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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
Descripción
Sumario: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.