Notes

Angiographic as well as Medical Profile regarding Patients Using COVID-19 Referenced with regard to Heart Angiography During SARS-CoV-2 Break out: Comes from a new Collaborative, European, Multicenter Personal computer registry.
This paper examines critically the economic package announced by the Indian central government to counter the challenges of lives and livelihood in the Covid-19 pandemic. This paper estimates the shares of the fiscal economic packages in two phases as per the shares of the vulnerable workers and number of Covid-19 cases in the Indian states. The recent data on labour market are used from National Sample Survey Organization and data on Covid-19 cases from Ministry of Health and Family Welfare. This paper recommends alternatively a fiscal stimulus package of Rs. 10 lakh crores (5% of GDP) with an immediate effect to counter the present problems of health, food and unemployment in the pandemic and should be extended to Rs. 24 lakh crores (12% of Indian GDP) to the Indian states for at least 1 year to protect the lives and livelihood of the most vulnerable, informal and migrant workers. The populous and poor states like Uttar Pradesh and Bihar have higher share of vulnerable workers and highly industrialized states like Maharashtra, Gujarat, Delhi and Tamil Nadu have higher number of Covid-19 cases. Due to the unplanned lockdown in India, there has been a surge in Covid-19 cases across the country that in turn led to an increase in vulnerable workers in poor states due to reverse migration from industrialized states to populous and poor states during the pandemic. Furthermore, the paper explains the five significant factors that justify the adoption of an expansionary fiscal policy rather than monetary policy.There has been much talk, globally and locally, about family violence during the COVID-19 pandemic. Family violence has received increasing interest from the researchers in many different fields, while family violence during the COVID-19 pandemic outbreak still needs researchers' attention to investigate its predictors and detect the prevalence among family members through this health crisis. This study aimed to investigate the spread of family violence and detect the predictors of it with the applied advanced statistical procedure, structural equation modeling (SEM). The researchers prepared the family violence scale that consisted of 21 items, and applied it in a random sample that consisted of (312) individual. The finding indicated that there are high levels of family violence, violence between spouses, violence from parents to children, and sibling violence. As well as, the findings found that the years of marriage are statistically significant of violence between spouses, violence from parents to children, and sibling violence, and the total score of the family violence. As well as, sex is a statistically significant predictor of violence between spouses. While the educational level, age, and income level did not predict violence (total score or dimensions). Based on the results of the current study, counseling programs to reduce family violence and psychotherapy programs to reduce the negative effects of family violence on parents and children must be planned. Therefore, the role of traditional and online family counseling and psychotherapy must be activated in light of the outbreak of the COVID-19 pandemic.During COVID-19 lockdown, individuals were asked to leave their home only to meet the most urgent needs, such as grocery purchases and medical emergencies. This study aimed to know the consumers' health safety practices and their concerns toward grocery shopping and to know their adoption of healthier food as a result of the outbreak. An online survey was conducted during the second month of the COVID-19 lockdown. This study includes 212 respondents. Appropriate statistical tools were used to analyze the data. The findings of the study revealed that females were ahead compared to males in pursuing health safety practices during grocery shopping, but the frequency of following physical distancing for both males and females was not up to the mark. The most important concern about grocery shopping was fear of unavailability of stocks and fear of getting infected from grocery storekeepers. It was also found that, compared to earlier, people had reduced their frequency of grocery shopping and tried to shop quickly and efficiently. People bought more packaged foods and also made purchases from brands that were new to them. As a result of the COVID-19 pandemic, the adoption of healthier food habits varied significantly with gender, age, and household income of the respondents. This study indicates that there is a need to raise awareness among people on how to shop safely in grocery stores and that good hygiene practice should be followed in grocery stores to mitigate the risk of infection to consumers.This paper empirically investigates the impact of COVID-19 on the volatility of stock prices in India with the help of a generalized autoregressive conditional heteroscedasticity model. Daily closing prices of stock indices, Nifty and Sensex from September 3, 2019 to July 10, 2020 has been used for the analysis. selleck kinase inhibitor Further, the study has been attempted to make a comparison of stock price return in pre-COVID-19 and during COVID-19 situation. Findings reveal that the stock market in India has experienced volatility during the pandemic period. While comparing the result during COVID period with that of the pre-COVID, we found that the return on the indices is higher in the pre-COVID-19 period than during COVID-19.This paper has been empirically investigated the existence of the day-of-the-week effect by using closing daily data for Nifty 50, Nifty 50 Midcap, Nifty 100, Nifty 100 Midcap, Nifty 100 Smallcap, and Nifty 200 for before and during the COVID-19 health crisis. This study used secondary data for all indices over the period 1 April 2005-14 May 2020. The present study used both dummy variable regression and the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. The total study period is divided into two sub-periods, that is, during and before the COVID-19 health crisis. A negative return is found for Mondays when the during-COVID-19 health crisis period is examined; in contrast, it was positive for the before COVID-19 period. Tuesday's effect on index return is found statistically significant and positive for all indices during the COVID-19 crisis.
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