The coronavirus disease 2019 (COVID-19) pandemic is spreading rapidly, and its psychosocial impact remains a big challenge. In this respect, quarantine has been recommended, as a significant practice, to prevent the given condition. Therefore, the present study was to determine the prevalence rates of depression, anxiety, and stress and to reflect on the impact of COVID-19, as a traumatic stressor event, on individuals. This web-based survey was fulfilled via an online questionnaire, completed by respondents selected through the cluster sampling technique, from March 24 to April 10, 2020, living in Mazandaran Province, Northern Iran. Accordingly, the data regarding demographic characteristics, physical health status, quarantine compliance, contact with COVID-19, and additional information were collected. The psychosocial impact of the pandemic was then assessed by the Impact of Event Scale-Revised (IES-R), and the respondents' mental health status was evaluated using the Depression, Anxiety, and Stress Scale-21 (DASS-21). Data analysis was further performed by linear regression. The study findings, from 1075 respondents, revealed that 22.5% of the cases had moderate-to-severe depression, 38.5% of the individuals were suffering from moderate-to-severe anxiety, and 47.2% of the participants were experiencing moderate-to-severe stress. In 14.5% of the respondents, the psychosocial impact of COVID-19 also varied from the possibility of post-traumatic stress disorder (PTSD) to immunosuppression (p  less then  0.01). https://www.selleckchem.com/products/H-89-dihydrochloride.html With the high prevalence rates of depression, anxiety, and stress, mental health professionals are suggested to develop psychosocial interventions and support plans for the general population to reduce the impact of the COVID-19 pandemic on public mental health status.Initiation of telemedicine in medical education in India was at par with developed countries but acceptance and progress have been slow. However, the recent coronavirus disease-19 (COVID-19) pandemic leading to disruption of Halstedian model of surgical teaching has changed the traditional dynamics of perception of this mode of education. Sanjay Gandhi PostGraduate Institute of Medical Sciences (SGPGIMS), has been a pioneer and introduced the telemedicine system into surgical education as early as in year 2001. In this article, we reviewed the literature on tele-education in surgical field in Indian scenario, with particular emphasis on tele-education activities at the SGPGIMS, with respect to current thinking and future prospects on surgical training.[This corrects the article DOI 10.1007/s12291-021-00986-x.].The coronavirus has a high basic reproduction number ( R 0 ) and has caused the global COVID-19 pandemic. Governments are implementing lockdowns that are leading to economic fallout in many countries. Policy makers can take better decisions if provided with the indicators connected with the disease spread. This study is aimed to cluster the countries using social, economic, health and environmental related metrics affecting the disease spread so as to implement the policies to control the widespread of disease. Thus, countries with similar factors can take proactive steps to fight against the pandemic. The data is acquired for 79 countries and 18 different feature variables (the factors that are associated with COVID-19 spread) are selected. Pearson Product Moment Correlation Analysis is performed between all the feature variables with cumulative death cases and cumulative confirmed cases individually to get an insight of relation of these factors with the spread of COVID-19. Unsupervised k-means algorithm is used and the feature set includes economic, environmental indicators and disease prevalence along with COVID-19 variables. The learning model is able to group the countries into 4 clusters on the basis of relation with all 18 feature variables. We also present an analysis of correlation between the selected feature variables, and COVID-19 confirmed cases and deaths. Prevalence of underlying diseases shows strong correlation with COVID-19 whereas environmental health indicators are weakly correlated with COVID-19.COVID-19 pandemic has affected more than a hundred fifty million people and killed over three million people worldwide over the past year. During this period, different forecasting models have tried to forecast time path of COVID-19 pandemic. Unlike the COVID-19 forecasting literature based on Autoregressive Integrated Moving Average (ARIMA) modelling, in this paper new COVID-19 cases were modelled and forecasted by conditional variance and asymmetric effects employing Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Threshold GARCH (TARCH) and Exponential GARCH (EGARCH) models. ARMA, ARMA-GARCH, ARMA-TGARCH and ARMA-EGARCH models were employed for one-day ahead forecasting performance for April, 2021 and three waves of COVID-19 pandemic in nine most affected countries -USA, India, Brazil, France, Russia, UK, Italy, Spain and Germany. Empirical results show that ARMA-GARCH models have better forecast performance than ARMA models by modelling both the conditional heteroskedasticity and the heavy-tailed distributions of the daily growth rate of the new confirmed cases; and asymmetric GARCH models show mixed results in terms of reducing the root mean squared error (RMSE).The COVID-19 pandemic is an evolving urban crisis. This research paper assesses impacts of the lockdown on food security and associated coping mechanisms in two small cities in Bangladesh (Mongla and Noapara) during March to May 2020. Due to restrictions during the prolonged lockdown, residents (in particular low-income groups) had limited access to livelihood opportunities and experienced significant or complete loss of income. This affected both the quantity and quality of food consumed. Coping strategies reported include curtailing consumption, relying on inexpensive starchy staples, increasing the share of total expenditure allocated to food, taking out loans and accessing relief. The pandemic has exacerbated the precariousness of existing food and nutrition security in these cities, although residents with guaranteed incomes and adequate savings did not suffer significantly during lockdown. While coping strategies and the importance of social capital are similar in small and large cities, food procurement and relationships with local governments show differences.