Geodesic
Statistical forecasting of the dynamics of epidemiological indicators for COVID-19 incidence in the republic of belarus
Journal of the Belarusian State University. Mathematics and Informatics, Tome 3 (2020), pp. 36-50

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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.
Keywords: forecasting; probability model; time series; point forecast; interval forecast; COVID-19. 
@article{BGUMI_2020_3_a3,
     author = {Yu. S. Kharin and V. A. Valoshka and O. V. Dernakova and V. I. Malugin and A. J. Kharin},
     title = {Statistical forecasting of the dynamics of epidemiological indicators for {COVID-19} incidence in the republic of belarus},
     journal = {Journal of the Belarusian State University. Mathematics and Informatics},
     pages = {36--50},
     publisher = {mathdoc},
     volume = {3},
     year = {2020},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/BGUMI_2020_3_a3/}
}
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Yu. S. Kharin; V. A. Valoshka; O. V. Dernakova; V. I. Malugin; A. J. Kharin. Statistical forecasting of the dynamics of epidemiological indicators for COVID-19 incidence in the republic of belarus. Journal of the Belarusian State University. Mathematics and Informatics, Tome 3 (2020), pp. 36-50. http://geodesic.mathdoc.fr/item/BGUMI_2020_3_a3/