Using the Lagrange Interpolation Polynomial Method to calculate the prevalence of coronavirus disease 2019 (COVID-19) in Turkey

Abstract

The goal of this paper is to look into a numerical approximation for the spread of the coronavirus disease 2019 (COVID-19) in Turkey. From March 11th to November 30th, all data is examined one by one for this purpose. The Lagrange interpolation method does not require evenly spaced x values. On the other hand, it is usually preferable to look for the closest value in the table and then use the lowest-order interpolation that is consistent with the functional form of the data. Using this method, a function for monthly and general data on the number of COVID-19 disease deaths and cases infected with the disease is obtained. Matlab programming is used to obtain Lagrange interpolation polynomials. Simulations for month by month and general data are obtained using Lagrange interpolation polynomial. The rate of spread of disease and death numbers is obtained by taking the first derivative of this function. Monthly and general tables are constructed for this propagation rate data. Peak point of the disease and different change values ​​are determined from the information in these simulations. The rates of death and spread of the disease by months are compared. As a result of this comparison, it can be seen in which months the rate of spread of disease and death increases and decreases. Monthly increase and decrease values ​​can be seen from the Figure 3-Figure 6. For example, a relative decrease can be observed in April and May