About: Spatially Explicit Modeling of 2019-nCoV Epidemic Trend based on Mobile Phone Data in Mainland China

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

About: Spatially Explicit Modeling of 2019-nCoV Epidemic Trend based on Mobile Phone Data in Mainland China 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	Spatially Explicit Modeling of 2019-nCoV Epidemic Trend based on Mobile Phone Data in Mainland China
Creator	Wei, Tao Tan, Xiaoyue Xu, Shuai Jia, Pengfei Quan, Zhenxian »more»
source	MedRxiv
abstract	IAs of February 11, 2020, all prefecture-level cities in mainland China have reported confirmed cases of 2019 novel coronavirus (2019-nCoV), but the city-level epidemical dynamics is unknown. The aim of this study is to model the current dynamics of 2019-nCoV at city level and predict the trend in the next 30 days under three possible scenarios in mainland China. We developed a spatially explicit epidemic model to consider the unique characteristics of the virus transmission in individual cities. Our model considered that the rate of virus transmission among local residents is different from those with Wuhan travel history due to the self-isolation policy. We introduced a decay rate to quantify the effort of each city to gradually control the disease spreading. We used mobile phone data to obtain the number of individuals in each city who have travel history to Wuhan. This city-level model was trained using confirmed cases up to February 10, 2020 and validated by new confirmed cases on February 11, 2020. We used the trained model to predict the future dynamics up to March 12, 2020 under different scenarios: the current trend maintained, control efforts expanded, and person-to-person contact increased due to work resuming. We estimated that the total infections in mainland China would be 72172, 54348, and 149774 by March 12, 2020 under each scenario respectively. Under the current trend, all cities will show the peak point of daily new infections by February 21. This date can be advanced to February 14 with control efforts expanded or postponed to February 26 under pressure of work resuming. Except Wuhan that cannot eliminate the disease by March 12, our model predicts that 95.4%, 100%, and 75.7% cities will have no new infections by the end of February under three scenarios. The spatial pattern of our prediction could help the government allocate resources to cities that have a more serious epidemic in the next 30 days.
has issue date	2020-02-11(xsd:dateTime)
bibo:doi	10.1101/2020.02.09.20021360
has license	medrxiv
sha1sum (hex)	2913d91f13fd59c698f68ba63008d8e0550c0607
schema:url	https://doi.org/10.1101/2020.02.09.20021360
resource representing a document's title	Spatially Explicit Modeling of 2019-nCoV Epidemic Trend based on Mobile Phone Data in Mainland China
resource representing a document's body	covid:2913d91f13fd59c698f68ba63008d8e0550c0607#body_text
is schema:about of	named entity 'travel' named entity 'Our' named entity 'history' named entity '2019-nCoV' named entity 'MODELING' »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