Computation (Feb 2022)

Hierarchical Epidemic Model on Structured Population: Diffusion Patterns and Control Policies

  • Elena Gubar,
  • Vladislav Taynitskiy,
  • Denis Fedyanin,
  • Ilya Petrov

DOI
https://doi.org/10.3390/computation10020031
Journal volume & issue
Vol. 10, no. 2
p. 31

Abstract

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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.

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