Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model - Alexei Alyokhin; Anna Brutman; Alexandr Grabovoy; Tetiana Shabelnyk (Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï)
The authors of this study propose a method of short-term forecasting of time series of the main indicators of the COVID-19 epidemic, which has a pronounced seasonality. This method, which has no direct analogies, provides the decomposition of a general forecasting task into several simpler tasks, such as the tasks of building a model of the seasonal cycle of a time series, aggregating the original time series, taking into account the duration of the seasonal cycle, forecasting an aggregated time series, developing an aggregated forecast into a forecast in the original time scale, using the seasonal cycle model. The solution for each task allows the usage of relatively simple methods of mathematical statistics. The article provides a formally rigorous description of all procedures of the method and illustrations of their numerical implementation on the example of a real forecasting task. The use of this method for short-term forecasting of the COVID-19 epidemic development in Ukraine has systematically demonstrated its effectiveness.