Применение индивидуум-ориентированного подхода для моделирования эпидемического процесса
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Application of the individual-based model for the epidemic process modeling

Borisenko A.A.,  idBorisenko A.B.

UDC 004.942, 519.6, 614.4
DOI: 10.26102/2310-6018/2023.41.2.024

  • Abstract
  • List of references
  • About authors

Forecasting of epidemic processes makes it possible to develop and substantiate measures to prevent the spread of infectious diseases among the population as well as eliminate the negative consequences caused by epidemics. The paper deals with modeling the development of the epidemic process by means of an individual-based model. In these models, modeling is carried out using not an average group, but an individual level with consideration to the heterogeneity of the population by characteristics. Each individual can have three states: Susceptible (S), Infected (I), or Recovered (R). Transmission in a population occurs from individuals in state I to individuals in state S. After recovering, individuals I change state to R and become immune. Immunity wanes over time and individuals R revert to a susceptible state S. This paper is devoted to the development and software implementation of an algorithm for solving an individually oriented model, which helps to study the population dynamics of those groups. The results obtained for various model parameter values are presented. The results obtained using the individual-based simulation are compared with the results obtained by solving numerically the well-known SIRS model, which is a system of ordinary differential equations. As a further work, it is planned to modify the model by introducing additional groups of individuals while taking into account additional individual parameters (age, spatial coordinates, social contacts, etc.). To reduce the computation time in the study of the epidemic spread in large populations, algorithm parallelizing appears to be a prospective option.

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Borisenko Anton Andreevich

North-Western State Medical University named after I.I. Mechnikov

Saint Petersburg, The Russian Federation

Borisenko Andrey Borisovich
Candidate of Technical Sciences, Associate Professor
Email: borisenko.ab@mail.tstu.ru

WoS | Scopus | ORCID | eLibrary |

Tambov State Technical University

Tambov, The Russian Federation

Keywords: modeling of the epidemic process, epidemic models, individual-based model, computer modeling

For citation: Borisenko A.A., Borisenko A.B. Application of the individual-based model for the epidemic process modeling. Modeling, Optimization and Information Technology. 2023;11(2). URL: https://moitvivt.ru/ru/journal/pdf?id=1344 DOI: 10.26102/2310-6018/2023.41.2.024 (In Russ).

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Full text in PDF

Received 31.03.2023

Revised 15.05.2023

Accepted 21.06.2023

Published 30.06.2023