Predicting the dynamics of the coronavirus (COVID-19) epidemic based on the case-based reasoning approach

被引:5
作者
Zakharov, V. V. [1 ]
Balykina, Yu E. [1 ]
机构
[1] St Petersburg State Univ, 7-9 Univ Skaya Nab, St Petersburg 199034, Russia
来源
VESTNIK SANKT-PETERBURGSKOGO UNIVERSITETA SERIYA 10 PRIKLADNAYA MATEMATIKA INFORMATIKA PROTSESSY UPRAVLENIYA | 2020年 / 16卷 / 03期
关键词
modeling; forecasting; COVID-19; epidemic; percentage rate of increase; case-based reasoning; heuristic;
D O I
10.21638/11701/spbu10.2020.303
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The case-based rate reasoning (CBRR) method is presented for predicting future values of the coronavirus epidemic's main parameters in Russia, which makes it possible to build short-term forecasts based on analogues of the percentage growth dynamics in other countries. A new heuristic method for estimating the duration of the transition process of the percentage increase between specified levels is described, taking into account information about the dynamics of epidemiological processes in countries of the spreading chain. The CBRR software module has been developed in the MATLAB environment, which implements the proposed approach and intelligent proprietary algorithms for constructing trajectories of predicted epidemic indicators.
引用
收藏
页码:249 / 259
页数:11
相关论文
共 9 条
[1]   Estimating the infection horizon of COVID-19 in eight countries with a data-driven approach [J].
Barmparis, G. D. ;
Tsironis, G. P. .
CHAOS SOLITONS & FRACTALS, 2020, 135
[2]   SBDiEM: A new mathematical model of infectious disease dynamics [J].
Bekiros, Stelios ;
Kouloumpou, Dimitra .
CHAOS SOLITONS & FRACTALS, 2020, 136 (136)
[3]   Analysis and forecast of COVID-19 spreading in China, Italy and France [J].
Fanelli, Duccio ;
Piazza, Francesco .
CHAOS SOLITONS & FRACTALS, 2020, 134
[4]  
[Кондратьев Михаил Александрович Kondratyev M.A.], 2013, [Компьютерные исследования и моделирование, Computer Research and Modeling, Komp'yuternye issledovaniya i modelirovanie], V5, P863
[5]   New coronavirus outbreak: Framing questions for pandemic prevention [J].
Layne, Scott P. ;
Hyman, James M. ;
Morens, David M. ;
Taubenberger, Jeffery K. .
SCIENCE TRANSLATIONAL MEDICINE, 2020, 12 (534)
[6]   A model based study on the dynamics of COVID-19: Prediction and control [J].
Mandal, Manotosh ;
Jana, Soovoojeet ;
Nandi, Swapan Kumar ;
Khatua, Anupam ;
Adak, Sayani ;
Kar, T. K. .
CHAOS SOLITONS & FRACTALS, 2020, 136
[7]  
Schmidt R, 2007, LECT NOTES COMPUT SC, V4692, P287
[8]   Prediction of the spread of influenza epidemics by the method of analogues [J].
Viboud, C ;
Boëlle, PY ;
Carrat, F ;
Valleron, AJ ;
Flahault, A .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2003, 158 (10) :996-1006
[9]   Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study [J].
Wu, Joseph T. ;
Leung, Kathy ;
Leung, Gabriel M. .
LANCET, 2020, 395 (10225) :689-697