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With more than 23 million infections and more than 814,000 deaths worldwide, the coronavirus disease-2019 (COVID-19) pandemic is still far from over. Several classes of drugs including antivirals, antiretrovirals, anti-inflammatory, immunomodulatory, and antibiotics have been tried with varying levels of success. Still, there is lack of any specific therapy to deal with this infection. Although less than 30% of these patients require intensive care unit admission, morbidity and mortality in this subgroup of patients remain high. Hence, it becomes imperative to have general principles to guide intensivists managing these patients. However, as the literature emerges, these recommendations may change and hence, frequent updates may be required. [ABSTRACT FROM AUTHOR]

In a resource-limited country like India, rationing of scarce critical care resources might be required to ensure appropriate delivery of care to the critically ill patients suffering from COVID-19 infection. Most of these patients require critical care support because of respiratory failure or presence of multiorgan dysfunction syndrome. As there is no pharmacological therapy available, respiratory support in the form of supplemental oxygen, noninvasive ventilation, and invasive mechanical ventilation remains mainstay of care in intensive care units. As there is still dearth of direct evidence, most of the data are extrapolated from the experience gained from the management of general critical care patients. [ABSTRACT FROM AUTHOR]

Considering the prevailing situations, the mathematical modeling and dynamics of novel coronavirus (2019-nCoV) particularly in India are studied in this paper. The goal of this work is to create an effective SEIRS model to study about the epidemic. Four different SEIRS models are considered and solved in this paper using an efficient homotopy perturbation method. A clear picture of disease spreading can be obtained from the solutions derived using this method. We parametrized the model by considering the number of infection cases from 1 April 2020 to 30 June 2020. Finally, numerical analysis and graphical representations are provided to interpret the spread of virus. [ABSTRACT FROM AUTHOR]

The digitalization process has been increasing rapidly worldwide today. There is various technologies developed and continue developing tremendously in the world, such as mobile payment systems. Such type of emerging technologies has made a very significant transformation in people lives everywhere. Technologies such as mobile devices facilitate people to finish their work in less time and effort required usually. That is why, these innovations and advancements in technologies led people to be more inclined toward their use. Furthermore, in the current scenario, mobile payments have become an integral part of the daily lives of people due to the impact of the novel coronavirus (COVID-19) disease on society. The presence of mobile payment systems can be considered for years, but the use of mobile payment systems has increased in the current situation of the COVID-19 pandemic, which is the core basis of this research paper. However, the user's acceptance of mobile payment systems is still low due to some pros and cons of this technology which are examined in this paper by applying a hybrid machine learning model. We collected primary data through Google Form from the institute in the Meerut region and other sources from India with a total of 222 respondents. In this study, the data is processed and applied on to the machine learning models. Data analysis and findings of the research showed that the proposed ensemble of classifier algorithms outperforms other exiting machine models in terms of accuracy, precision, recall and F1-score. The research and findings will help the organizations have a clear and correct analysis of the scenario of the adoption of mobile payments in India and also design better mobile payment systems to curb the situation like the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Purpose: The novel coronavirus (COVID-19) leaves Indian business teetering on the edge of survival. This paper aims to set out to assess the impact of the pandemic shocks on the small and medium business segments in India. The research also explores the strategies that potentially take the segments back to recovery and growth. Design/methodology/approach: The findings draw on the perspectives of academic and business people, and the authors use linear and nonlinear regression modelling under three recovery scenarios to support our arguments. Findings: Evidence suggests that the shocks to business are manifold and the severity of most of the issues will aggravate as the recovery prolongs. Practical implications: The paper explains the rationale of realistic strategies and compares its effects across potent recoveries. The findings are useful for both academics and business and relates to the strategic decisions that would be taken by small and medium enterprises to expedite recovery from the crisis. Originality/value: The research is unique in surveying the academics and entrepreneurs about the impact of COVID-19 on Indian business. [ABSTRACT FROM AUTHOR]

The World Health Organization announced on March 11, 2020 that COVID-19 could become a pandemic. COVID-19 is a contagious disease caused by the coronavirus that causes severe acute respiratory syndrome (SARS-CoV-2). Viruses usually enter the body through the mouth or nose. The virus then enters the alveoli, which are small air sacs inside the lungs. Cough, fatigue, fever, shortness of breath or breathing difficulties, and loss of smell and taste are all symptoms of COVID-19. Anosmia, also known as smell blindness, is a condition in which the ability to detect one or more smells is lost. Olfaction uses chemoreceptors to create signals that are processed in the brain and form the sense of smell in anosmia. Anosmia is recognised as a COVID-19 symptom in many countries, and some have developed "smell tests" as potential screening tools. The first level of screening, which is currently used in India, is primarily based on temperature and can result in false positives and negatives (fever as a symptom has not yet been developed although infection). One of the methods for detecting COVID-19 is an intermediate level of screening based on assessing an olfactory function, depending on the usage. This paper provides an overview of COVID-19 and its effects on the human body, as well as an overview of anosmia and how it contributes to one of the symptoms of COVID-19. [ABSTRACT FROM AUTHOR]

Health-care providers or health-care workers (HCWs) are at higher risk of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection when compared to the general population. An early routine screening of both symptomatic and asymptomatic HCWs is essential to prevent transmission of infection and thus the nosocomial spread. The cumulative prevalence of SARS-CoV-2 infection among Indian HCWs is unknown. This systematic review was aimed to analyse the prevalence of SARS-Co-V2 disease (COVID-19) among Indian HCWs. Data were collected from a comprehensive computerised search in PubMed, Google Scholar, ScienceDirect, ResearchGate, Scopus and Web of Science using the terms 'Prevalence of COVID-19 among HCWs in India' and 'prevalence of SARS-CoV-2 among HCWs in India'. Results of original research papers and meta-analysis published were collected and data analysed. Results of seven studies on 31656 HCWs in India were pooled. Overall, average prevalence of COVID-19 among the HCWs was 12.3%. Majorities were frontline workers irrespective of the gender. Most of the cases were symptomatic, with cough and fever as major clinical presentations. Findings suggest that adequate organisation of clinical wards and personnel, appropriate personal protective equipment supply and training of all workers directly and repeatedly exposed to COVID-19 patients should be prioritised to decrease the risk of infection. Furthermore, the duty time of HCWs who works in COVID treating area should be minimised. [ABSTRACT FROM AUTHOR]

Background: COVID-19 caused by the SARS-COV-2; a novel corona virus is a highly contagious respiratory disease. Objective: The Corona Virus disease 2019 (COVID-19) caused by the SARS-COV-2,a novel corona virus known as severe acute respiratory syndrome is highly contagious respiratory disease, transmitted by respiratory route. There is no specific treatment for COVID-19 and there is a constant need for updating knowledge since the related facts are evolving on day-to-day basis. Knowledge, Attitude, and practice (KAP) study was conducted among the medical students of a tertiary care hospital to assess their Knowledge, Attitude and practices regarding COVID-19. As we never know how the novel virus may change its behaviour and pose a great public health problem to all in society where even the medical students may be one of the primary doctor and are provider. Methods: A total no of 258 medical students from 3rd and 4th semester batch of SCB Medical College & Hospital were included in the study. They were provided with the predesigned questionnaire and their responses were collected by online survey keeping in view the COVID situation and minimizing the risk of viral transmission by paper being exchanging hands. Results: Out of the 258 students 58% were from the 3rd semester and 42% from 4th semester, from them 99.22% do not have any previous training in COVID-19. Out of the 59.3% males and 40.7% females. 100% of students knew COVID-19 is a viral infection and transmitted by close contact with the infected person. About 96% knew that only patients with co morbid conditions progress to severe forms. Majority (96%) used mass media, Internet to update their knowledge 93% believed infected person should not donate blood while 88.7% were of the opinion the vaccination should not be given to pregnant ladies, Lactating mothers and children under 18 years of age. Majority (98%,) showed a positive response towards stringent lockdown, 94% gave the opinion that HCW should be immunized first with COVID Vaccination. Only 80% gave an optimistic response towards beneficial role of convalescent plasma therapy for managing moderately severe cases. Majority of medical students observed COVID appropriate behaviour that is to use masks (88%), sanitizer (94%) and observed social distancing (100%) supporting that the students showed expected levels of KAP regarding COVID-19. Conclusion: The results of our study showed good, expected levels of knowledge regarding various aspects of COVID-19. As it is a novel virus and new concept are emerging every day, there is need to educate the Health care workers and students by regular training programmes, seminars and webinars in order to fight with this dreadful illness. [ABSTRACT FROM AUTHOR]

A novel Corona virus disease 2019 (COVID-19) outbreak is declared as the international public health emergency concern by the World Health Organization in the month of March 2020. This viral disease invented from China in the month of December 2019 has previously caused havoc around the world, including India. In this paper, efficient mathematical models using Gustafson–Kessel fuzzy clustering approach for the transmission of the COVID-19 are developed by considering the actual reported cases in the state of Tamil Nadu, India. The results proved a good concord between the reported data and the estimated data given by the proposed models. Moreover, the developed models are also capable to predict the requirements of beds in hospitals on the month of August 2020 in Tamil Nadu, India. Also, this work suggests strictly implementing/extending the complete lockdown for at least 21 days in the month of August 2020 and immediate separation of infected cases are the positive steps to reduce the spread of novel corona virus in Tamil Nadu state, India. [ABSTRACT FROM AUTHOR]

The corona virus disease 2019 (COVID-19) pandemic, which originated in the city of Wuhan, China, has rapidly spread to various countries, with many cases having been reported. Some existing antiviral agents showed positive results to inhibit the infection and transmission of the novel corona virus 2019 (2019-nCoV) in vitro. Covaxin is India's first indigenous COVID-19 vaccine. In this paper, we introduce the Gourava and hyper-Gourava polynomials of a graph. We compute the Gourava and hyper-Gourava polynomials of some specific class of graphs. Further, we obtain the Gourava and hyper-Gourava polynomials of some chemical structures viz., chloroquine, hydroxychloroquine, remdesivir and theaflavin which were used in the treatment of COVID-19. The Gourava and hyper-Gourava indices are investigated for the aforesaid antiviral drugs using polynomial approach. The Indian Council of Medical Research and Bharat Biotech announced that Phase 3 results of covaxin, developed by them, have shown an interim vaccine efficacy of 81 percent. So, the results obtained may be useful for finding the design of new medicine for the treatment of COVID-19. [ABSTRACT FROM AUTHOR]

COVID -19 is causing plenty of deaths in India as well as globally and many of them are health care workers (HCWs). As per data given by IMA 744 MBBS doctors have been died due to Covid - 19 till 4 February 20213. As this disease transmitted between person to person by respiratory droplets hence mask hygiene is very important effective preventive measure for HCWs. In market due to high demand, much different type of masks is available with different specifications. Some of them are from Indian origin and many of them are procured from foreign. Many of them are not effective to safeguard health care workers against COVID 19 infection2. Hence this paper will discuss different country specific standards of masks in relation to SARS COV-2 as well as home based disinfection method of masks. In market many masks are available and most of them are sub-standard and making falsely claim of N95. Most of them are not able to protect Health Care Workers from the infection of SARS COV-2. Hence in this paper will examine different countries specific standard of mask with respect to size of SARS COV-2. US standard N95 masks will give desire level of protection against SARS COV-2. Conclusion: NIOSH certified N95 or N99 or N100 mask should be given priority over other counties N95 equivalent masks. Chinese masks GB2626-2006 are least recommended among all other countries N95 equivalent masks6. [ABSTRACT FROM AUTHOR]

This paper focuses on the spread of disinformation on novel coronavirus (COVID-19) and creating the larger phenomena of information disorder. It analyses an array of definitional meaning and disinformation on COVID-19, which has been identified and grounded with valid information by the fact-checkers. The study's aim is to explore and analyse the intents behind the circulation of misleading information (intended and unintended) on COVID-19. For the study, quantitative content analysis and qualitative discourse analysis methods were utilised to explore the extent of the misleading information on COVID-19. Further, in-depth interviews were conducted with factcheckers, media professionals, academicians, and a psychologist to understand the purpose of disinformation and its impact on society at large. The study's findings propose that fact-checking is a crucial method to identify fake/misleading information, which can be counter acted by accurate and verified information. This paper argues that holding journalists, fact-checkers, the Government, and the citizens' accountable, is necessary to counter the threat of disinformation about the pandemic. [ABSTRACT FROM AUTHOR]

Background: As a global pandemic, Covid-19 has aroused great concern and garnered research interest world-wide In India a growing number of related researches have been published in the last few months. Therefore, a bibliometric analysis of these publications may provide indication of current status and future research trends in the field. Methods: The India's literature about Covid-19 published during 2019-2021 were searched in the Scopus database using a well-defined search strategy. The following keywords "Covid 19" or "2019 novel coronavirus" or "coronavirus 2019" or "coronavirus disease 2019" or "2019-novel CoV" or "2019 ncov" or covid 2019 or covid19 or "corona virus 2019" or ncov-2019 or ncov2019 or "nCoV 2019" or 2019-ncov or covid-19 or "Severe acute respiratory syndrome coronavirus 2" or "SARS-CoV-2"were used in "Keyord" and "Title" (Title of articles) tags to reach the relevant publications. VOSviewer was applied to perform the bibliometric analysis of these articles. Results: The bibliometric analysis of India's literature on Covid-19 indicates that there were 10,233 indexed publications in Scopus database until April 2021. Of all these publications, 52.87% were original articles and 11.75% (1202) publications received external funding from more than 150 agencies and 27.41% (2805) involve international collaboration with more than 150 countries. USA contributed the largest share (38.47%) in India's international collaborative papers, followed by U.K. (22.89%), China (11.55%), Saudi Arabia (11.44), Australia (11.23%), etc. In the geographical distribution, Delhi tops the publication list (with 21.86% share), followed by Mumbai (7.30%), Chennai (7.27%), Pune (6.44%) and Kolkata (6.04%). Among population age groups, "Adults" accounts for the largest publication share (9.98%), followed by "Middle Aged" (5.07%), "Children" (3.65%), "Aged" (3.65%) and "Adolescents" (2.82%). "Treatment studies" among prominent topics, account for the largest publication share (34.12% share), followed by "Clinical Studies" (13.13%), "Epidemiology" (10.54%), "Imaging and Diagnostics" (9.64%), "Pathophysiology" (6.27%), and etc. The 1311 organizations and 3413 authors participated in India's research on Covid-19, of which the top 30 organizations and authors contributed 43.50% and 11.57% national publication share and 45.62% and 32.14% national citation share. AIIMS-New Delhi and PGIMER-Chandigarh were the most productive organizations (with 623 and 468 papers). IVRIBareilly (21.32 and 4.44) and IIT-New Delhi (12.37 and 2.58) were the most impactful organizations. V. Wiwanitkit and K. Dhama were the most productive authors (with 182 and. 107 papers). R. Sah (42.89 and 8.93) and A. Misra (41.93 and 8.74) were the most impactful authors. International Journal of Research in Pharmaceutical Sciences (270 papers) and Indian Journal of Ophthalmology (210 papers) were the most productive journals. Science of the Total Environment (43.98) and Asian Journal of Psychiatry (19.19) were the most impactful journals. Conclusion: The paper provides a deeper understanding of the current Covid-19 research milieu in India, by identifying key players (and their collaboration linkages) and key sub-fields, while highlighting potential patterns that could assist future researchers in their scientific pursuits. [ABSTRACT FROM AUTHOR]

The world is in great chaotic condition due to the outbreak of COVID-19 caused by a novel coronavirus. People are facing havoc in every corner of the world. As it is an actual novel virus, people search everywhere on the internet and other platforms to know much about this lethal virus. This paper examines various aspects of informationseeking behavior and pattern among ordinary people in India through online mode. The data were collected from August to November 2020. This paper also seeks to identify different areas of information need among common people and their problems while searching for desired information. The primary objectives of the paper include examining the users’ activeness towards social media usage, identifying the most preferred information sources by users, and investigating different purposes for seeking information related to COVID-19 by users. [ABSTRACT FROM AUTHOR]

Karur, one of the oldest towns in Tamil Nadu, a southern state in India, embedded with its rich cultural history and heritage of over more than 2000 years can be considered a key textile hub in present times. Being perennially busy with home furnishings and garment exports, like any other "Textile" town of India or other textile players of the world, Karur was pushed into lockdown one after another from March 2020 for a few undecided months owing to the pandemic outbreak of the disease Covid-19 with a new class of corona virus, known as SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) being responsible for the occurrence of this disease. With uncertainty and a lack of clarity looming over their heads, many owners with the backing of their employees of the textile firms and industries jumpstarted their lives trying their best in beating the odds laid on themselves in quite successful ways backed with technical innovations. Though it happened for few, it didn't realize for some. This paper attempts to track and research on some of the life stories of achievement and the unprecedented misery few were suddenly pushed into. While this town's success stories as a meticulous process of change in its people's mindset in desperate times toward themselves and those around can be studied to be implemented as a role model for other towns, the future lying in its unpredictability can never be ascertained thereby only making the successful solutions of those a base study of learning for the next. [ABSTRACT FROM AUTHOR]

The novel coronavirus 2019 (COVID-19) disease is a pandemic which affects thousands of people throughout the world. It has rapidly spread throughout India since the first case in India was reported on 30 January 2020. The official report says that totally 4, 11,773 cases are positive, 2, 28,307 recovered, and the country reported 12,948 deaths as of 21 June 2020. Vaccination is the only way to prevent the spreading of COVID-19 disease. Due to various reasons, there is vaccine hesitancy across many people. Hence, the Indian government has the solution to avoid the spread of the disease by instructing their citizens to maintain social distancing, wearing masks, avoiding crowds, and cleaning your hands. Moreover, lots of poverty cases are reported due to social distancing, and hence, both the center government and the respective state governments decide to issue relief funds to all its citizens. The government is unable to maintain social distancing during the relief schemes as the population is huge and available support staffs are less. In this paper, the proposed algorithm makes use of graph theory to schedule the timing of the relief funds so that with the available support staff, the government would able to implement its relief scheme while maintaining social distancing. Furthermore, we have used LSTM deep learning model to predict the spread rate and analyze the daily positive COVID cases. [ABSTRACT FROM AUTHOR]

At this moment in time, an outbreak of COVID-19 is transmitting from human to human. Different parts have different quality of life (e.g., India compared to Russia), which implies the impact varies in each part of the world. Although clinical vaccines are available to cure, the question is how to minimize the spread without considering the vaccine. In this paper, via a mathematical model, the transmission dynamics of novel coronavirus with quarantine and isolation facilities have been proposed. The examination of the proposed model is set in motion with the boundedness and positivity of the solution, sole disease-free equilibrium, and local stability. Then, the condition for the existence of sole endemic equilibrium and its local stability has established. In addition, the global stability of the endemic equilibrium for a special case has been investigated. Further, it has shown that the system undergoes a transcritical bifurcation. A threshold analysis has also performed to examine the effect of quarantine on transmission dynamics. Lastly, numerical simulations are giving support to theoretical results. [ABSTRACT FROM AUTHOR]

Novel coronavirus has altered the socio-economic condition of the whole world through its devastating effects on the human population. Mathematical models and computation techniques may play an important role in understanding this epidemic and contribute a lot in policy making to control the infection in a more systematic and effective way. In this paper, we have proposed a deterministic mathematical model for the Covid-19 pandemic taking into account the different epidemiological status of individuals of a given geographical region and analyzed it with respect to the basic reproduction number. Uncertainty is obvious in the case of a growing epidemic and it multiplies if the disease etiology is unknown. Taking into account the uncertainty in the epidemiological parameters, we extended the deterministic system into a stochastic system through random parameter perturbations in three epidemiological parameters. Analyzing the model, we determined the disease persistence and eradication conditions. The asymptotic behavior of the stochastic solution around the coexistence equilibrium of the deterministic model was also presented. As a case study, we considered the Covid-19 pandemic of India and estimated the model parameters from the epidemic data. We demonstrated different analytical results and predicted the course of the epidemic. Our simulation results indicate that the epidemic in India may continue up to third week of July 2021 and the cumulative confirmed Covid-19 cases may vary from 12.13 × 10 6 to 13.41 × 10 6. Such results may be useful from management and policy development viewpoints. [ABSTRACT FROM AUTHOR]

Novel Coronavirus (COVID-19) has become one of the deadliest pandemics that has affected almost all the nations in the world. Lockdown and systematic re-opening of shopping malls, offices, etc. is still one of the major weapons against this virus. However, the government and medical agencies take long time to reopen the places due to risks involved in this deadly virus. The delay to reopen places has resulted in sharp decline in the growth of economy. In this paper a current context aware framework is proposed which uses multiple inputs for a specific region to decide whether to open it or not. The proposed framework used series of deep neural network models to generate recommendations specific to a particular region. Most of the inputs are real-time and readily available with the government. The main aim is to develop framework which can be used in any kind of pandemic even in small region to easily contain it. However, it has been tested using opensource data available for COVID-19. Data was crawled from web for 22 districts of Haryana state of India. Experimental result proved the efficiency of proposed framework. [ABSTRACT FROM AUTHOR]

• Prophet Model provides understanding of the number of people affected daily by this disease. • The imposed interventions are reflected by five significant changepoints detected by the model in the growth curve of India. • The model forecasts90 days future growth trend and finds the peak time for all the six countries and six states of India. • The model has achieved around 85% MAPE for all the six countries and the six states of India. Covid-19 disease caused by novel coronavirus (SARS-CoV-2) is a highly contagious epidemic that originated in Wuhan, Hubei Province of China in late December 2019. World Health Organization (WHO) declared Covid-19 as a pandemic on 12th March 2020. Researchers and policy makers are designing strategies to control the pandemic in order to minimize its impact on human health and economy round the clock. The SARS-CoV-2 virus transmits mostly through respiratory droplets and through contaminated surfacesin human body.Securing an appropriate level of safety during the pandemic situation is a highly problematic issue which resulted from the transportation sector which has been hit hard by COVID-19. This paper focuses on developing an intelligent computing model for forecasting the outbreak of COVID-19. The Facebook Prophet model predicts 90 days future values including the peak date of the confirmed cases of COVID-19 for six worst hit countries of the world including India and six high incidence states of India. The model also identifies five significant changepoints in the growth curve of confirmed cases of India which indicate the impact of the interventions imposed by Government of India on the growth rate of the infection. The goodness-of-fit of the model measures 85% MAPE for all six countries and all six states of India. The above computational analysis may be able to throw some light on planning and management of healthcare system and infrastructure. [Display omitted] [ABSTRACT FROM AUTHOR]

The Novel Coronavirus which emerged in India on January/30/2020 has become a catastrophe to the country on the basis of health and economy. Due to rapid variations in the transmission of COVID-19, an accurate prediction to determine the long term effects is infeasible. This paper has introduced a nonlinear mathematical model to interpret the transmission dynamics of COVID-19 infection along with providing vaccination in the precedence. To minimize the level of infection and treatment burden, the optimal control strategies are carried out by using the Pontryagin's Maximum Principle. The data validation has been done by correlating the estimated number of infectives with the real data of India for the month of March/2021. Corresponding to the model, the basic reproduction number R 0 is introduced to understand the transmission dynamics of COVID-19. To justify the significance of parameters we determined the sensitivity analysis of R 0 using the parameters value. In the numerical simulations, we concluded that reducing R 0 below unity is not sufficient enough to eradicate the COVID-19 disease and thus, it is required to increase the vaccination rate and its efficacy by motivating individuals to take precautionary measures. [ABSTRACT FROM AUTHOR]

Background: The world has historically faced and recovered from many pandemics. The most recent global pandemic that the whole world is facing is Novel Coronavirus - Covid-19. The objective of current study is to compare and forecast COVID-19 trends for Pakistan and India. Methods: The data set for this research is obtained from the World Health Organization (WHO) online repository (https://covid19.who.int/). The time period we have considered since the first corona related case and death were observed in both countries. This research paper analyzes corona related cases and deaths in Pakistan and India till 28th February 2021, a total of 578,797 cases in Pakistan and 11,096,731 cases in India has been confirmed including 128,37 and 1,570,51 deaths respectively. The Auto-Regressive Integrated Moving Average (ARIMA) model is used to forecast the variables cumulative cases and deaths. It is simple to use and more predictive than any other regression model. Results: Based on the current trend, the forecast graph reveals that the number of cumulative corona cases could reach 999,767 in Pakistan and 16,481,122 in India up to 31st December 2021. Conclusion: This research found that corona related cumulative cases and deaths are on the rise in both countries. The pandemic situation in India is worse than in Pakistan nevertheless both countries are at high risk. There is a sudden increasing pattern in the number of corona related cases in both countries. Both governments must impose effective policies to control this pandemic. [ABSTRACT FROM AUTHOR]

Background: Many popular disease transmission models have helped nations respond to the COVID-19 pandemic by informing decisions about pandemic planning, resource allocation, implementation of social distancing measures, lockdowns, and other non-pharmaceutical interventions. We study how five epidemiological models forecast and assess the course of the pandemic in India: a baseline curve-fitting model, an extended SIR (eSIR) model, two extended SEIR (SAPHIRE and SEIR-fansy) models, and a semi-mechanistic Bayesian hierarchical model (ICM).Methods: Using COVID-19 case-recovery-death count data reported in India from March 15 to October 15 to train the models, we generate predictions from each of the five models from October 16 to December 31. To compare prediction accuracy with respect to reported cumulative and active case counts and reported cumulative death counts, we compute the symmetric mean absolute prediction error (SMAPE) for each of the five models. For reported cumulative cases and deaths, we compute Pearson's and Lin's correlation coefficients to investigate how well the projected and observed reported counts agree. We also present underreporting factors when available, and comment on uncertainty of projections from each model.Results: For active case counts, SMAPE values are 35.14% (SEIR-fansy) and 37.96% (eSIR). For cumulative case counts, SMAPE values are 6.89% (baseline), 6.59% (eSIR), 2.25% (SAPHIRE) and 2.29% (SEIR-fansy). For cumulative death counts, the SMAPE values are 4.74% (SEIR-fansy), 8.94% (eSIR) and 0.77% (ICM). Three models (SAPHIRE, SEIR-fansy and ICM) return total (sum of reported and unreported) cumulative case counts as well. We compute underreporting factors as of October 31 and note that for cumulative cases, the SEIR-fansy model yields an underreporting factor of 7.25 and ICM model yields 4.54 for the same quantity. For total (sum of reported and unreported) cumulative deaths the SEIR-fansy model reports an underreporting factor of 2.97. On October 31, we observe 8.18 million cumulative reported cases, while the projections (in millions) from the baseline model are 8.71 (95% credible interval: 8.63-8.80), while eSIR yields 8.35 (7.19-9.60), SAPHIRE returns 8.17 (7.90-8.52) and SEIR-fansy projects 8.51 (8.18-8.85) million cases. Cumulative case projections from the eSIR model have the highest uncertainty in terms of width of 95% credible intervals, followed by those from SAPHIRE, the baseline model and finally SEIR-fansy.Conclusions: In this comparative paper, we describe five different models used to study the transmission dynamics of the SARS-Cov-2 virus in India. While simulation studies are the only gold standard way to compare the accuracy of the models, here we were uniquely poised to compare the projected case-counts against observed data on a test period. The largest variability across models is observed in predicting the "total" number of infections including reported and unreported cases (on which we have no validation data). The degree of under-reporting has been a major concern in India and is characterized in this report. Overall, the SEIR-fansy model appeared to be a good choice with publicly available R-package and desired flexibility plus accuracy. [ABSTRACT FROM AUTHOR]

The outbreak Coronavirus disease 2019 (COVID-19) is a respiratory tract infection caused by a highly contagious and lethal beta coronavirus SARS-CoV-2, which has spread fast to encroach the entire globe and hence declare pandemic. Pregnancy alters body physiology and immune systems, can have worse effects of some respiratory infections and due to limited research and published data we still are in dilemma of appropriate management guidelines This article covers the updated guidelines for infection prevention and control (IPC), screening, sampling, antenatal visit schedules, risk scoring, triaging, supportive care, delivery, postpartum care and care of the newborn. This article aims to provide up-to-date information as per recent guidelines of various association which would serve as guidance in managing pregnant women and newborn with suspected or confirmed COVID-19. All the published papers till date, NCPRE, WHO Interim guidelines, RCOG, FOGS GCPRI, Medical Council of India, ICMR, MOFHW, CDC, ACOG guidelines are referred to compile this article to reach to a conclusion of evidence based management of pregnant ladies during COVID-19 pandemic. This article covers the not only infection prevention and control (IPC) guidelines, but also screening and sampling guidelines, antenatal visit schedules, risk scoring, triaging but also in-patient supportive care, delivery, postpartum care and care of the newborn. Data are very limited and hence very difficult to accurately define clinical management strategies and needs to be constantly updated. [ABSTRACT FROM AUTHOR]

Included here are some cases that highlight exceptional behaviour under the novel coronavirus (CV) pandemic that cuts across religious boundaries. The Christian cases were drawn from the United States and South Korea; Islamic cases were drawn both from India and Iran; and the Hindu and Sikh cases were highlighted from India. Of these, notably, Iran is a declared theocracy, whereas the United States and India are arguably contexts of rising Christian and Hindu theocracies. We are familiar with the evidence of the positive role of religions in society. This paper brings together exceptional cases where irrationality, control and selfishness trump wisdom and altruism. The evidence highlighted here shows that people are capable of suspending reason and behaving with a motive inspired by faith (often tarnished by the state's intervention), even when it is clear there might be serious personal and social costs involved. [ABSTRACT FROM AUTHOR]

India's first case of novel coronavirus (COVID-2019) detected on January 30, 2020, in the State of Kerala, and the government switched to alert mode. As the number of confirmed COVID-19 positive cases discerned an increase, the government clamped Epidemic Diseases Act, 1897 on March 11, 2020, by mandating the norm of social distancing and the voluntary public curfew in the country. The nation-wide Lockdowns-I (March 25, 2020, to April 14 2020), II (April 15, 2020, to May 3 2020), and III (May 4, 2020, to May 17, 2020) justified on the ground of Sections 6, 10, 38 and 72 of the Disaster Management Act, 2005. During the lockdown period, the protection of medical and paramedical forces has been a central concern in controlling novel COVID-19 pandemic in India. Therefore, the State also invoked quarantine disobedience under sections 188, 269, 270, 271 of Indian Penal Code, 1860 on command and control theory but unable to control the riotous situation working against medical care personnel. Realizing this exigency, the President under Article 123 of the Constitution of India, 1950 promulgated the Epidemic Diseases (Amendment) Ordinance, 2020. To deal with the miscreants effectively, the Ordinance declares 'act of violence' cognizable and non-bailable with high deterrent value. The paper contextualizes the Epidemic Diseases (Amendment) Ordinance, 2020 in controlling horrendous Epidemic-Pandemic Syndrome of COVID-19 in India in historical and contemporary perspective. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 is a type of coronavirus that has caused the pandemic known as the Coronavirus Disease of 2019, or COVID-19. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viral diseases, there is a distinct "asymptomatic" group A , which does not show any symptoms, but can nevertheless infect others, at the same rate as infected symptomatic patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stillianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabililty of the SAIR model, both without and with vital dynamics. Then we develop compartmental SAIR models to cater to the migration of population across geographic regions, and once again establish global asymptotic stability. Next, we go beyond long-term asymptotic analysis and present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and demonstrate that the predicted trajectories of the disease closely match actual data. We show that "herd immunity" (defined as the time when the number of infected persons is maximum) can be achieved when the total of infected, symptomatic and asymptomatic persons is as low as 25% of the population. Previous estimates are typically 50% or higher. We also conclude that "lockdown" as a way of greatly reducing inter-personal contact has been very effective in checking the progress of the disease. [ABSTRACT FROM AUTHOR]

Cataract is the second leading cause of preventable blindness on the globe. Several programs across the country have been running efficiently to increase the cataract surgical rates and decrease blindness due to cataract. The current COVID-19 pandemic has led to a complete halt of these programs and thus accumulating all the elective cataract procedures. At present with the better understanding of the safety precautions among the health care workers and general population the Government of India (GoI) has given clearance for functioning of eye care facilities. In order to facilitate smooth functioning of every clinic, in this paper, we prepared preferred practice pattern based on consensus discussions between leading ophthalmologists in India including representatives from major governmental and private institutions as well as the All India Ophthalmological Society leadership. These guidelines will be applicable to all practice settings including tertiary institutions, corporate and group practices and individual eye clinics. The guidelines include triage, use of personal protective equipment, precautions to be taken in the OPD and operating room as well for elective cataract screening and surgery. These guidelines have been prepared based on current situation but are expected to evolve over a period of time based on the ongoing pandemic and guidelines from GoI. [ABSTRACT FROM AUTHOR]

Novel Coronavirus (COVID 19) has usurped human peace and mobility. Since December 2019, the virus has claimed the lives of 87,816 people across the globe as of April 9, 2020 with India reporting a high case fatality of 3.4%. Among the vulnerable population, elderly people, and patients with comorbidities such as diabetes, chronic life-threatening illnesses, such as COPD and advanced malignancies are susceptible to COVID-19 infection and may have poor clinical outcomes. Considering the imbalance in demand and supply of healthcare resources, initiating palliative care will be essential to alleviate the suffering of such patients. The current paper deliberates on the following aspects of palliative care delivery in the community; the need for palliative care in a pandemic crisis, the role of telemedicine in palliative care delivery in the community, the vital role of a family physician in providing primary palliative care in the community and a "wholistic" community palliative care package to serve the needy in the community. [ABSTRACT FROM AUTHOR]

COVID-19 is more virulent and challenging to human life. In India, the Ministry of AYUSH recommended some strategies through Siddha, homeopathy, and other methods to effectively manage COVID-19 (Guidelines for AYUSH Clinical Studies in COVID-19, 2020). Kabasura Kudineer and homeopathy medicines are in use for the prevention and treatment of COVID-19 infection; however, the mechanism of action is less explored. This study aims to understand the antagonist activity of natural compounds found in Kabasura Kudineer and homeopathy medicines against the SARS-CoV-2 using computational methods. Potential compounds were screened against NSP-12, NSP-13, NSP-14, NSP-15, main protease, and spike proteins. Structure-based virtual screening results shows that, out of 14,682 Kabasura Kudineer compounds, the 250395, 129677029, 44259583, 44259584, and 88583189 compounds and, out of 3,112 homeopathy compounds, the 3802778, 320361, 5315832, 14590080, and 74029795 compounds have good scoring function against the SARS-CoV-2 structural and nonstructural proteins. As a result of docking, homeopathy compounds have a docking score ranging from −5.636 to 13.631 kcal/mol, while Kabasura Kudineer compounds have a docking score varying from −8.290 to −13.759 kcal/mol. It has been found that the selected compounds bind well to the active site of SARS-CoV-2 proteins and form hydrogen bonds. The molecular dynamics simulation study shows that the selected compounds have maintained stable conformation in the simulation period and interact with the target. This study supports the antagonist activity of natural compounds from Kabasura Kudineer and homeopathy against SARS-CoV-2's structural and nonstructural proteins. [ABSTRACT FROM AUTHOR]