About: A fractional-order model for the novel coronavirus (COVID-19) outbreak

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About: A fractional-order model for the novel coronavirus (COVID-19) outbreak Goto Sponge NotDistinct Permalink

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A fractional-order model for the novel coronavirus (COVID-19) outbreak
Creator	Fatemeh, Hasanzadeh Hamarash, I Hamarash, Ismael Hasanzadeh, N Hussain, I Hussain, Iqtadar Ibrahim, Parastesh Jafari, S Jafari, Sajad Jafari, · Navid, · Parastesh, F Rajagopal, K Rajagopal, Karthikeyan
Source	Medline; PMC
abstract	The outbreak of the novel coronavirus (COVID-19), which was firstly reported in China, has affected many countries worldwide. To understand and predict the transmission dynamics of this disease, mathematical models can be very effective. It has been shown that the fractional order is related to the memory effects, which seems to be more effective for modeling the epidemic diseases. Motivated by this, in this paper, we propose fractional-order susceptible individuals, asymptomatic infected, symptomatic infected, recovered, and deceased (SEIRD) model for the spread of COVID-19. We consider both classical and fractional-order models and estimate the parameters by using the real data of Italy, reported by the World Health Organization. The results show that the fractional-order model has less root-mean-square error than the classical one. Finally, the prediction ability of both of the integer- and fractional-order models is evaluated by using a test data set. The results show that the fractional model provides a closer forecast to the real data.
has issue date	2020-06-24(xsd:dateTime)
bibo:doi	10.1007/s11071-020-05757-6
bibo:pmid	32836806
has license	no-cc
sha1sum (hex)	7b543b99ed47cd7ac54de3dc1da291b952d370ba
schema:url	https://doi.org/10.1007/s11071-020-05757-6
resource representing a document's title	A fractional-order model for the novel coronavirus (COVID-19) outbreak
has PubMed Central identifier	PMC7314430
has PubMed identifier	32836806
schema:publication	Nonlinear Dyn
resource representing a document's body	covid:7b543b99ed47cd7ac54de3dc1da291b952d370ba#body_text
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