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

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About: Inversion of a SIR-based model: A critical analysis about the application to COVID-19 epidemic Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Inversion of a SIR-based model: A critical analysis about the application to COVID-19 epidemic
Creator	Comunian, Alessandro Gaburro, Romina Giudici, Mauro
Source	Elsevier; Medline; PMC
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.
has issue date	2020-08-12(xsd:dateTime)
bibo:doi	10.1016/j.physd.2020.132674
bibo:pmid	32834252
has license	no-cc
sha1sum (hex)	79c8e154907a972d60d8c04d2398bdcbeb644144
schema:url	https://doi.org/10.1016/j.physd.2020.132674
resource representing a document's title	Inversion of a SIR-based model: A critical analysis about the application to COVID-19 epidemic
has PubMed Central identifier	PMC7419377
has PubMed identifier	32834252
schema:publication	Physica D
resource representing a document's body	covid:79c8e154907a972d60d8c04d2398bdcbeb644144#body_text
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