About: A simple Stochastic SIR model for COVID 19 Infection Dynamics for Karnataka: Learning from Europe

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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 simple Stochastic SIR model for COVID 19 Infection Dynamics for Karnataka: Learning from Europe
Creator	Narayana, Sujay Prasad, R Simha, Ashutosh
Source	ArXiv
abstract	In this short note we model the region-wise trends of the evolution to COVID-19 infections using a stochastic SIR model. The SIR dynamics are expressed using /textit{It/^o-stochastic differential equations}. We first derive the parameters of the model from the available daily data from European regions based on a 24-day history of infections, recoveries and deaths. The derived parameters have been aggregated to project future trends for the Indian subcontinent, which is currently at an early stage in the infection cycle. The projections are meant to serve as a guideline for strategizing the socio-political counter measures to mitigate COVID-19.
has issue date	2020-03-26(xsd:dateTime)
has license	arxiv
sha1sum (hex)	f24445e5b4c855ab11bf858988810895d302cd5a
resource representing a document's title	A simple Stochastic SIR model for COVID 19 Infection Dynamics for Karnataka: Learning from Europe
resource representing a document's body	covid:f24445e5b4c855ab11bf858988810895d302cd5a#body_text
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