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The mathematical relationship between COVID-19 cases and socio-economic indicators of OECD countries

ABSTRACT In most aspects, the COVID-19 pandemic has been the most impactful disease in the last few decades. Although two years have passed since the start of the COVID-19 pandemic, it is clear that the pandemic is far from being brought under full control. This pandemic, which was kept under control in part by the discovery of vaccines, has had a negative impact on people’s daily lives as well as global economies. The transmission and death rate of this disease, which was detected in Wuhan, China in December 2019, has differed between countries. The reason for these different rates according to countries has been investigated while developing a mathematical model in this comprehensive study. The effect of 16 different socioeconomic indicators of countries on the parameters of the COVID-19 pandemic was analyzed in this study, which was performed on 35 countries, the majority of which are OECD countries. The main objective of this research is to minimize potential negative effects by improving or taking these indicators into account in future similar outbreaks. In this study, canonical correlation analysis was used to obtain the appropriate mathematical model and the performance of the obtained model has been tested statistically. According to the mathematical model obtained, the age factor comes to the fore as the most important indicator in the COVID-19 pandemic and the next important indicator is the health expenditures of the countries. The influence of 16 different socioeconomic indicators on the COVID-19 pandemic parameters are presented as a percentage with details.