Mathematical modeling of the spread of COVID-19 in Moscow

Koltsova, E.M.; Kurkina, E. S.; Vasetsky, Aleksey M.

doi:10.33693/2313-223x-2020-7-1-99-105

Cited by 19 publications

(17 citation statements)

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“…This is consistent with other researchers worldwide (e.g. see Amanso et al, 2020;Donsimoni et al, 2020;Koltsova et al, 2020;Lucero, 2020;Roy & Roy Bhattacharya, 2020;Sugiyanto & Abrori, 2020) who have also constructed different models according to different parameters in relation to their countries. For example, Italy has seen a sharp increase in the number of new infections and deaths since the first case was recorded and as such researchers' close investigations and mathematical modeling may help political pioneers and health care systems to apportion enough resources, including work force, beds, and concentrated intensive care units, to deal with the circumstance in the following difficulty days and weeks (Lazzerini & Putoto, 2020;Remuzzi & Remuzzi, 2020).…”

Section: Introductionsupporting

confidence: 91%

“…Until 11 th May 2020, the number of COVID-19 confirmed cases increased to 267 with 117 recoveries but sadly the number of deaths due to COVID-19 increased to 7. The virus, which has progressed in a highly deadly manner especially in the United States of America, United Kingdom and Italy and caused massive deaths globally -is continuing to spread (Cakir & Savas, 2020;Shrivastava & Shrivastava, 2020;Basilaia & Kvavadze, 2020;Koltsova et al, 2020). The rate at which this infection is spreading worldwide is alarming.…”

Section: Introductionmentioning

confidence: 99%

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Spread of COVID-19 Pandemic in Zambia: A Mathematical Model

Mulenga

2020

AQUADEMIA

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There has been a cumulative increase in the number of COVID-19 confirmed cases, recoveries as well as deaths in Zambia as declared by the Ministry of Health on regular basis. Based on the available statistical information, this article will discuss a mathematical model concerning the spread of COVID-19 in Zambia. To predict the spread of COVID-19 in Zambian provinces, a multiple regression analysis describing the interplay of factors influencing the increase in the number of cases is used to formalize the relationship. To ascertain the accuracy of the mathematical model used, exponential graphs regarding the spread of coronavirus (COVID-19) since its arrival over time in Zambia were obtained.

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Section: Introductionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Spread of COVID-19 Pandemic in Zambia: A Mathematical Model

Mulenga

2020

AQUADEMIA

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“…Вот уже целый год мы проводим исследования и делаем прогнозы по динамике распространения эпидемии в разных странах и регионах, начиная с марта 2020 г. [19][20][21][22]. Мы моделировали развитие эпидемии в Бразилии, Индии, США, Испании, Италии, Швеции, России, Москве и др.…”

Section: результаты моделированияunclassified

Mathematical modeling and forecasting of the spread of the COVID-19 coronavirus epidemic

Kurkina

Koltsova

2021

Futurity Designing. Digital Reality Problems

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In this paper, using the Feigenbaum logistic map, mathematical modeling of the spread of waves of the coronavirus epidemic in different countries is carried out. It is shown that the chosen model is optimal for describing the complex dynamics of the spread of infections in open, heterogeneous systems with inaccurately specified statistical data. A method for detecting local epidemic waves and determining the model parameters has been developed. It is shown that the model makes it possible to describe statistical data well and make realistic forecasts. The model is used to model the total number of cases, the total number of deaths, recoveries, and the calculation of active cases.

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“…The inverse problem (1)-(3) is in determining the vector of parameters q using the additional measurements (3).…”

Section: Inverse Problemmentioning

confidence: 99%

“…Papers [2] and [3] are the first to describe some scenarios of the coronavirus epidemic development in Moscow. The COVID-19 epidemic spread in China, taking into account the incubation period, passenger traffic, and decisions of the Health Care Commission is studied with SEIR mathematical models in [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling and Forecasting of COVID-19 in Moscow and Novosibirsk Region

Krivorotko

Кабанихин

Zyatkov

et al. 2020

Numer. Analys. Appl.

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We investigate inverse problems of finding unknown parameters of mathematical models SEIR-HCD and SEIR-D of COVID-19 spread with additional information about the number of detected cases, mortality, self-isolation coefficient, and tests performed for the city of Moscow and Novosibirsk region since 23.03.2020. In SEIR-HCD the population is divided into seven groups, and in SEIR-D into five groups with similar characteristics and transition probabilities depending on the specific region of interest. An identifiability analysis of SEIR-HCD is made to reveal the least sensitive unknown parameters as related to the additional information. The parameters are corrected by minimizing some objective functionals which is made by stochastic methods (simulated annealing, differential evolution, and genetic algorithm). Prognostic scenarios for COVID-19 spread in Moscow and in Novosibirsk region are developed, and the applicability of the models is analyzed.

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Mathematical modeling of the spread of COVID-19 in Moscow

Cited by 19 publications

References 0 publications

Spread of COVID-19 Pandemic in Zambia: A Mathematical Model

Spread of COVID-19 Pandemic in Zambia: A Mathematical Model

Mathematical modeling and forecasting of the spread of the COVID-19 coronavirus epidemic

Mathematical Modeling and Forecasting of COVID-19 in Moscow and Novosibirsk Region

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