Sıla Övgü KORKUT UYSAL, Nurcan GÜCÜYENEN, Yeşim ÇİÇEK

A NONLINEAR REGRESSION MODEL, ANALYSIS AND SIMULATIONS FOR THE SECOND WAVE OF COVID-19: THE CASE STUDY OF TURKEY

COVID-19 pandemic disease gained major attention among scientists due to its high mortality/ infectiousness rate. Moreover, the analysis of this disease requires much attention by the Government to take precautions and construct strategies. This study aims to develop a new nonlinear model for COVID-19. The main focus is the time when the number of daily infected individuals has begun to increase constantly. To this end, the time series from 1 August 2020 to 22 September 2020 is conducted. Moreover, the proposed model takes into account the disease characteristics. After the model parameters are obtained by detailed mathematical analysis by the trained data, the model is validated by the test/evaluation data set. The results and simulations show that the proposed model has a perfect match with the raw data. Furthermore, the calculated standard errors when compared by the population of Turkey are evidence of how well the model fits the raw data. This study is important not only because it achieves good results but also because it is the first nonlinear regression model including its mathematical analysis for the COVID-19 pandemic.

Anahtar Kelimeler:

COVID-19, , Nonlinear Regression, , Nonlinear Analysis, Simulation, Standard Error

A NONLINEAR REGRESSION MODEL, ANALYSIS AND SIMULATIONS FOR THE SECOND WAVE OF COVID-19: THE CASE STUDY OF TURKEY

Keywords:

COVID-19, Nonlinear Regression, Nonlinear Analysis, Simulation, Standard Error,

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