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arXiv · 2004.07738

Inversion of a SIR-based model: a critical analysis about the application to COVID-19 epidemic

Mauro Giudici·Alessandro Comunian·Romina Gaburro
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Abstract

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 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.

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Mauro Giudici, Alessandro Comunian, Romina Gaburro. 2020-04-16. Inversion of a SIR-based model: a critical analysis about the application to COVID-19 epidemic. https://arxiv.org/abs/2004.07738

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