About: Prediction of the COVID-19 outbreak based on a realistic stochastic model

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

About: Prediction of the COVID-19 outbreak based on a realistic stochastic model 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	Prediction of the COVID-19 outbreak based on a realistic stochastic model
Creator	Zhang, Yuan Cai, Zhenghao Hu, Wenjie Sun, Jiarui You, Chong »more»
source	MedRxiv
abstract	The current outbreak of coronavirus disease 2019 (COVID-19) has become a global crisis due to its quick and wide spread over the world. A good understanding of the dynamic of the disease would greatly enhance the control and prevention of COVID-19. However, to the best of our knowledge, the unique features of the outbreak have limited the applications of all existing models. In this paper, a novel stochastic model is proposed which aims to account for the unique transmission dynamics of COVID-19 and capture the effects of intervention measures implemented in Mainland China. We find that, (1) instead of aberration, there is a remarkable amount of asymptomatic individuals, (2) an individual with symptoms is approximately twice more likely to pass the disease to others than that of an asymptomatic patient, (3) the transmission rate has reduced significantly since the implementation of control measures in Mainland China, (4) it is expected that the epidemic outbreak would be contained by early March in the the selected provinces and cities.
has issue date	2020-03-13(xsd:dateTime)
bibo:doi	10.1101/2020.03.10.20033803
has license	medrxiv
sha1sum (hex)	f99704d3a52a14737288ddaa3abf387bad364fe8
schema:url	https://doi.org/10.1101/2020.03.10.20033803
resource representing a document's title	Prediction of the COVID-19 outbreak based on a realistic stochastic model
resource representing a document's body	covid:f99704d3a52a14737288ddaa3abf387bad364fe8#body_text
is schema:about of	named entity 'PEER REVIEW' named entity 'GOOD' named entity 'KNOWLEDGE' named entity '282' covid:arg/f99704d3a52a14737288ddaa3abf387bad364fe8 »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