Mathematical model of the spread of COVID-19 in the rostov region for 2020–2022

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Abstract

BACKGROUND: In the context of the COVID-19 epidemic, there is a need for forecasting tools that enables us to predict the possible epidemic consequences and evaluate the effectiveness of epidemic control. Mathematical modeling can serve as such a tool.

AIM: The Aim is to present a mathematical model of the spread of COVID-19 in the Rostov Region for 2020–2022. To be more precise, the aim is to forecast how the number of people infected, recovered, hospitalized and died from the epidemic of the new coronovirus will change over this period of time.

MATERIALS AND METHODS: The modeling of the epidemics was based on the extended SEIR model proposed by R. Neyer et al. for forecasting the COVID-19 epidemic and implemented as a freely available web application.

RESULTS: The model under consideration made it possible to forecast the volume of hospitalization and the number of deaths in the course of COVID-19 epidemic in the Rostov region for 2020–2022.

CONCLUSIONS: The performed simulations demonstrated the capabilities the considered SEIR model for forecasting the COVID-19 epidemic. It was found that the number of hospitalized patients for the entire period covered by the model does not exceed the capabilities of the health care system of the Rostov Region.

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About the authors

Viktor V. Denisenko

Rostov Research Institute of Microbiology and Parasitology

Author for correspondence.
Email: vct.dns@gmail.com
ORCID iD: 0000-0002-1389-2453
SPIN-code: 4871-7267

Engineer of the Laboratory for Virology, Microbiology and Molecular Biological Research Methods

Russian Federation, Rostov-on-Don

Anna V. Aleshukina

Rostov Research Institute of Microbiology and Parasitology

Email: aaleshukina@mail.ru
ORCID iD: 0000-0002-9797-2441
SPIN-code: 5248-8912
Scopus Author ID: 6505968090

MD, Dr. Sci. (Med.), Head of the Laboratory for Virology, Microbiology and Molecular Biological Research Methods

Russian Federation, Rostov-on-Don

References

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Supplementary files

Supplementary Files
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1. JATS XML
2. Fig. 1. Modeling the spread of COVID-19 in the Rostov Region. The number of recovered, infectious, registered cases and deaths

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3. Fig. 2. Modeling the spread of COVID-19 in the Rostov Region. The number of hospitalized

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4. Fig. 3. Modeling the spread of COVID-19 in the Rostov Region. The number of deaths

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