To simulate how the number of COVID-19 cases increases versus time, various data sets and different mathematical models can be used . In particular, previous simulations of the COVID-19 epidemic dynamics in Ukraine were based on smoothing of the dependence of the number of cases on time and the generalized SIR (susceptible-infected-removed) model . Since real number of cases is much higher than the official numbers of laboratory confirmed ones, there is a need to assess the degree of data incompleteness and correct the relevant forecasts . We have improved the method of estimating the unknown parameters of the generalized SIR model and calculated the optimal values of the parameters . It turned out that the real number of diseases exceeded the officially registered values by about 4.1 times at the end of 2020 in Ukraine . This fact requires a reassessment of the COVID-19 pandemic dynamics in other countries and clarification of world forecasts.