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# Abstracts

## Mathematical modeling of the epidemic situation COVID-19 in the Kirov region

Vishnyakov A.V.

Federal State Budgetary Educational Institution of Higher Education "Kirov State Medical University" of the Ministry of Healthcare of the Russian Federation, 112 Karl Marx str., Kirov, 610027, Russia, tel. 8(8322) 374840, e-mail mishakrossingover@gmail.com

1 pp. (accepted)

A mathematical model of the spread of a new coronavirus infection should have parameters easily selected from statistical data in order to make it possible to realistically predict the dynamics of morbidity growth and, consequently, calculate the burden on the healthcare system [1]. Studies have been conducted in different countries using coplanar models such as SIR [2], etc. To date, in relation to the strategy of doctors' work, modeling of the epidemic situation at the regional level is relevant, which is what this work is devoted to. The study uses an "epidemic calculator" developed by G. Goh [3] based on the SEIR model, taking into account additional information about mortality and the burden on healthcare. To achieve compliance of the model with real statistical data for the region (Yandex database [4]), such parameters are selected as: the number of initially infected people, the basic reproductive number, the duration of the incubation period and the release of the pathogen to infected people, as well as mortality. Certain values of the parameters of the model used in the work make it possible to explain the available statistical data, but the predictive ability of the calculator at the regional level is questioned due to the obvious statistical uncertainty of the initial data. It turned out that in order to identify a mathematical model, it is necessary to use smoothing procedures for the initial data.

References.

1. Кольцова Э.М., Куркина Е.С., Васецкий А.М. Математическое моделирование распространения эпидемии коронавируса Covid-19 в ряде европейских, азиатских стран, Израиле и России // Проблемы экономики и юридической практики. 2020. №2. URL: https://cyberleninka.ru/article/n/matematicheskoe-modelirovanie-rasprostraneniya-epidemii-koronavirusa-covid-19-v-ryade-evropeyskih-aziatskih-stran-izraile-i-rossii-1 (дата обращения: 30.12.2021).

2. Marinov T.T., Marinova R.S. Dynamics of COVID-19 using inverse problem for coefficient identification in SIR epidemic models // Chaos, Solitons & Fractals: X 5 (2020) 100041

3. Epidemic Calculator // gabgoh.github.io URL: https://gabgoh.github.io/COVID/index.html (дата обращения: 30.12.2021).

4. Динамика по регионам, прирост за день // datalens.yandex.ru URL: https://datalens.yandex.ru/wizard/sfs1fm2c8wpal-dinamika-po-regionam-prirost-za-den (дата обращения: 13.12.2021).

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