About: Covid-19 Incidence Rate Evolution Modeling using Dual Wave Gaussian-Lorentzian Composite Functions

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Covid-19 Incidence Rate Evolution Modeling using Dual Wave Gaussian-Lorentzian Composite Functions 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
title	Covid-19 Incidence Rate Evolution Modeling using Dual Wave Gaussian-Lorentzian Composite Functions
Creator	Poomari, Radhakrishnan
source	MedRxiv
abstract	Modeling the evolution of Covid-19 incidence rate is critical to deciding and assessing non-medical intervention strategies that can lead to successful containment of the pandemic. This research presents a mathematical model to empirically assess measures related to various pandemic containment strategies, their similarities and a probabilistic estimate on the evolution of Covid-19 incidence rates. The model is built on the principle that, the exponential rise and decay of the number of confirmed Covid-19 infections can be construed as a set of concurrent non-linear waves. These waves can be characterized by a linear combination of Gaussian and Cauchy Lorentz functions collectively termed as Gaussian-Lorentzian Composite (GLC) function. The GLC function is used for non-linear approximation of officially confirmed Covid-19 incidence rates in each country. Results of fitting GLC based models to incidence rate trends of 20 different countries proves that the models can empirically explain the growth and decay trajectory Covid-19 infections in a given population.
has issue date	2020-06-09(xsd:dateTime)
bibo:doi	10.1101/2020.06.07.20124966
has license	medrxiv
sha1sum (hex)	84dfb5439055b00e6bd646fa5ee564fced36fc91
schema:url	https://doi.org/10.1101/2020.06.07.20124966
resource representing a document's title	Covid-19 Incidence Rate Evolution Modeling using Dual Wave Gaussian-Lorentzian Composite Functions
resource representing a document's body	covid:84dfb5439055b00e6bd646fa5ee564fced36fc91#body_text
is schema:about of	named entity 'GLC' named entity 'mathematical model' named entity 'similarities' named entity 'empirically' named entity 'termed' »more»

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software