youngsters may also access traditional recipes provided by the elderly. Studies show that sharing recipes linked with memories stimulates generative activity in older adults and makes them happy later. The study demonstrates that the platform is accessible to both user groups, young people are interested in receiving traditional recipes, and they would like to use this platform which directly bridges the generation gap in recipe sharing, search, and management. MISOhungry promotes the idea of “Happiness is Homemade” by making cooking more accessible to both user groups. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Background: Tocilizumab is an IgG1 class humanized monoclonal antibody targeting IL-6 receptor (IL-6R). IL-6 is a key cytokine involved in cytokine storm of severe COVID-19. Tocilizumab down-regulates IL-6 preventing fatal and permanent damage to vital organs, significantly preventing COVID-19 related mortality and morbidity. Therefore, this study aimed to compare the efficacy and safety of Tocilizumab (biosimilar) developed by Hetero Biopharma Ltd, India vs reference medicinal product (RMP)-Tocilizumab manufactured by Roche in cytokine storm of severe COVID-19 pneumonia. Methods: This multicenter, randomized, double-blind, active-controlled study enrolled patients aged 18 to 65 years, with laboratory-confirmed, hospitalized, severe COVID-19 disease with elevated inflammatory markers not on mechanical ventilation. Patients were randomized (3:1 ratio) to receive either Test-Tocilizumab (Test) 8 mg/kg or RMP-Tocilizumab 8mg/kg, maximum 800mg, administered once on day 1. The primary endpoint was the cumulative proportion of patients requiring mechanical ventilation by Day 14. Secondary endpoints included 28 day mortality rate, proportion of patients with a 2-point decrease in WHO ordinal scale, time to clinical failure (death or required mechanical ventilation or withdrawn), change in inflammatory markers (CRP, IL-6, Ferritin and D-dimer) and duration of hospital stay in days. Safety endpoints included the incidence of adverse events;the proportion of patients discontinued the study due to adverse events and the incidence of any post-treatment bacterial and/or fungal infection. Results: Out of 211 patients screened, 172 patients were randomized (131 to Test and 41 to RMP) to receive Tocilizumab 8mg/kg. Patients were similar in both groups at baseline in terms of age, gender, weight etc. Fourteen (10.69%) patients in Test and 5 (12.20%) patients in RMP progressed to mechanical ventilation by Day 14 (p=0.7789). Overall, 9 (7.83%) patients died in Test vs 5 (13.16%) in RMP during 28 days follow up (p=0.3382). Clinical improvement was seen 62.60% and 77.10% vs 53.66% and 73.17% in Test vs RMP at day 14 and 28 respectively. The time to clinical failure was 6 vs 5 days and time to clinical improvement was 11 vs 11.5 days. Hospitalization duration was 12.9 versus 13.8 days in the Test and RMP. ARDS, Insomnia and Pain were most commonly reported adverse events. Conclusion: Tocilizumab biosimilar is comparable with RMP-Tocilizumab in preventing mechanical ventilation in severe COVID19 pneumonia patients.
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OBJECTIVE: As COVID-19 engulfed the world, people are shifting to a new way of life with social distancing and self isolation, especially in developing countries. In such a scenario, online retailing has gone through a sea change with a new wave of increased demand and where the healthcare sector has also adjusted with the augmented transition from physical shops to e-commerce. The current study aims to assess the adoption and usage intention of consumers towards telemedicine among people during pandemic times. METHOD: The adoption of telemedicine by consumers depends upon some factors such as reliability, affordability, convenience, authenticity, offers and discount;which could enhance the intention to adopt and continual use by consumers. A modified version of 'Technology Acceptance Model' is incorporated in this study to validate the concept of adoption of telemedicine in cities of North India. RESULTS: The study has found the positive and significant relationship between the factors of adoption and the intention to adopt telemedicine. Also, the 'Effect of COVID-19' plays a moderating role between the different factors of adoption and the intention to adopt telemedicine. CONCLUSION: The adoption of telemedicine by people is significantly associated with different internal and external factors. The intention to adopt telemedicine is the construct that strongly influences the actual usage of telemedicine in developing countries. The scope of this study is restricted to the Northern region of India. A future study can be undertaken in relation to the global perspective of consumers.
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Background:COVID-19 is a respiratory disease caused by novel coronavirus SARS CoV -2 and has been declared as pan- demic by WHO. The timely detection of cases and their contacts is crucial to help curtail the pandemic. Introduction of antigen based RDT has been able to bridge the time gap of detection and tracing as these tests are timely and easy to perform. However the real world performance of these assays is uncertain and the sensitivity of the test is claimed to be between 50% to 87%. This study was conducted to evaluate the currently used antigen -based RDT for the detection of SARS CoV-2 virus in respiratory specimens. Methods:This prospective study included patients who were seeking healthcare in Ophthalmology department for eye ailments and were subjected to SARS CoV-2 antigen based RDT. Regardless of results of RDT, nasopharyngeal swabs were collected from these patients and were tested for SARS CoV-2 RNA by real-time RT PCR using commercial assay (SD Biosensor). The evaluation of antigen-based RDT for the detection of SARS CoV-2 virus was performed with real time RT-PCR as gold standard. Results:A total of 564 patients were tested by both antigen based RDT and real time RT -PCR. The antigen based RDT exhibited analytical sensitivity and specificity of 37.5% and 99.79% respectively. Positive predictive value and negative predictive value of RDT were 96.4% and 91.6% respectively. Negative correlation was found between antigens based RDT’s positivity and Ct values of E and RdRp genes. Conclusions:Overall poor sensitivity of RDT does not allow adopting it as point of care test in screening for COVID -19 and it only serves as an additional test to RT-PCR because of potential false negative results.
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The lockdown has seen an increase in the use of Internet among the public. It has also emphasized the need to look into the factors related to excessive use as well as its management. The clinical interview was carried out to understand the pattern of Internet use among cases presented to tertiary specialty clinic for the management of technology use. The clinical interview revealed an increased use of Internet immediately after the lockdown. The increased use was attributed to the modality of passing time with limited options of entertainment as well as to cope up with negative emotions. It implicates the need for building awareness about excessive use of Internet during lockdown as well as strategies to promote healthy use of technology.
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Background: Patients with cardiovascular disease (CVD) are at an increased risk of developing severe disease and mortality associated with coronavirus disease 2019 (COVID-19). Statins form the cornerstone of therapy for primary and secondary prevention of CVD. Objective: This review aims at exploring the possible advantages and the risks associated with the use of statins in patients with COVID-19. Methods: We searched the PubMed and Google Scholar databases until June 5, 2020, and reviewed the available literature on this topic. Results: Statins have been shown to improve outcomes in acute respiratory distress syndrome, which is one of the major causes of death in COVID-19. Statins exert many pleiotropic effects (anti-inflammatory, immunomodulatory effect, nitric oxide release, and effects on coagulation cascade), which would theoretically appear beneficial in COVID-19. Statins also increase angiotensin-converting enzyme 2 levels in animal models and can potentially reduce lung injury related to viral infections. Besides, the cardioprotective effects of statins can be beneficial in cardiovascular complications (e.g., acute myocardial infarction) of COVID-19. Nonetheless, there are concerns regarding the adverse effects associated with the use of statins in the setting of COVID-19, which can be simply avoided by dose modification and clinical monitoring. Conclusions: Statins appear to be beneficial in COVID-19 and may improve the outcome, but future-focused studies are needed before recommending their de novo use in COVID-19.