Short-term forecasting of the main indicators of the COVID-19 epidemic in Ukraine based on the seasonal cycle model

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, su...

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Bibliographic Details
Main Authors: Alexei Alyokhin, Anna Brutman, Alexandr Grabovoy, Tetiana Shabelnyk
Format: Article
Language:Ukrainian
Published: Igor Sikorsky Kyiv Polytechnic Institute 2024-12-01
Series:Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
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Online Access:http://journal.iasa.kpi.ua/article/view/322459
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Summary: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.
ISSN:1681-6048
2308-8893