Data analysis of coronavirus COVID-19 epidemic in South Korea based on recovered and death cases.

Coronavirus epidemic caused an emergency in South Korea. The first infected case came to light on 20 January 2020 followed by 9583 more cases that were reported by 29 March 2020. This indicates that the number of confirmed cases is increasing rapidly, which can cause a nationwide crisis for the country. The aim of this study is to fill a gap between previous studies and the current rate of spreading of COVID-19 by extracting a relationship between independent variables and the dependent ones. This study statistically analyzed the effect of factors such as sex, region, infection reasons, birth year, and released or diseased date on the reported number of recovered and deceased cases. The results found that sex, region, and infection reasons affected both recovered and deceased cases, while birth year affected only the deceased cases. Besides, no deceased cases are reported for released cases, while 11.3% of deceased cases positive confirmed after their deceased. Unknown reason of infection is the main variable that detected in South Korea with more than 33% of total infected cases.

The impact of Russo-Ukrainian war, COVID-19, and oil prices on global food security.

Context: Light of recent global upheavals, including volatile oil prices, the Russo-Ukrainian conflict, and the COVID-19 pandemic this study delves into their profound impact on the import and export dynamics of global foodstuffs. With rising staple food prices reminiscent of the 2010-2011 global food crisis, understanding these shifts comprehensively is imperative. Objective: Our objective is to evaluate this impact by examining six independent variables (year, month, Brent crude oil, COVID-19, the Russo-Ukrainian conflict) alongside six food indicators as dependent variables. Employing Pearson's correlation, linear regression, and seasonal autoregressive integrated moving averages (SARIMA), we scrutinize intricate relationships among these variables. Results and conclusions: Our findings reveal varying degrees of association, notably highlighting a robust correlation between Brent crude oil and food indicators. Linear regression analysis suggests a positive influence of the Russo-Ukrainian conflict, Brent oil on food price indices, and COVID-19. Furthermore, integrating SARIMA enhances predictive accuracy, offering insights into future projections. Significance: Finally, this research has a significant role in providing a valuable analysis into the intricate dynamics of global food pricing, informing decision-making amidst global challenges and bridging critical gaps in prior research on forecasting food price indices.