MATHEMATICAL MODELING OF COVID-19 PHENOMENON; THE CASES: GERMANY, ISRAEL AND CANADA

Abstract

Epidemic diseases are described as a pandemic that affects the enormous majority of the world, spreads rapidly among people, and causes deaths. Negative effects, the number of casualties, rates of spread, and the duration of the commencement and the end of such outbreaks differ from each other and depend on the regions of effect, the processes of the vaccination studies, and cure. Recently a virus has been discovered which has caused a pandemic that has threatened all the world: COVID-19. It is a kind of coronavirus that emerged originally among chickens in 1960s. This essay introduces COVID-19 cases using a mathematical method. It carefully examines data from worldometers, makes models, and estimations. The data discussed under titles such as Total Case, Outside China, Active Case, Total Cured, Critical Case, Germany, Israel, and Canada are analyzed without isolating their context. While the maximum-minimum ranges and standard deviations of the variables are displayed by a descriptive analysis, binary relations are observed by the correlation matrix. While the homogeneous distribution of the data is determined by factor analysis, hierarchical groups are expressed by cluster analysis. Future estimations are presented by data models presented to the reader with nine different variables.