Therapeutic Options for the Treatment of 2019-Novel Coronavirus in India: A Review

Purpose: As of, from 30th Jan to 31st May, 2020, more than 182,143 confirmed cases were reported in India along with 86,984 recovered cases and 5164 deceased cases of COVID-19. More than 53 countries are also affected with this pandemic virus. However, the lack of specific drugs to prevent/treat this pandemic disease is a major problem in this current scenario. In this re-gard, this systemic review was conducted to identify the therapeutic approaches and researches, which are ongoing in India against COVID-19. Method(s): We had screened Google Scholar database with the keywords nCoV, corona virus in In-dia, effect of SARS-CoV-2 in India, 2019-nCoV, treatment pattern in India for nCoV and therapy used to treat nCoV in India. In the final review, we had included a total of 49 articles. Result(s): As a result we had found that the Indian Council of Medical Research and NIH have giv-en a standard guideline of Hydroxychloroquine and other antiviral drugs for nCoV, and also there are various researches going on related to nCoV treatment like, chemicals from natural products, herbs and spices commonly used in India, combination therapy of lopinavir and ritonavir, ultra-vio-let radiation therapy, molecular dynamic (MD) simulations of molecules for vaccine preparation, Convalescent plasma transfusion (CPT) therapy and many more. Conclusion(s): New drugs and therapy are in the premature stage for this hazardous pandemic. We need more time to gain the detailed knowledge of the life cycle of the nCoV, which can speed up the drug/vaccine development process against nCoV.Copyright © 2022 Bentham Science Publishers.

Impact Assessment of ‘ICT Practices' on ‘Supply Chain Management Performance' in Automotive Industry in India

In the era of COVID-19, most of the business declined and a huge loss of jobs due to no demand and automobile sector is not the exception. Nearly 7.5% of India's GDP comes from the car industry, and supply chain is one of the key factors in a firm's overall value creation. The efficient and effective supply chain is dependent on information and communication technologies (ICTs) at present, and hence, it implies that ICT is spine of SCM. The major objective of the study was to draw conclusions on how information and communications technology practices affect supply chain management performance in the Indian auto-sector. The outcomes state that ICT practices have high correlation and direct impact on SCM performance, however, it does not have much impact on operational performance. The research also suggested that better and more effective ICT practices result better supply chain performance. The limitation of the research was the respondents' voluntary cooperation, and the ICT practices are limited to supply chain operational performance in various departments and functions only and not the applications in any vehicles. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Study to Analyse Covid-19 Outbreak Using Multiple Linear Regression: A Supervised Machine Learning Approach

Introduction: Globally, COVID-19 have impacted people's quality of life Machine learning have recently be-come popular for making predictions because of their precision and adaptability in identifying diseases. This study aims to identify significant predictors for daily active cases and to visualise trends in daily active, positive cases, and immunisations. Material and methods: This paper utilized secondary data from Covid-19 health bulletin of Uttarakhand and multiple linear regression as a part of supervised machine learning is performed to analyse dataset. Results: Multiple Linear Regression model is more accurate in terms of greater score of R2 (=0.90) as com-pared to Linear Regression model with R2 =0.88. The daily number of positive, cured, deceased cases are significant predictors for daily active cases (p <0.001). Using time series linear regression approach, cumulative number of active cases is forecasted to be 6695 (95% CI: 6259-7131) on 93rd day since 18 Sep 2022, if similar trend continues in upcoming 3 weeks in Uttarakhand. Conclusion: Regression models are useful for forecasting COVID-19 instances, which will help governments and health organisations address this pandemic in future and establish appropriate policies and recommen-dations for regular prevention. © 2023 National Journal of Community Medicine.

Clinicopathological association of mucormycosis in COVID 19 pandemic.

Context: Coinfection and superadded infections in patients with coronavirus disease 2019 (COVID-19) has been reported on multiple series. The emerging second wave of the pandemic has come with a lot of changes, especially in developing countries like India. One of such changes is sudden, significant rise in mucormycosis cases. Aims: To find out clinicopathological association of invasive mucormycosis with COVID-19 infection status and immunocompromised state. Settings and Design: A cross-sectional study done at a tertiary care centre. Methods and Material: All cases admitted in the dedicated mucormycosis ward between 1-06-2021 and 15-06-2021 were included in the study. The cases were admitted with suspicion of mucormycosis. The histopathological results were correlated with KOH mount and radiological reports. The clinicopathological association of occurrence of mucormycosis in post-covid and non-COVID patients along with other risk factors. Statistical Analysis Used: Odds ratio, chi square test were used to find the association using MS Excel 2010 and SPSS. Results: Thirty-six (81.82%) cases were of the post-COVID status, and 8 cases were non-COVID status. Out of 36 post-COVID patients, 33 (91.67%) showed evidence of invasive mucormycosis and of 8 non-COVIDpatients, 7 had evidence of mucormycosis (odds ratio = 1.57). Out of the total diagnosed cases of mucormycosis, 21 (52.5%) patients were known cases of diabetes mellitus (DM), and 7 (17.5%) cases of newly diagnosed hyperglycemia. Thirty (75%) patients out of 40 had some form of immunocompromised state. This shows statistically significant association of DM and immunocompromised state with the occurrence of mucormycosis in post-COVID patients (chi square value2 = 6.891, P value = 0.008). Twenty-five patients had the history of steroid use during the treatment of COVID-19. Conclusions: The infection with COVID-19 definitely increases the odds of contracting mucormycosis, but most of the cases had diabetes mellitus. So, it is possible that COVID-19 virus predisposes individuals to invasive fungal infection by precipitating DM.

Re-imagining Time in the Midst of Crisis: From Sci Fi Thrillers and Zombie Flicks to Young People's Lived Temporalities of COVID-19

Popular films often depict pandemics in apocalyptic ways, temporally portraying how day by day, fear increases as a virus takes over the world. The speed of transmission, alongside the virus's seemingly unstoppable global spread, evoke a sense of being engulfed by the extraordinary, creating an experience of time characterised by feelings of intensity and fear, both on and off-screen. In contrast, the lived realities of young New Zealanders during the COVID-19 pandemic speak to a more elongated, 'empty' experience of time that lacks such intensity. Our interviews with New Zealand youth revealed their sense of time as ever-shifting, characterised occasionally by moments of fear and anxiety, but much more so by long hours of boredom and disturbing lack of structure, particularly during lockdowns. This paper draws on Bakhtin's notion of the chronotope, alongside Bergson's insights into lived experiences of time and Deleuze's Cinema books, to compare the emotional temporalities of two leading science fiction pandemic films, 'Contagion' and 'Outbreak', and a range of popular zombie movies, to young New Zealanders' lived experiences of multiple COVID-19 lockdowns. We consider how New Zealand youth (in our interviews, but also on social media) narrate their lived experiences of COVID-19 by drawing upon an 'imaginative repertoire' made up of sci fi films, zombie references and moral ideas of the self, which can help us to better understand how temporality is reshaped during a pandemic, particularly for young people.

Role of Urban Control Centers for City Planning and Monitoring in a Pandemic Outbreak

The whole world is struggling with the staggering consequences of the pandemic COVID -19. Governments and organizations worldwide are discussing how novel and innovative technologies can be used to eliminate the effects of the pandemic and how the coming pandemics can be averted or contained. Among the proposed solutions, the advancement of additional competent and comprehensive smart city initiatives will improve the way critical data is retrieved, managed, stored and distributed in a pandemic by reducing the implementation time for dangerous activities. The best response to a pandemic is to use various technological solutions that can eventually be deployed in an integrated manner, exploring numerous options. Therefore, this article discusses possible solutions, including contemporary approaches that are practical and helpful in developing novel health-oriented smart cities. The pandemic COVID -19 is forcing new ways for city governments to manage public health emergencies and protect city residents. To this end, urban control centres play an essential role in the surveillance and management of the city’s dynamics. The urban monitoring centre identifies irregularities and takes care of them. It also ensures that any disturbances or problems in the city are either appropriately rectified or immediately addressed so that the city returns to its normal operations as soon as possible. © 2022 Nova Science Publishers, Inc.

Universal Healthcare Distant Dream or Reality: An Initiative by Rajasthan State through Chiranjeevi Swasthya Bima Yojana

"If health care is not affordable & accessible to all, is not of any use" Since the COVID-19 outbreak in 2020, many people have been forced to give up their savings for the treatment of their families or for themselves. While the beds at the government hospitals were always occupied, many had to rush to the private hospitals at times of an emergency. It made a considerably large hole in the pockets of the middle-class Indians. Recently, in view of the current situation, a health insurance scheme was launched by the name of 'Mukhyamantri Chiranjeevi SwasthyaBima Yojana' by the chief minister of Rajasthan, Ashok Gehlot. This state-operated scheme is supposed to offer cashless treatment to the residents of the state. Let's dive into details and learn about the different benefits this scheme is supposed to offer to the citizens of Rajasthan. A large number of people in the State are not able to afford the expenditure of their treatment. High expenditure on health care is the major cause of rural indebtedness. The Rajasthan State Government has taken an unprecedented decision to start the CHIRANJEEVI SWASTHYA BIMA YOJANA has been started in the state from 1st may 2021. Rajasthan has taken a step towards 'universal health coverage' by providing quality free medical services to the citizens of the state on hospitalization in government as well as private hospitals and reducing the expenditure incurred by the family for health services. To assess the awareness and understanding of Chiranjeevi Swasthya Bima Yojana in Bikaner Administrative Division a primary research was conducted on 400 respondents in Bikaner Division througharea sampling. The primary data was collected through schedule and data was analysed through Microsoft Excel and descriptive statistical measures like percentage and mean were calculated. The data collected for this study showed that the awareness level of Chiranjeevi SwasthyaBima Yojana in Bikaner Administrative Division was low in urban areas.

Evaluating the relevance and influence of the Internet of things and Deep Learning on Organisations during Economic downturns

The study explores about Current advancements in manufacturing techniques and automation have resulted in 'Industry 4.0, a new industrial revolution. Industry 4.0' is a vast subject that encompasses information management, industrial competitiveness, manufacturing processes, and productivity. The phrase Industry 4.0 refers to a set of important allowing 'technologies, such as the Internet of Things (IoT), Deep Learning, and artificial intelligence', which are key sources to automated and computerized industrial settings. 'Industry 4.0 technologies' aid in the attainment of sustainability in corporate processes. The present study achievements and future studies potential of Industry 4.0 technologies to accomplish 'manufacturing sustainability' are investigated using a comprehensive literature review method for the research. 'The function and effect of several Industry 4.0 technologies on manufacturing sustainability are thoroughly' addressed. However, loT may have a major impact on the economy and society. Some fear that it may result in the formation of amazingly centers of income and expertise, which will have a negative impact on the whole economy. Today, the coronavirus infection COVID-19 is wreaking havoc on the economies of most nations, causing disruptions in supply chains, the failure of small and medium-sized enterprises, an increase in the number of jobless, and other consequences. Under these circumstances, the digitization of all economic sectors and individuals' fundamental aspects of life becomes extremely vital. The essay examines multinational organizations connected to the idea of Industry 4.0 and illnesses caused by coronavirus infection. Artificial intelligence systems can aid in the mapping, management, prediction, and modelling of complicated systems, decreasing uncertainty and assisting experts in making decisions. The Internet of Things enables data transmission, improves control and automation, and gives potential to reduce the business's operational expenses. © 2022 IEEE.

Robust Approach for Detecting Face Mask Using Deep Learning and Its Comparative Analysis

The world is fighting against the novel coronavirus, and a lot of people have lost their lives with the scenario getting bad to worse and worst. This infection is communicated from one individual to another while wheezing or talking as drops. To prevent Covid-19, wearing masks is very beneficial. In this paper, an existing model, ‘DenseNet201’, is being modified to efficiently track the persons who are wearing a mask or not. This system uses a convolutional neural network (CNN) and computer vision to limit the risk of Covid-19 and make sure nobody violates the rule. The dataset used in the process contains two classes, namely 'with mask' and 'without a mask'. Data pre-processing and splitting take place before the model training;then comparative analysis has been made in between the modified versions of the three transfer learning models, viz. DenseNet201, InceptionResnetV2, and ResNet101V2 to validate the modified model's efficiency. Results suggest that the revised version of DenseNet201 is very effective and can detect the events where face masks are not used at all or in an improper manner, with an accuracy of 98.90%. Various other metrics for performance are also being evaluated and reported in the paper. This model can work with images and videos/CCTV cameras using the help of OpenCV, TensorFlow, and Keras. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Seroprevalence of Immunoglobulin G Antibody among Contacts of COVID-19 Cases: A Study from India

Objective: To estimate COVID-19 seropositivity among contacts of cases and to compare the seropositivity among different types of contact for assessing the differential risk & transmission dynamics. Material and Methods: A large-scale population-based serosurvey was carried out among the general population of Ahmedabad during the second half of October 2020. The contacts of cases were selected based on the population proportion and enrolled as an additional category. The seropositivity among the contacts was estimated using the enzyme-linked immunosorbent assay and compared with different types of contact and available demographic factors. Results: As of October 2020, the seropositivity against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2) among contacts of cases in Ahmedabad was 26.0% [95% confidence interval 24.2–28.0]. The seropositivity among family contacts was significantly higher (28.8%) compared to other contacts (24.4%) (Z=2.19, p-value=0.028). This trend was seen across all age groups and both sexes. The seropositivity was higher among females (27.7%) compared to males (24.5%) but the difference was statistically not significant (Z=1.64, p-value=0.101). In terms of age groups, the positivity had an increasing trend up to 60 years but declined after that. Conclusion: A seropositivity of 26.0% among contacts indicates that a large proportion of contacts demonstrated Immunoglobulin-G antibodies. This highlights asymptomatic transmission and/or low sensitivity of the diagnostic tests. The current strategy for contact tracing and testing among contacts is justified based on the significantly higher seropositiviamong family contacts. © 2021 JHSMR.

Assessment of Knowledge of Undergraduate and Postgraduate Medical Students about Home-Isolation Guidelines of COVID-19

Background: COVID-19 patients can stay at home if isolated from others. The present study was carried out for assessment of knowledge of home-isolation (HI) guidelines. Method: Cross sectional descriptive study was done amongst 289 Undergraduate (UG) and Postgraduate (PG) medical students. The data collected through Google form were analysed and calculation of per-centages, proportion, mean, SD etc. was done. Results: Response rate was 61.49%. Mean age was 21.32 ± 2.27 years. Female to male ratio was 1.4:1. 93.42% and 6.57% were UG students and PG students respectively. 80.97% had performed COVID duty. There is no significant difference between boys and girls in performing COVID-19 duties. (z=1.46, p>0.05). 38.06% correctly defined HI, 50.52% knew when to discontinue HI, and 66.09% knew eligibility criteria for HI. 18.68% had knowledge about hand washing, 20.07% knew about COVID 19 helpline numbers. The mean score of the UG students was 6.84±2.17 whereas same as for PG students was 7.79±2.07. Conclusions: Students had higher level of correct knowledge about, when to seek medical attention for home isolated person;infection control practices followed by hand hygiene, use of mask by care giver. There is less knowledge about other aspects of home isolation. © 2021, MedSci Publications. All rights reserved.

From Farm to Fork: Early Impacts of COVID-19 on Food Supply Chain

COVID-19 pandemic has resulted in widespread global disruptions. While much is being discussed about the health and economic impacts, there has been a limited focus on the immediate food sector shocks and their related social implications in developing countries, especially when the farmer surveys cannot be conducted due to mobility restrictions in many countries. To overcome these challenges, this study uses news mining and content analysis of media articles published from February to April 2020, to assess the early impacts of the COVID-19 pandemic on the food supply chain and farm distress in India. It also presents the media perception of the impact of the pandemic and resulting policy measures using sentiment analysis, in addition to the cross-tabulation of results that show differential impacts across food supply chain components among different commodity groups and regions. The results show wide-scale impacts across different components of the food supply chain ranging from crop harvesting and processing, distribution and logistics to disruptions across food markets, as represented by 22, 11 and 30% of total articles, respectively. The impacts are also differentiated by commodity groups, with animal products having more trade and demand-side issues, logistic bottlenecks in fruits and vegetables and crops showing problems in labor availability and harvesting. Sentiment analysis of news items shows a spike in the negative sentiment immediately post the national lockdown, with relatively less negativity in subsequent weeks due to large-scale policy and community action. Sentiment classification along different indicators shows the highest negative sentiment for animal products (85%) in commodity groups, western states of India (78%) among different regions, and food supply (85%) and markets (83%) among supply chain components. Further, extreme weather analysis (using excess rainfall events) shows that farmers faced compound risks from the COVID-19 pandemic and extreme weather events in many parts of the country. The results highlight the importance of building resilient food systems, especially when the biotic and abiotic shocks are projected to increase globally due to many drivers including biodiversity loss and climate change.

Evaluation of large-scale rapid antigen testing of incoming passengers at a dynamic point of care setting carried out by dental students for COVID-19 screening - a field report

BACKGROUND: Assessment of the results of large-scale rapid antigen diagnostic (RAD) testing for detection of SARS-CoV-2 amongst incoming passengers was carried out by Ahmedabad Municipal Corporation (AMC) Dental College Students at the Central Railway Station of Ahmedabad city. We wanted to determine the sensitivity and specificity of RAD testing for detection of Covid-19 amongst passengers disembarking from scheduled trains arriving at the Central Railway Terminus of Ahmedabad city. METHODS: Under the campaign "Chase the Virus" launched by Ahmedabad Municipal Corporation (AMC), Interns & Final Year students of AMC Dental College were trained to carry out rapid antigen testing of scheduled trains running on special routes starting from 07/09/2020 to 05/10/2020.14 dental teams were deputed at a temporary testing facility formulated for day-to-day testing at the Central Station using the standalone Standard - Q Covid-19 Ag testing kit (SD Biosensor, South Korea). RESULTS: In total, 18901 travellers were tested in a span of 26 days out of which 324 tested positive with an overall percentage positivity of 1.71%. An average number of 727 (+or- 182) tests were performed with an overall sensitivity of 66.01% and specificity of 99.71%. CONCLUSIONS: In response to the growing Covid-19 pandemic and complexity of laboratory-based molecular tests, rapid antigen detection tests have proved to be efficient in the easier and faster diagnosis of the passengers in such point of care settings.

Serosurveillance among covid-19 cases in ahmedabad using sars-cov2 igg antibodies

Background: Serosurveillance study focusing on antibodies against SARS-CoV2 among the Covid19 cases can add value in the scientific knowledge & help in formulating valid predictions regarding immunity status in the post-covid period. Objectives: To estimate seropositivity among covid19 cases and to identify various factors affecting seropositivity. Methods: During second half of October 2020, a population based serosurvey on Covid19 cases was carried out in Ahmedabad. Covid-Kavach test kits were used and estimated seroprevalence was compared with available demographic and covid19 case related parameters to identify factors affecting seropositivity in the post-covid period. Simple proportions and Z-test were used as appropriate. Results: As on October 2020, the sero-positivity among Covid19 cases in Ahmedabad was 54.51% [95% Confidence Interval (CI) 52.14-56.86%]. Females have higher positivity (54.78%) as compared to males (54.30%) but the difference was statistically not significant (Z=0.19, P=0.84). Among children and elderly, the positivity is high and from young adults to elderly the seropositivity has an increasing trend. Severity of clinical illness and longer duration of hospitalization are associated with higher seropositivity. Conclusion: With 54.51% seropositivity among covid19 cases, it is clear that all the covid19 cases may not have developed IgG antibodies, have undetectable level or might have disappeared during the post-covid period. Comparison of seropositivity with age group and clinical case details clearly suggest close correlation with the severity of clinical symptoms. The seronegative cases indicate the need for further in-depth scientific research to identify the factors affecting immunity and to uncover the reasons behind the same. © 2021, Indian Association of Preventive and Social Medicine. All rights reserved.

A comparative study of different feature extraction techniques for identifying COVID-19 patients using chest X-rays images

The coronavirus (COVID-19) outbreak has been labeled as a pandemic with no assured vaccine and drug till now. Many medical trials are going on for finding treatment against this disease and some have achieved success but reaching out to all stakeholders is strenuous. A quick and proper identification through testing of a COVID-19 patient is equally important to prevent the spread of the virus to other healthy patients. Thus, a comparative study of different feature extraction techniques for identifying COVID-19 patients using chest X-rays images is done in this work. The combination of local binary patterns features extraction technique and gradient boosting classifier performs the best with 94.453% accuracy as compared to other approaches. So, this work will be of great help in the screening of COVID-19 and also contribute to the healthcare system to fight against it. © 2020 IEEE.

Evidence of community pharmacists' response preparedness during COVID-19 public health crisis: A cross-sectional study.

INTRODUCTION: Community pharmacists are often the first point of contact for the public, especially during pandemics. As outlined by the International Pharmaceutical Federation, community pharmacists have an important public health role during this Coronavirus Disease 2019 (COVID-19) public health emergency. We therefore investigated the current practices, response preparedness and professional development needs of community pharmacists in Qatar. METHODOLOGY: A descriptive cross-sectional online 38-item questionnaire-based survey constructed on evidence-based public health roles of pharmacists was conducted between 28 May and 18 June 2020. Questions related to current practices required responses on a 5-point Likert-type scale ranging from "always" to "never". The questionnaire was evaluated for validity and the reliability analysis showed a Cronbach's alpha coefficient of 0.921. RESULTS: The response (n = 311) rate for the survey was 34.2%. More than 75% of pharmacists "always" encouraged and practiced hygiene and social distancing measures. On the other hand, the proportion of pharmacists "always" involved in patient assessment, education or providing information related to COVID-19 and application of evidence-based protocol ranged from 32 to 73%. The vast majority (87-96%) of pharmacists indicated that they needed professional development related to COVID-19. Overall, 77% of pharmacists either "strongly agreed" or "agreed" that they have all the necessary COVID-19 related emergency response preparedness and training. Country from which pharmacists obtained their first degree, and the type of pharmacy where they practice influenced their overall perception toward emergency response preparedness. CONCLUSIONS: Community pharmacists in Qatar are willing to receive additional training related to COVID-19 public health crisis despite being prepared to engage with patients.