About: A model for 2019-nCoV infection with treatment

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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	A model for 2019-nCoV infection with treatment
Creator	Al Basir, Fahad Chatterjee, Amar
topic	covid:4f79b4f685424d235bb6e1e2402c87424307afdd#this
Source	MedRxiv
abstract	The current emergence of coronavirus (2019-nCoV or COVID-19) puts the world in threat. 2019-nCoV remains the outbreak of SARS-CoV 2002-2003. The structural research on the receptor recognition by SARS-CoV has identified the key interactions between SARS-CoV spike protein and its host receptor, also known as angiotensin converting enzyme 2 (ACE2). It controls both the cross-species and human-to-human transmissions of SARS-CoV. In this article, we have considered the infection dynamics of SARS-CoV-2 infection in the acute stage. Our aim is to propose and analyse a mathematical model for investigating the effect of CTL responses over the viral mutation to control the viral infection when a post-infection vaccine is administered at regular intervals. Dynamics of the system with and without impulses have been analysed using qualitative theory. Main findings are supported through numerical simulations.
has issue date	2020-04-29(xsd:dateTime)
bibo:doi	10.1101/2020.04.24.20077958
has license	medrxiv
sha1sum (hex)	4f79b4f685424d235bb6e1e2402c87424307afdd
schema:url	https://doi.org/10.1101/2020.04.24.20077958
resource representing a document's title	A model for 2019-nCoV infection with treatment
resource representing a document's body	covid:4f79b4f685424d235bb6e1e2402c87424307afdd#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/4f79b4f685424d235bb6e1e2402c87424307afdd
is schema:about of	named entity 'ACE2' named entity 'infection' named entity 'converting' named entity 'outbreak' named entity 'supported' named entity 'USING' named entity 'DYNAMICS' named entity 'POST' named entity '2019-NCOV' named entity 'RESEARCH' named entity 'REMAINS' named entity 'VIRAL INFECTION' named entity 'INTERACTIONS' named entity 'AIM' named entity 'CONSIDERED' named entity 'IDENTIFIED' named entity 'aim' named entity 'angiotensin' named entity 'controls' named entity 'CTL' named entity 'Main' named entity 'SARS-CoV' named entity 'spike' named entity 'receptor' named entity 'protein' named entity 'control' named entity 'mutation' named entity 'coronavirus' named entity 'ACE2' named entity 'numerical simulations' named entity 'SARS-CoV-2' named entity 'infection' named entity 'peer review' named entity 'viral infection' named entity 'cell membrane' named entity 'preprint' named entity 'hydrolyzed' named entity 'WHO' named entity 'SARS-CoV-2' named entity 'maximum concentration' named entity 'province of China' named entity 'infection rate' named entity 'receptor' named entity 'epithelial cells' named entity 'vaccination' named entity 'preprint' named entity 'endemic equilibrium' named entity 'infection' named entity 'Floquet theory' named entity 'infection' named entity 'pathogen' named entity 'viruses' named entity 'ACE2' named entity 'CTL' named entity 'infection' named entity 'CTL' named entity 'infection' named entity 'periodic orbit' named entity 'fatigue' named entity 'virus' named entity 'SARS-CoV-2' named entity 'COVID-19' named entity 'vomiting' named entity 'DPP4' named entity 'virus' named entity 'antibodies' named entity 'basic reproduction number' named entity 'COVID' named entity 'viral entry' named entity 'SARS-CoV-2' named entity 'periodic orbit' named entity 'ACE2' named entity 'precursor cells' named entity 'COVID 19' named entity 'antibody' named entity 'preprint' named entity 'vaccination' named entity 'antibody' named entity 'ACE2 receptor' named entity 'preprint' named entity 'endemic' named entity 'infection rate'

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