About: Extended SEIQR type model for COVID-19 epidemic and data analysis

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

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Extended SEIQR type model for COVID-19 epidemic and data analysis
Creator	Sharma, Swarnali Volpert, Vitaly Banerjee, Malay
source	MedRxiv
abstract	An extended SEIQR type model is considered in order to model the COVID-19 epidemic. It contains the classes of susceptible individuals, exposed, infected symptomatic and asymptomatic, quarantined, hospitalized and recovered. The basic reproduction number and the final size of epidemic are determined. The model is used to fit available data for some European countries. A more detailed model with two different subclasses of susceptible individuals is introduced in order to study the influence of social interaction on the disease progression. The coefficient of social interaction $K$ characterizes the level of social contacts in comparison with complete lockdown (K=0) and the absence of lockdown (K=1). The fitting of data shows that the actual level of this coefficient in some European countries is about 0.1, characterizing a slow disease progression. A slight increase of this value in the autumn can lead to a strong epidemic burst.
has issue date	2020-08-12(xsd:dateTime)
bibo:doi	10.1101/2020.08.10.20171439
has license	medrxiv
sha1sum (hex)	c19b1d67038a10ff10f9e4c3b240b28a0e8df148
schema:url	https://doi.org/10.1101/2020.08.10.20171439
resource representing a document's title	Extended SEIQR type model for COVID-19 epidemic and data analysis
resource representing a document's body	covid:c19b1d67038a10ff10f9e4c3b240b28a0e8df148#body_text
is schema:about of	named entity 'coefficient' named entity 'CLASSES' named entity 'ABSENCE OF' named entity 'INCREASE' named entity 'SYMPTOMATIC' »more»

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