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Modeling and controlling the spread of epidemic with various social and economic scenarios

We propose a dynamical model for describing the spread of epidemics. This model is an extension of the SIQR (susceptible-infected-quarantined-recovered) and SIRP (susceptible-infected-recovered-pathogen) models used earlier to describe various scenarios of epidemic spreading. As compared to the basi...

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Autores principales: Gandzha, I.S., Kliushnichenko, O.V., Lukyanets, S.P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174143/
https://www.ncbi.nlm.nih.gov/pubmed/34103789
http://dx.doi.org/10.1016/j.chaos.2021.111046
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author Gandzha, I.S.
Kliushnichenko, O.V.
Lukyanets, S.P.
author_facet Gandzha, I.S.
Kliushnichenko, O.V.
Lukyanets, S.P.
author_sort Gandzha, I.S.
collection PubMed
description We propose a dynamical model for describing the spread of epidemics. This model is an extension of the SIQR (susceptible-infected-quarantined-recovered) and SIRP (susceptible-infected-recovered-pathogen) models used earlier to describe various scenarios of epidemic spreading. As compared to the basic SIR model, our model takes into account two possible routes of contagion transmission: direct from the infected compartment to the susceptible compartment and indirect via some intermediate medium or fomites. Transmission rates are estimated in terms of average distances between the individuals in selected social environments and characteristic time spans for which the individuals stay in each of these environments. We also introduce a collective economic resource associated with the average amount of money or income per individual to describe the socioeconomic interplay between the spreading process and the resource available to infected individuals. The epidemic-resource coupling is supposed to be of activation type, with the recovery rate governed by the Arrhenius-like law. Our model brings an advantage of building various control strategies to mitigate the effect of epidemic and can be applied, in particular, to modeling the spread of COVID-19.
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spelling pubmed-81741432021-06-04 Modeling and controlling the spread of epidemic with various social and economic scenarios Gandzha, I.S. Kliushnichenko, O.V. Lukyanets, S.P. Chaos Solitons Fractals Article We propose a dynamical model for describing the spread of epidemics. This model is an extension of the SIQR (susceptible-infected-quarantined-recovered) and SIRP (susceptible-infected-recovered-pathogen) models used earlier to describe various scenarios of epidemic spreading. As compared to the basic SIR model, our model takes into account two possible routes of contagion transmission: direct from the infected compartment to the susceptible compartment and indirect via some intermediate medium or fomites. Transmission rates are estimated in terms of average distances between the individuals in selected social environments and characteristic time spans for which the individuals stay in each of these environments. We also introduce a collective economic resource associated with the average amount of money or income per individual to describe the socioeconomic interplay between the spreading process and the resource available to infected individuals. The epidemic-resource coupling is supposed to be of activation type, with the recovery rate governed by the Arrhenius-like law. Our model brings an advantage of building various control strategies to mitigate the effect of epidemic and can be applied, in particular, to modeling the spread of COVID-19. Elsevier Ltd. 2021-07 2021-06-03 /pmc/articles/PMC8174143/ /pubmed/34103789 http://dx.doi.org/10.1016/j.chaos.2021.111046 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Gandzha, I.S.
Kliushnichenko, O.V.
Lukyanets, S.P.
Modeling and controlling the spread of epidemic with various social and economic scenarios
title Modeling and controlling the spread of epidemic with various social and economic scenarios
title_full Modeling and controlling the spread of epidemic with various social and economic scenarios
title_fullStr Modeling and controlling the spread of epidemic with various social and economic scenarios
title_full_unstemmed Modeling and controlling the spread of epidemic with various social and economic scenarios
title_short Modeling and controlling the spread of epidemic with various social and economic scenarios
title_sort modeling and controlling the spread of epidemic with various social and economic scenarios
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174143/
https://www.ncbi.nlm.nih.gov/pubmed/34103789
http://dx.doi.org/10.1016/j.chaos.2021.111046
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