Türkiye'de CoronaVac ile Kovid-19 Aşılama Başlangıcında Sars-Cov-2 Yayılımının Matematiksel Modellenmesi

Abstract

The Sars-CoV-2 virus, first detected in Wuhan, China, became a global crisis that affected the entire world and was declared a pandemic by the World Health Organization (WHO) in March 2020. The most basic protective measure in the fight against pandemics facing humanity is vaccination. From this point of view, data is collected between January 13 and February 11, 2021 by taking the number of daily cases, deaths and recovered patients in Türkiye. During this period, vaccination against Covid-19 with Sinovac's CoronaVac vaccine is started in Türkiye. Mathematical predictive models of the observed values are constructed and compared using polynomial regression (up to the 3rd degree) and nonlinear regression, i.e., curve fitting methods, and SIR (Susceptible-Infected-Removed), which is a system of ordinary differential equations (ODEs). The efficiencies of these prediction models are tested, validated, and the most effective mathematical prediction models are proposed. The values of root mean square error (RMSE) and mean absolute percentage error (MAPE) are used as performance measures to compare the methods. The proposed prediction models are also used for forecasting. The number of new cases occurring each day is predicted using the time-dependent equations of the SIR method, which are solved using the Euler method. It is found that the SIR method is quite successful in predicting the observed values compared to the other methods, but the QR method are given more successful results in predicting the total number of deaths