Journal
PHYSICA D-NONLINEAR PHENOMENA
Volume 413, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.physd.2020.132674
Keywords
Inverse problems; SIR models; COVID-19
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Calibration of a SIR (Susceptibles-Infected-Recovered) model with official international data for the COVID-19 pandemics provides a good example of the difficulties inherent in the solution of inverse problems. Inverse modeling is set up in a framework of discrete inverse problems, which explicitly considers the role and the relevance of data. Together with a physical vision of the model, the present work addresses numerically the issue of parameters calibration in SIR models, it discusses the uncertainties in the data provided by international authorities, how they influence the reliability of calibrated model parameters and, ultimately, of model predictions. (C) 2020 Elsevier B.V. All rights reserved.
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