TY - JOUR

T1 - Numerical-statistical study of the prognostic efficiency of the SEIR model

AU - Lotova, Galiya Z.

AU - Lukinov, Vitaliy L.

AU - Marchenko, Mikhail A.

AU - Mikhailov, Guennady A.

AU - Smirnov, Dmitrii D.

N1 - Numerical-statistical study of the prognostic efficiency of the SEIR model / G. Z. Lotova, V. L. Lukinov, M. A. Marchenko [et al.] // Russian Journal of Numerical Analysis and Mathematical Modelling. – 2021. – Vol. 36. – No 6. – P. 337-345. Publisher Copyright: © 2021 Walter de Gruyter GmbH, Berlin/Boston.

PY - 2021/12/1

Y1 - 2021/12/1

N2 - A comparative analysis of the differential and the corresponding stochastic Poisson SEIR-models is performed for the test problem of COVID-19 epidemic in Novosibirsk modelling the period from March 23, 2020 to June 21, 2020 with the initial population N = 2 798 170. Varying the initial population in the form N = n m with m ≥ 2, we show that the average numbers of identified sick patients is less (beginning from April 7, 2020) than the corresponding differential values by the quantity that does not differ statistically from C(t)/m, with C ≈ 27.3 on June 21, 2020. This relationship allows us to use the stochastic model for big population N. The practically useful 'two sigma' confidential interval for the time interval from June 1, 2020 to June 21, 2020 is about 108% (as to the statistical average) and involves the corresponding real statistical estimates. The influence of the introduction of delay on the prognosis, i.e., the incubation period corresponding to Poisson model is also studied.

AB - A comparative analysis of the differential and the corresponding stochastic Poisson SEIR-models is performed for the test problem of COVID-19 epidemic in Novosibirsk modelling the period from March 23, 2020 to June 21, 2020 with the initial population N = 2 798 170. Varying the initial population in the form N = n m with m ≥ 2, we show that the average numbers of identified sick patients is less (beginning from April 7, 2020) than the corresponding differential values by the quantity that does not differ statistically from C(t)/m, with C ≈ 27.3 on June 21, 2020. This relationship allows us to use the stochastic model for big population N. The practically useful 'two sigma' confidential interval for the time interval from June 1, 2020 to June 21, 2020 is about 108% (as to the statistical average) and involves the corresponding real statistical estimates. The influence of the introduction of delay on the prognosis, i.e., the incubation period corresponding to Poisson model is also studied.

KW - COVID-19

KW - Monte Carlo methods

KW - Poisson flow

KW - SEIR model

KW - statistical simulation

UR - http://www.scopus.com/inward/record.url?scp=85121774099&partnerID=8YFLogxK

UR - https://www.elibrary.ru/item.asp?id=47546206

U2 - 10.1515/rnam-2021-0027

DO - 10.1515/rnam-2021-0027

M3 - Article

AN - SCOPUS:85121774099

VL - 36

SP - 337

EP - 345

JO - Russian Journal of Numerical Analysis and Mathematical Modelling

JF - Russian Journal of Numerical Analysis and Mathematical Modelling

SN - 0927-6467

IS - 6

ER -