The aim of this article is to examine the impacts of Coronavirus Disease -19 (Covid-19) vaccines on economic condition and sustainable development goals. In other words, we are going to study the economic condition during Covid19. We have studied the economic costs of pandemic, benefits in terms of gross domestic product (GDP), public finances and employment, investment on vaccines around the world, progress and totally the economic impacts of vaccines and the impacts of emerging markets (EM) on achieving sustainable development goals (SDGs), including no poverty, good health and well-being, zero hunger, reduced inequality etc. The importance of emerging economies in reducing the harmful effects of the Corona has also been noted. We have tried to do experimental results and forecast daily new death cases from Feb-2020 to Aug-2021 in Iran using Artificial Neural Network (ANN) and Beetle Antennae Search (BAS) algorithm as a case study with econometric models and regression analysis. The findings show that Covid19 has had devastating economic and health effects on the world, and the vaccine can be very helpful in eliminating these effects specially in long-term. We observed that there is inequality in the distribution of Corona vaccines in rich countries compared to poor which EM can decrease the gap between them. The results show that both models (i.e., Artificial intelligence (AI) and econometric models) almost have the same results but AI optimization models can robust the model and prediction. The main contribution of this article is that we have surveyed the impacts of vaccination from socio-economic viewpoint not just report some facts and truth. We have surveyed the impacts of vaccines on sustainable development goals and the role of EM in achieving SDGs. In addition to using the theoretical framework, we have also used quantitative and empirical results that have rarely been seen in other articles.

From 2020 to 2022 the Covid-19 was spread and many people died. Death is near to everyone. The aim of the study was to investigate differences of concept of good death and view of life and death cross cultural. Participants were 92 Japanese, 110 Korean and 100 American who were ordinary people. We used the Good Death questionnaire to measure desirable death and the Death Attitude Inventory to measure view of life and death. Participants completed both questionnaires. As for Good Death, Japanese and Korean regarded “not being burden to others” as important the most, and American regarded “feeling that one’s life is worth living” as important. The scores of “unawareness of death” and “religious and spiritual comfort” of Korean were the highest, following American, and Japan. As for the Death Attitude Inventory, the score of American was higher than Japanese and Korean totally. The scores of “Death as release” or “Death Avoidance” of American were the highest. These results suggest that although Japanese and Korean regard “Not being burden to others” as important in common, Korean regard religious and spiritual comfort as important. American may avoid to think of death and regard it as release. We can make use of these cultural differences in clinical situation.

Novel corona virus disease (COVID-19) pandemic, which started in China's Hubei province in 2019, has caused a significant loss of human lives globally. This study describes the epidemiologic and clinical profiles of COVID-19 related deaths among patients admitted to treatment centers in Sidama region, Ethiopia. A cross-sectional study of 186 in hospital COVID-19 related deaths that occurred from July 2020 to December 2021 in Sidama region were analyzed. Data was extracted from regional emergency operation center death report. Data was entered using Epidata v3.1 and analysis was done using SPSS v.20. Categorical data was summarized using frequency and percentage while continuous data was summarized using median and interquartile range. Association between variables was assessed using chi-square test. More than two-third of the deceased patients were male (135; 72.6%) and median age at death was 60. The majority of deaths (151; 81.1%) occurred in 2021, while April 2021 had the highest death records. Cough and shortness of breath were the main presenting symptoms occurring in 89.2% and 85.5% of deceased patients respectively. Most of the COVID-19 related deaths (64.5%) had associated comorbidities. Diabetes (50%) and Hypertension (39.2%) were the most prevalent comorbidities. Significant proportion of patients (74.73%) presented on severe end of disease spectrum (critical/ severe). Of the deceased patients, around two-third required Intensive care unit (ICU) admission and 111 of them were put on mechanical ventilator. Moreover, the median ICU stay was 4 days. Around half of the death (48.4%) occurred in the first 5 days. The median survival time from symptom onset was 11.5 days with most (43.5%) of the deaths occurring within the first 14 days of symptom onset. Age category was significantly associated with the number of days from onset to death (p=0.006). The case fatality rate was 1.87% which is lower than national and global reports. Unlike previous studies, the prevalence of asthma among deceased patients was low and there were no patients with documented COPD.

Background: Coronavirus disease has caused global turmoil especially causing huge impact on human life all over the world. Current reports states more than 3 million people have lost life and more than 160 million people are known to be suspected with the SARS-CoV-2. Transmission and disease incidence rates are indicators to assess the seriousness of COVID-19 pandemic and studies to understand the factors that aid in this direction are very vital to curb the disease. Methods: The study intends to discover the relationship by performing statistical analysis using correlation and multiple linear regression analysis between the variable’s population density, temperature, relative humidity, and active time of virus and find out the parameters that predict the cases reported per million population in 83 countries. Results: Analysis indicates active time of virus in days is very positively associated with the COVID -19 cases in all the countries r = .604, p < .01. Active time of virus shows strong negative correlation with temperature r = -.930, p < .01 revealing that rise in temperature will reduce the virus activity in the population. Together, these variables will account for 36.2% variance in the cases per million population with no significant prediction estimated from any factor. Conclusion: The study outcomes clearly state that population density alone is insufficient to estimate the extent of influence on COVID -19 cases as the number of persons living per sq. km of land is a dynamic quantity tend to fluctuate over time and space due to migration of population. In conjunction to the previous studies reported on the environmental and climatic factors influencing the cases reported, population dynamics does not show much significance on the disease spread and incidence. Contribution: The rise in confirmed cases and the high incidence rate reported in countries can be attributed to the active time of virus life expectancy as there is a positive correlation observed between the COVID-19 cases reported and the virus active time in the examined countries. Also, environment and climatic factors play a role in modulating the infection and transmission rate with less significant influence of population density on the COVID-19.