To check the effect of bhagottar gutika and abhyanga in post covid respiratory distress

Gender differences in COVID-19 knowledge, risk perception, and public stigma among the general community: Findings from a nationwide cross-sectional study in India.

Introduction: Individual and community characteristics predictive of knowledge, perception, and attitude on COVID-19, specifically on gender, have not been adequately explored. Objective: To examine the gender differences in COVID-19 knowledge, self-risk perception and public stigma among the general community and to understand other socio-demographic factors which were predictive of them. Method: A nationally representative cross-sectional multi-centric survey was conducted among adult individuals(≥18 yrs) from the community member (N = 1978) from six states and one union territory of India between August 2020 to February 2021. The participants were selected using systematic random sampling. The data were collected telephonically using pilot-tested structured questionnaires and were analyzed using STATA. Gender-segregated multivariable analysis was conducted to identify statistically significant predictors (p < 0.05) of COVID-19-related knowledge, risk perception, and public stigma in the community. Results: Study identified significant differences between males and females in their self-risk perception (22.0% & 18.2% respectively) and stigmatizing attitude (55.3% & 47.1% respectively). Highly educated males and females had higher odds of having COVID-19 knowledge (aOR: 16.83: p < 0.05) than illiterates. Highly educated women had higher odds of having self-risk perception (aOR: 2.6; p < 0.05) but lower public stigma [aOR: 0.57; p < 0.05]. Male rural residents had lower odds of having self-risk perception and knowledge [aOR: 0.55; p < 0.05 & aOR: 0.72; p < 0.05] and female rural residents had higher odds of having public stigma [aOR: 1.36; p < 0.05]. Conclusion: Our study findings suggest the importance of considering thegender differentials and their background, education status and residential status in designing effective interventions to improve knowledge and reduce risk perception and stigma in the community about COVID-19.

Challenges in Accessing and Delivering Maternal and Child Health Services during the COVID-19 Pandemic: A Cross-Sectional Rapid Survey from Six States of India.

BACKGROUND/OBJECTIVES: Globally, the COVID-19 pandemic and its prevention and control policies have impacted maternal and child health (MCH) services. This study documents the challenges faced by patients in accessing MCH services, and the experiences of health care providers in delivering those services during the COVID-19 outbreak, explicitly focusing on the lockdown period in India. METHODS: A cross-sectional study (rapid survey) was conducted in 18 districts from 6 states of India during March to June, 2020. The sample size included 540 MCH patients, 18 gynaecologists, 18 paediatricians, 18 district immunisation officers and 108 frontline health workers. Bivariate analysis and multivariable analysis were used to assess the association between sociodemographic characteristics, and challenges faced by the patients. RESULTS: More than one-third of patients (n = 212; 39%) reported that accessing MCH services was a challenge during the lockdown period, with major challenges being transportation-related difficulties (n = 99; 46%) unavailability of hospital-based services (n = 54; 23%) and interrupted outreach health services (n = 39; 18.4%). The supply-side challenges mainly included lack of infrastructural preparedness for outbreak situations, and a shortage of human resources. CONCLUSIONS/RECOMMENDATIONS: A holistic approach is required that focuses on both preparedness and response to the outbreak, as well reassignment and reinforcement of health care professionals to continue catering to and maintaining essential MCH services during the pandemic.

To stay put or migrate: Dynamics of migration in a village in Jharkhand, India

Through a study of a village in Jharkhand, India, the paper maps the migration process of workers due to the structural transformation of the rural area. The nature of transformation in Jharkhand has led to a process of migration as a temporary strategy. This paper illustrates the processes wherein the socio-economic dynamic of the village is reflected in different migration strategies which take the form of identity and assignment-based networks. The paper develops a rudimentary typology of migrant workers to map the differential effects of reverse migration. Reverse migration due to the COVID-19 pandemic has resulted in lost skills, lost opportunities and increased competition which has affected workers in different networks and identity groups to varying extents. The breakdown of networks and their revival in the subsequent period led to the solidification of the identity-based networks, which is a reflection of the hierarchy in the village. The paper argues that reverse migration and the subsequent revival of the migration networks are taking on an exclusionary form that affect an already vulnerable population disproportionately.

Development & validation of scales to assess stigma related to COVID-19 in India.

Background & objectives: COVID-19 pandemic has triggered social stigma towards individuals affected and their families. This study describes the process undertaken for the development and validation of scales to assess stigmatizing attitudes and experiences among COVID-19 and non-COVID-19 participants from the community. Methods: COVID-19 Stigma Scale and Community COVID-19 Stigma Scale constituting 13 and six items, respectively, were developed based on review of literature and news reports, expert committee evaluation and participants' interviews through telephone for a multicentric study in India. For content validity, 61 (30 COVID-19-recovered and 31 non-COVID-19 participants from the community) were recruited. Test-retest reliability of the scales was assessed among 99 participants (41 COVID-19 recovered and 58 non-COVID-19). Participants were administered the scale at two-time points after a gap of 7-12 days. Cronbach's alpha, overall percentage agreement and kappa statistics were used to assess internal consistency and test-retest reliability. Results: Items in the scales were relevant and comprehensible. Both the scales had Cronbach's α above 0.6 indicating moderate-to-good internal consistency. Test-retest reliability assessed using kappa statistics indicated that for the COVID-19 Stigma Scale, seven items had a moderate agreement (0.4-0.6). For the Community COVID-19 Stigma Scale, four items had a moderate agreement. Interpretation & conclusions: Validity and reliability of the two stigma scales indicated that the scales were comprehensible and had moderate internal consistency. These scales could be used to assess COVID-19 stigma and help in the development of appropriate stigma reduction interventions for COVID-19 infected, and mitigation of stigmatizing attitudes in the community.

Experiencing the COVID-19 pandemic as a healthcare provider in rural Dhanbad, India: An interpretative phenomenological analysis.

BACKGROUND: The COVID-19 pandemic is causing widespread morbidity and mortality. It has led to a myriad of mental health problems, particularly in health care providers (HCPs). To strengthen the fight against COVID-19, it is essential to investigate the mental health challenges being faced by the HCPs, their emotional responses, and coping strategies. OBJECTIVES: We aimed to explore the lived experiences of frontline HCPs in rural India during the peak of the second wave of the COVID-19 pandemic. METHODS: Through purposive heterogenous snowball sampling, five HCPs in rural Dhanbad were recruited and one-on-one double-blind unstructured interviews were conducted. The interviews were transcribed and master themes and subthemes were extracted by interpretative phenomenological analysis. RESULTS: Six master themes and 23 subthemes were identified. Our findings demonstrate that the participants were under mental duress due to heavy workloads, fear of getting infected and transmitting the infection, urban-rural disparities in access to medical supplies and peer support, and negative social perception of HCPs during the pandemic. Most HCPs have not yet processed the psychological effects of being at the frontlines of the COVID-19 pandemic in a resource-poor setting; however, spirituality seems to be an important coping mechanism that helps them get through the day. CONCLUSIONS: This study is unique in the sense that not many studies have been conducted to evaluate the psychological issues of Indian HCPs during this pandemic. Much less is known about the mental health of HCPs in rural settings. Moreover, novel findings such as negative social perception of HCPs during the pandemic and HCPs resorting to spirituality as a coping strategy against stress, open a plethora of research opportunities wherein the results of this qualitative study, along with the existing literature and findings of future quantitative studies, can establish better understanding of the impact of the pandemic on HCPs.

Analysis of predictors and outcomes of COVID-19 patients requiring ICU admission from COVID 19 (preprint)

BackgroundSevere Corona virus disease (COVID-19) is associated with high mortality. Although single centre intensive care units (ICU) have reported clinical characteristics and outcomes, no large scale multicentric study from India has been published. The present retrospective, multi-centre study was aimed to describe the predictors and outcomes of COVID-19 patients requiring ICU admission from COVID-19 Registry of Indian council of Medical Research (ICMR), India.MethodsProspectively collected data from multiple participating institutions was entered in the electronic National Clinical Registry of COVID 19. We enrolled patients aged>18 years with COVID-19 pneumonia requiring ICU admission between March 2020 and August 2021. Exclusion criteria were negative RT PCR, death within 24 hours of ICU admission, or patients with incomplete data in the registry Their demographic characteristics, laboratory variables, ICU severity indices, treatment strategies and outcomes were analysed.ResultsA total of 5865 patients, with mean age 56±15 years, with 3840/5865 (65.4%) men, were enrolled in the ICMR registry.. Overall mortality was 2535/5865 (43.5%). Non-survivors were older than survivors (58.2±15.4 years vs 53.6 ±14.7 years; P=0.001). Non-survivors had multiple comorbidities (n=1951, 52.9%) with hypertension (47.2%) and diabetes (45.6%) being the most common, higher creatinine (1.6 ± P=0.001, high D-dimer (1.56 vs 1.37, P=0.001), higher CT severity index (16.8±5.2 vs 13.5 ±5.47 ) compared to  survivors. Non survivors had longer hospital and ICU stay (P=0.001). On multivariate regression analysis, high NLR (HR 1.017, 95% CI 1.005- 1.029, P=0.001), high CRP (HR 1.008, 95% CI 1.006- 1.010, P=0.001), high D dimer ((HR 1.089, 95% CI 1.065- 1.113, P=0.001) were associated with mechanical ventilation while younger age, (HR 0.974, CI 0.965-0.983, p=0.001), high D dimer (HR-1.014, CI 1.001-1.027, P=0.035) and use of prophylactic LMWH (HR 0.647, CI 0.527-0.794, p=0.001) were independently associated with mortality. ConclusionIn this large retrospective study of 5865 critically ill COVID 19 patients admitted to ICU, overall mortality was 2535/5865 (43.5%). Age, high D dimer, CT Severity score and use of prophylactic LMWH were independently associated with mortality. 

COVID-19 Vaccination Effect on Stock Market and Death Rate in India

The COVID-19 epidemic has brought attention to the vulnerability of new illnesses, and immunization remains a viable option for resuming normal life. This paper examines the influence of COVID-19 vaccination on the death rate and the performance of stock market in India. For this study, COVID-19 vaccination and death rate data is gathered from the Ministry of Health and Family Welfare (MoHFW) portal, and the data for the stock index is taken from the Bombay Stock Exchange (BSE), India. In order to achieve a precise representation of feature significance and distribution, EDA (Exploratory Data Analysis) is utilized in this study. The impact of COVID-19 immunization on the mortality rate and stock market index is investigated using both statistical analysis and Machine Learning Regression-based models. The models are remarkably accurate in reproducing actual result. The empirical study suggests that vaccination has a strong positive impact on the stock market and reducing the death rate. Furthermore, the policies recommended by government and monetary authorities coupled with COVID-19 vaccine supported the stock market recovery in pandemic.

Impact of novel microbial secondary metabolites on the pharma industry.

Microorganisms are remarkable producers of a wide diversity of natural products that significantly improve human health and well-being. Currently, these natural products comprise half of all the pharmaceuticals on the market. After the discovery of penicillin by Alexander Fleming 85 years ago, the search for and study of antibiotics began to gain relevance as drugs. Since then, antibiotics have played a valuable role in treating infectious diseases and have saved many human lives. New molecules with anticancer, hypocholesterolemic, and immunosuppressive activity have now been introduced to treat other relevant diseases. Smaller biotechnology companies and academic laboratories generate novel antibiotics and other secondary metabolites that big pharmaceutical companies no longer develop. The purpose of this review is to illustrate some of the recent developments and to show the potential that some modern technologies like metagenomics and genome mining offer for the discovery and development of new molecules, with different functions like therapeutic alternatives needed to overcome current severe problems, such as the SARS-CoV-2 pandemic, antibiotic resistance, and other emerging diseases. KEY POINTS: • Novel alternatives for the treatment of infections caused by bacteria, fungi, and viruses. • Second wave of efforts of microbial origin against SARS-CoV-2 and related variants. • Microbial drugs used in clinical practice as hypocholesterolemic agents, immunosuppressants, and anticancer therapy.

Understanding the protective roles of Indian joint families for children during the early phase of the COVID-19 pandemic (preprint)

The COVID-19 is exerting deleterious impacts on children. We intend to understand the protective roles of Indian joint families for the perceived life outcomes of children (9-12 years) during the early phase of the current pandemic. The qualitative study revealed six themes: perceived distress, the multiplicity of relationships, harmonious relationships, involvement in household activities, facilitating role of the elders, and collective values and practices. The uncertainty and fear enhanced the perceived distress of the family members and concerns for children. The abundant supportive relational resources, involvement in household activities, warmth, optimism and cooperation of the elderly and interdependence and religious practices were the resources described to protect the children from the pandemic’s ill-effects. Indian joint families adhere to collectivistic values which may have facilitated more support, cooperation, care, interdependence, discipline, cultural knowledge, and conflict resolution mechanisms. Integrity, emotional stability and care of the elderly may have significant protective forces. 

Subnational mortality estimates for India in 2019: a baseline for evaluating excess deaths due to the COVID-19 pandemic.

BACKGROUND: Estimates of excess mortality are required to assess and compare the impact of the COVID-19 pandemic across populations. For India, reliable baseline prepandemic mortality patterns at national and subnational level are necessary for such assessments. However, available data from the Civil Registration System (CRS) is affected by incompleteness of death recording that varies by sex, age and location. METHODS: Under-reporting of CRS 2019 deaths was assessed for three age groups (< 5 years, 15-59 years and ≥60 years) at subnational level, through comparison with age-specific death rates from alternate sources. Age-specific corrections for under-reporting were applied to derive adjusted death counts by sex for each location. These were used to compute life expectancy (LE) at birth by sex in 2019, which were compared with subnational LEs from the Global Burden of Disease (GBD) 2019 Study. RESULTS: A total of 9.92 million deaths (95% UI 9.70 to 10.02) were estimated across India in 2019, about 2.28 million more than CRS reports. Adjustments to under-five and elderly mortality accounted for 30% and 56% of additional deaths, respectively. Adjustments in Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh accounted for 75% of all additional deaths. Adjusted LEs were below corresponding GBD estimates by ≥2 years for males at national level and in 20 states, and by ≥1 year for females in 12 states. CONCLUSIONS: These results represent the first-ever subnational mortality estimates for India derived from CRS reported deaths, and serve as a baseline for assessing excess mortality from the COVID-19 pandemic. Adjusted life expectancies indicate higher mortality patterns in India than previously perceived. Under-reporting of infant deaths and those among women and the elderly is evident in many locations. Further CRS strengthening is required to improve the empirical basis for local mortality measurement across the country.

Systematic Review on Treatment Trials of Tocilizumab: A Repurposing Drug against COVID-19.

BACKGROUND: Coronavirus disease (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has become a global issue today. There exists an ongoing health crisis all over the world, and efficacious drugs against COVID-19 are not available yet. Therefore, on an urgent basis, scientists are looking for safe and efficacious drugs against SARSCoV- 2. METHODS: The reported individual patient data and clinical outcomes, including the rate of recovery and mortality, patients' characteristics, and complications, are reviewed. Randomized controlled trials, single-center cohort studies, and different case studies are provided, and the PICO model is used to illustrate the outcomes. RESULTS: There exist several FDA (U.S Food and Drug Administration) approved anti coronavirus drugs that sometimes are unsuccessful in curing COVID-19 critical conditions. It has been observed that a humanized monoclonal antibody, Tocilizumab (licensed for the treatment of rheumatoid arthritis), targeting the interleukin-6 (IL-6) receptor, has an integral role in the treatment of COVID-19. CONCLUSION: The cause behind the mortality of COVID-19 patients was found to be the Cytokine Release Syndrome (CRS). Therefore, besides other antiviral drugs, the utilization of tocilizumab should also be considered as it can effectively block IL-6 and reduce the inflammatory signal.

Mathematical model, forecast and analysis on the spread of COVID-19.

Pandemic COVID-19 which has infected more than 35,027,546 people and death more than 1,034,837 people in 235 countries as on October 05, 2020 has created a chaos across the globe. In this paper, we develop a compartmental epidemic model to understand the spreading behaviour of the disease in human population with a special case of Bhilwara, a desert town in India where successful control measures TTT (tracking, testing and treatment) was adopted to curb the disease in the very early phase of the spread of the disease in India. Local and global asymptotic stability is established for endemic equilibrium. Extensive numerical simulations with real parametric values are performed to validate the analytical results. Trend analysis of fatality rate, infection rate, and impact of lockdown is performed for USA, European countries, Russia, Iran, China, Japan, S. Korea with a comparative assessment by India. Kruskal - Wallis test is performed to test the null hypothesis for infected cases during the four lockdown phases in India. It has been observed that there is a significant difference at both 95% and 99% confidence interval in the infected cases, recovered cases and the case fatality rate during all the four phases of the lockdown.

Neurological manifestations and comorbidity associated with COVID-19: an overview.

First in 2002, severe acute respiratory syndrome coronavirus (SARS-CoV), second in 2012, Middle East respiratory syndrome coronavirus (MERS-CoV), and now the third in the December 2019, emergence of tremendously pathogenic and large-scale epidemic novel coronavirus (SARS-CoV-2) has brought the worst conditions into the human inhabitants of the twenty-first century. The SARS-CoV-2 uses the resembling receptor, angiotensin-converting enzyme 2 (ACE2) as that for SARS-CoV, and mainly feasts through the respiratory tract. The ACE2 receptor appearances have been also detected upon glial cells and neurons, which makes them a potential target of SARS-CoV-2 disease (COVID-19). Consequently, cells expressing ACE2, apart from lung and cardiovascular tissue, neurons and glial cells may act as targets and are thus vulnerable to SARS-CoV-2 systemic infection as well as its central nervous system (CNS) comorbidities. Investigation of the neurological manifestations of COVID-19 is a step towards better understanding the SARS-CoV-2 infections, inhibiting the additional spread and treating patients affected by this pandemic. In this concern, more clinical examinations for CNS involvement of SARS-CoV-2 are warranted. In this article, we have reviewed the neurological characteristic features of COVID-19 patients, latent neurotropic mechanisms of SARS-CoV-2 involvement in the comorbidity associated with CNS disorders, and neurological manifestations associated with COVID-19. Therefore, in the perspective of COVID-19 pandemic, clinicians and healthcare workers should be aware of a wide spectrum of neurological manifestations associated with COVID-19 along with their signs and symptoms for initial diagnosis and isolation of the patients.

Amendments in Entrepreneurship & Innovation Because of COVID-19 Pandemic (preprint)

The bond of innovation and entrepreneurship began from early days of humankind. From the accidental invention of fire because of striking of two stones together during the ages of early man to using those fire power for building steam engines, gas stoves and war weapons things get invented either intentionally or accidentally .Inventions and discoveries not only create new things but they open a wide areas of innovation so that things can be made better and more efficient. We humans have never stopped inventing and innovating things. Our mind keeps on seeing things from varied perspectives and opinions. Those opinions are put into action and reality. If the practical application of any new logic, theory, patent or strategy becomes successful it comes into the market of usage that how people can use this new invention so that they can trade it and can gain their own benefits. In other words, innovation and entrepreneurship are like magnets who always stick together. Time is the ultimate game changer in the world of invention and innovation that builds the platform of entrepreneurship. As time passed, we evolved from being early man living in caves to civilized human beings. Not only our lifestyle has innovated but our surroundings and environment have also got evolved over time. Let’s begin with education, during early years people used bark of trees and leaves as the medium to write things on but as time changed and the paper was discovered people started manufacturing them and using them as primary medium to write upon. Many companies have built their fortune upon innovating the quality of paper. From the days where children sat under the tree or in a small hut like place which they treated like schools where great scientists and philosophers were their teachers to building high class fully facilitated campuses which is capable of providing every possible platform for the students to rise , shine and innovate the existing things. So inspiring students at school for inventions that could make things better is innovation and investing capital for a school in order to gain profits and assets is entrepreneurship. But as we explore our history mother nature has always played a much bigger role in the cyclical interdependence of entrepreneurship and innovation with the introduction of some or the other calamity and pandemic which forces human race to see things in a different perspective and break the monotonous chain of how they invent and sell things We all are aware that before the introduction of COVID-19 our lives seem to be pretty monotonous like companies enhancing existing technologies, people claiming their copyright on those techs so that they can gain profit out of it and general public using it for their personal interest thinking that this way of living is only life. With the introduction of corona virus into this world people shut every possible way of what they were doing normally like visiting friends, conducting meetings etc and started prioritizing towards those areas which they were paying the least attention to. With the advancements in life style people seem to pay least attention those minute things like cleaning every single bit of yourself and your stuff before entering your house. This habit seemed nothing but now it has become mandatory to do so. Cleaning hands several times seemed a waste of time but now it has become a “new normal”. Actually mother nature through corona virus wants us to pay attention to those areas which are actually necessary in and for our lives.

Explainable-Machine-Learning to discover drivers and to predict mental illness during COVID-19 (preprint)

COVID-19 pandemic has deeply affected the global economy, education, and travel and stranded people in their respective zones. Most importantly, it has claimed more than half a million lives and is poised to create long and short term consequences through mental health impairment. Identification of important factors affecting mental health can help people manage emotional, psychological, and social well-being. Here, we focus on identifying factors that have a significant impact on mental health during COVID pandemics. In this study, We have used a survey of 17764 adults in the USA at different age groups, genders, and socioeconomic statuses. Through initial statistical analysis followed by Bayesian Network inference, we have identified key factors affecting Mental health during the COVID pandemic. Integrating Bayesian networks with classical machine learning approaches lead to effective modeling of the level of mental health. Overall, females are more stressed than males, and people of age-group 18-29 are more vulnerable to anxiety than other age groups. Using the Bayesian Network Model, we found that people with the chronic medical condition of mental illness are more prone to mental disorders during COVID age. The new realities of working from home, home-schooling, and lack of communication with family/friends/neighbors induces mental pressure. Financial assistance from social security helps in reducing mental stress during COVID generated economic crises. Finally, using supervised ML models, we predicted the most mentally vulnerable people with ~80% accuracy.