About: Agent-Level Pandemic Simulation (ALPS) for Analyzing Effects of Lockdown Measures

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About: Agent-Level Pandemic Simulation (ALPS) for Analyzing Effects of Lockdown Measures Goto Sponge NotDistinct Permalink

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	Agent-Level Pandemic Simulation (ALPS) for Analyzing Effects of Lockdown Measures
Creator	Srivastava, Anuj
source	ArXiv
abstract	This paper develops an agent-level simulation model, termed ALPS, for simulating the spread of an infectious disease in a confined community. The mechanism of transmission is agent-to-agent contact, using parameters reported for Corona COVID-19 pandemic. The main goal of the ALPS simulation is analyze effects of preventive measures -- imposition and lifting of lockdown norms -- on the rates of infections, fatalities and recoveries. The model assumptions and choices represent a balance between competing demands of being realistic and being efficient for real-time inferences. The model provides quantification of gains in reducing casualties by imposition and maintenance of restrictive measures in place.
has issue date	2020-04-25(xsd:dateTime)
has license	arxiv
sha1sum (hex)	1bca8f0eae80a8e86c7e277413a6a0b067b3a04c
resource representing a document's title	Agent-Level Pandemic Simulation (ALPS) for Analyzing Effects of Lockdown Measures
resource representing a document's body	covid:1bca8f0eae80a8e86c7e277413a6a0b067b3a04c#body_text
is schema:about of	named entity 'norms' named entity 'quantification' named entity 'model assumptions' named entity 'COVID-19' named entity 'preventive' »more»

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