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, 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.
Authors
- Anna Brutman (ORCID: https://orcid.org/0000-0002-7774-5356)
- O.B. Alyokhin (ORCID: https://orcid.org/0000-0001-5209-8036)
- A. N. Grabovoy (ORCID: https://orcid.org/0000-0001-5705-9909)
- Tetiana Shabelnyk (ORCID: https://orcid.org/0000-0001-9798-391X)
Publication Details
- Journal
- System research and information technologies
- Published
- 2024-12-25
- DOI
- https://doi.org/10.20535/srit.2308-8893.2024.4.02
- Citations
- 1
- Primary Topic
- Business and Economic Development
- Type
- article
- Field-Weighted Citation Impact
- 0.71