About: A mathematical model of the COVID-19 pandemic dynamics with dependent variable infection rate: Application to South Korea

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

About: A mathematical model of the COVID-19 pandemic dynamics with dependent variable infection rate: Application to South Korea 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	A mathematical model of the COVID-19 pandemic dynamics with dependent variable infection rate: Application to South Korea
Creator	Cesmelioglu, Aycil Kuttler, Kenneth Shillor, Meir Spagnuolo, Anna
source	ArXiv
abstract	This work constructs, analyzes, and simulates a new SEIR-type model for the dynamics and potential control of the current coronavirus (COVID-19) pandemic. It has a compartmental structure and a differential inclusion for a variable infection rate. The novelty in this work is three-fold. First, the population is separated, according to compliance with the disease control directives (shelter-in-place, masks/face coverings, physical distancing, etc.), into those who fully follow the directives and those who only partially comply with the directives or are necessarily mobile. This allows the assessment of the overall effectiveness of the control measures and the impact of their relaxing or tightening on the disease spread. Second, the model treats the infection rate as an unknown and keeps track of how it changes, due to virus mutations and saturation effects, via a differential inclusion. Third, by introducing randomness to some of the system coefficients, we study the model's sensitivity to these parameters and provide bounds and intervals of confidence for the model simulations. As a case study, the pandemic outbreak in South Korea is simulated. The model parameters were found by minimizing the deviation of the model prediction from the reported data. The simulations show that the model captures the pandemic dynamics in South Korea accurately, which provides confidence in the model predictions and its future use.
has issue date	2020-07-27(xsd:dateTime)
has license	arxiv
sha1sum (hex)	1527aeb20cea98292c3d3c26da9fc07f69bf1f87
resource representing a document's title	A mathematical model of the COVID-19 pandemic dynamics with dependent variable infection rate: Application to South Korea
resource representing a document's body	covid:1527aeb20cea98292c3d3c26da9fc07f69bf1f87#body_text
is schema:about of	named entity 'SYSTEM' named entity 'USE' named entity 'disease control' named entity 'coronavirus pandemic' named entity 'infection rate' »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