A queuing model application on COVID 19 world data with a stochastic approach

This study was conducted to examine the world distribution of the Covid 19 virus outbreak and to analyze the change in the virus population. In the study, the birth-death process, which is a stochastic process approach, was tried to be examined by using the immigration and emigration data of the Covid-19 population in the years 2020-2021. In this study, the stochastic process approach of birth-death model was examined by utilizing the immigration and emigration data in Covid-19 population during the period of 2020-2021. For this purpose, the daily official data of the WHO (World Health Organization) were used. In the scope of this research, Europe was represented by Germany, France, England, Spain and Italy, North America by USA, South America by Brazil, East Asia by China and Japan, and Asia by Russia and India. While examining these groups, the example of Turkey has also been handled. Given that the factors causing inflow or outflow in migration are stochastic, probability distributions of entry and exit to populations were determined for each country. Transformations have been applied to accurately compare the rates of virus spread or improvements in countries. Using these transformed data, a new formula has been proposed as a traffic density parameter that provides ease of application and interpretation in outbreaks. Stochastic models were used in the study, principal component analysis and factor analysis applications were performed for grouping purposes during the analysis. In the light of these analyses, country and region groupings were interpreted by making comparisons and contrasts. Keywords: Queuing Theory, Covid-19 Disease, Birth-and-Death Process.