Короткострокове прогнозування основних показників епідемії в Україні на основі моделі сезонних циклів

• Date: 2024
• Author Affiliations: Alexei Alyokhin — Mariupol State University, Kyiv; Anna Brutman — National University “Zaporizhzhia Polytechnic”, Zaporizhzhia; Alexandr Grabovoy — Bogomolets National Medical University, Kyiv; Tetiana Shabelnyk — Simon Kuznets Kharkiv National University of Economics, Kharkiv
• Keywords: keywords
• Main Authors: Alyokhin, Alexei, Brutman, Anna, Grabovoy, Alexandr, Shabelnyk, Tetiana
• Format: Article
• Language: English
• Published: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2024
• Subjects: епідемія COVID-19; часові ряди; короткострокове прогнозування
• Online Access: https://journal.iasa.kpi.ua/article/view/322459
• Journal Title: System research and information technologies

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.