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Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America

This work presents a method for solving an Adaptive Susceptible-Infected-Removed (A-SIR) epidemic model with time-dependent transmission and removal rates. Available COVID-19 data as of March 2021 are used for identifying the rates from an inverse problem. The estimated rates are used to solve the a...

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Detalles Bibliográficos
Autores principales: Marinov, Tchavdar T., Marinova, Rossitza S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674112/
https://www.ncbi.nlm.nih.gov/pubmed/34934870
http://dx.doi.org/10.1016/j.idm.2021.12.001
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author Marinov, Tchavdar T.
Marinova, Rossitza S.
author_facet Marinov, Tchavdar T.
Marinova, Rossitza S.
author_sort Marinov, Tchavdar T.
collection PubMed
description This work presents a method for solving an Adaptive Susceptible-Infected-Removed (A-SIR) epidemic model with time-dependent transmission and removal rates. Available COVID-19 data as of March 2021 are used for identifying the rates from an inverse problem. The estimated rates are used to solve the adaptive SIR system for the spread of the infectious disease. This method simultaneously solves the problem for the time-dependent rates and the unknown functions of the A-SIR system. Presented results show the spread of COVID-19 in the World, Argentina, Brazil, Colombia, Dominican Republic, and Honduras. Comparisons of the reported affected by the disease individuals from the available real data and the values obtained with the A-SIR model demonstrate how well the model simulates the dynamic of the infectious disease.
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spelling pubmed-86741122021-12-16 Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America Marinov, Tchavdar T. Marinova, Rossitza S. Infect Dis Model Original Research Article This work presents a method for solving an Adaptive Susceptible-Infected-Removed (A-SIR) epidemic model with time-dependent transmission and removal rates. Available COVID-19 data as of March 2021 are used for identifying the rates from an inverse problem. The estimated rates are used to solve the adaptive SIR system for the spread of the infectious disease. This method simultaneously solves the problem for the time-dependent rates and the unknown functions of the A-SIR system. Presented results show the spread of COVID-19 in the World, Argentina, Brazil, Colombia, Dominican Republic, and Honduras. Comparisons of the reported affected by the disease individuals from the available real data and the values obtained with the A-SIR model demonstrate how well the model simulates the dynamic of the infectious disease. KeAi Publishing 2021-12-16 /pmc/articles/PMC8674112/ /pubmed/34934870 http://dx.doi.org/10.1016/j.idm.2021.12.001 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research Article
Marinov, Tchavdar T.
Marinova, Rossitza S.
Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America
title Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America
title_full Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America
title_fullStr Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America
title_full_unstemmed Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America
title_short Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America
title_sort inverse problem for adaptive sir model: application to covid-19 in latin america
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8674112/
https://www.ncbi.nlm.nih.gov/pubmed/34934870
http://dx.doi.org/10.1016/j.idm.2021.12.001
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