Standard

Hierarchical Epidemic Model on Structured Population : Diffusion Patterns and Control Policies. / Gubar, Elena; Taynitskiy, Vladislav; Fedyanin, Denis; Petrov, Ilya.

In: Computation, Vol. 10, No. 2, 31, 02.2022.

Research output: Contribution to journal › Article › peer-review

Harvard

Gubar, E, Taynitskiy, V, Fedyanin, D & Petrov, I 2022, 'Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies', Computation, vol. 10, no. 2, 31. https://doi.org/10.3390/computation10020031

APA

Gubar, E., Taynitskiy, V., Fedyanin, D., & Petrov, I. (2022). Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies. Computation, 10(2), [31]. https://doi.org/10.3390/computation10020031

Vancouver

Gubar E, Taynitskiy V, Fedyanin D, Petrov I. Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies. Computation. 2022 Feb;10(2). 31. https://doi.org/10.3390/computation10020031

Author

Gubar, Elena ; Taynitskiy, Vladislav ; Fedyanin, Denis ; Petrov, Ilya. / Hierarchical Epidemic Model on Structured Population : Diffusion Patterns and Control Policies. In: Computation. 2022 ; Vol. 10, No. 2.

BibTeX

@article{d19a69c2b87c4398b101ba52c11dad98,
title = "Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies",
abstract = "In the current study, we define a hierarchical epidemic model that helps to describe the propagation of a pathogen in a clustered human population. The estimation of a novel coronavirus spreading worldwide leads to the idea of the hierarchical structure of the epidemic process. Thus, the propagation process is divided into three possible levels: a city, a country, and a worldwide. On each level, the pathogen propagation process is based on the susceptible-exposed-infected-recovered (SEIR) model. We thus formulate a modified transmission model of infected individuals between levels. The control of the pathogen{\textquoteright}s spread can be seen as an optimal control problem. A trade-off exists between the cost of active virus propagation and the design of appropriate quarantine measures. Each level of the hierarchy is defined by its network. A series of numerical experiments was conducted to corroborate the obtained results.",
keywords = "Compartment epidemic models, Epidemic process, Optimal control, SIR model, SPREADING PROCESSES, VIRUS, epidemic process, compartment epidemic models, INFLUENZA, DYNAMICS, optimal control",
author = "Elena Gubar and Vladislav Taynitskiy and Denis Fedyanin and Ilya Petrov",
note = "Gubar, E.; Taynitskiy, V.; Fedyanin, D.; Petrov, I. Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies. Computation 2022, 10, 31. https://doi.org/10.3390/computation10020031",
year = "2022",
month = feb,
doi = "10.3390/computation10020031",
language = "English",
volume = "10",
journal = "Computation",
issn = "2079-3197",
publisher = "MDPI AG",
number = "2",

}

RIS

TY - JOUR

T1 - Hierarchical Epidemic Model on Structured Population

T2 - Diffusion Patterns and Control Policies

AU - Gubar, Elena

AU - Taynitskiy, Vladislav

AU - Fedyanin, Denis

AU - Petrov, Ilya

N1 - Gubar, E.; Taynitskiy, V.; Fedyanin, D.; Petrov, I. Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies. Computation 2022, 10, 31. https://doi.org/10.3390/computation10020031

PY - 2022/2

Y1 - 2022/2

N2 - In the current study, we define a hierarchical epidemic model that helps to describe the propagation of a pathogen in a clustered human population. The estimation of a novel coronavirus spreading worldwide leads to the idea of the hierarchical structure of the epidemic process. Thus, the propagation process is divided into three possible levels: a city, a country, and a worldwide. On each level, the pathogen propagation process is based on the susceptible-exposed-infected-recovered (SEIR) model. We thus formulate a modified transmission model of infected individuals between levels. The control of the pathogen’s spread can be seen as an optimal control problem. A trade-off exists between the cost of active virus propagation and the design of appropriate quarantine measures. Each level of the hierarchy is defined by its network. A series of numerical experiments was conducted to corroborate the obtained results.

AB - In the current study, we define a hierarchical epidemic model that helps to describe the propagation of a pathogen in a clustered human population. The estimation of a novel coronavirus spreading worldwide leads to the idea of the hierarchical structure of the epidemic process. Thus, the propagation process is divided into three possible levels: a city, a country, and a worldwide. On each level, the pathogen propagation process is based on the susceptible-exposed-infected-recovered (SEIR) model. We thus formulate a modified transmission model of infected individuals between levels. The control of the pathogen’s spread can be seen as an optimal control problem. A trade-off exists between the cost of active virus propagation and the design of appropriate quarantine measures. Each level of the hierarchy is defined by its network. A series of numerical experiments was conducted to corroborate the obtained results.

KW - Compartment epidemic models

KW - Epidemic process

KW - Optimal control

KW - SIR model

KW - SPREADING PROCESSES

KW - VIRUS

KW - epidemic process

KW - compartment epidemic models

KW - INFLUENZA

KW - DYNAMICS

KW - optimal control

UR - http://www.scopus.com/inward/record.url?scp=85125144812&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/68a0867f-ea1a-32c6-b908-9183e9ab0b34/

U2 - 10.3390/computation10020031

DO - 10.3390/computation10020031

M3 - Article

AN - SCOPUS:85125144812

VL - 10

JO - Computation

JF - Computation

SN - 2079-3197

IS - 2

M1 - 31

ER -

ID: 93923679