Abstract:
The article is devoted to the construction of a mathematical model that takes into account some features of COVID-19 propagation.
The presented model is based on the classic SEIRD epidemic distribution model. The created model, in contrast to the basic one, takes into account the fact that latent COVIND-19 carriers are somewhat contagious and that in a significant number of infected people, the disease is asymptomatic. The SEIIRDm model reflects the fact that identified patients are isolating (hospitalizing) and the probability of infection from them decreases sharply and also that the measures taken over the quarantine are massive moreover, both the degree of their rigidity and the moment of introduction are important. Besides, the article draws attention to the fact that the relationship between the rate of change in the relative number of cases and susceptible and the relative number of infected may be nonlinear, and this fact is reflected in the built model.
The article provides examples of numerical forecasting of the development of the epidemiological process as well as modeling the impact of mass quarantine measures, calculated on the basis of the created mathematical model.
Keywords:
mathematical model, spread of the epidemic, COVID-19, differential equations.
Received: 20.09.2020 Revised: 14.10.2020
Bibliographic databases:
Document Type:
Article
UDC:517.958:57
Language: Russian
Citation:
N. I. Eremeeva, “Building a modification of the SEIRD model of epidemic spread that takes into account the features of COVID-19”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2020, no. 4, 14–27
\Bibitem{Ere20}
\by N.~I.~Eremeeva
\paper Building a modification of the SEIRD model of epidemic spread that takes into account the features of COVID-19
\jour Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.]
\yr 2020
\issue 4
\pages 14--27
\mathnet{http://mi.mathnet.ru/vtpmk602}
\crossref{https://doi.org/10.26456/vtpmk602}
\elib{https://elibrary.ru/item.asp?id=44503257}
Linking options:
https://www.mathnet.ru/eng/vtpmk602
https://www.mathnet.ru/eng/vtpmk/y2020/i4/p14
This publication is cited in the following 3 articles:
V. A. Sadovnichii, A. A. Akaev, A. I. Zvyagintsev, A. I. Sarygulov, “Mathematical modeling of overcoming the COVID-19 pandemic and restoring economic growth”, Dokl. Math., 106:1 (2022), 230–235
V. A. Sudakov, Yu. P. Titov, “Pandemic forecasting by machine learning in a decision support problem”, Math. Models Comput. Simul., 15:3 (2023), 520–528
Nina I. Eremeeva, “NUMERICAL MODELING OF THE IMPACT OF QUARANTINE MEASURES ON THE DYNAMICS OF THE EPIDEMIOLOGICAL PROCESS BASED ON THE SEIRD MODEL”, TSU Herald. Phys Math Model. Oil, Gas, Energy, 7:2 (2021), 170