Statistical forecasting of the dynamics of epidemiological indicators for COVID-19 incidence in the Republic of Belarus

• Main Authors: Yuriy S. Kharin, Valery A. Valoshka, Oksana V. Dernakova, Vladimir I. Malugin, Alexey Yu. Kharin
• Format: Article
• Language: Belarusian
• Published: Belarusian State University 2020-12-01
• Series: Журнал Белорусского государственного университета: Математика, информатика
• Subjects: forecasting, probability model, time series, point forecast, interval forecast, covid-19
• Online Access: https://journals.bsu.by/index.php/mathematics/article/view/3451

The paper is devoted to the urgent problem of statistical forecasting for the dynamics of the main epidemiological indicators for the COVID-19 pandemic in the Republic of Belarus based on the observed time series. To solve this problem, five methods are proposed: forecasting method based on «moving trends»; local-median forecasting method; forecasting method based on discrete time series; forecasting method based on the vector econometric error correction model; method of sequential statistical analysis. Algorithms for computation of point and interval forecasts for the main epidemiological indicators have been developed. The numerical results of computer forecasting are presented on the example of the Republic of Belarus.