About: Changing transmission dynamics of COVID-19 in China: a nationwide population-based piecewise mathematical modelling study

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

About: Changing transmission dynamics of COVID-19 in China: a nationwide population-based piecewise mathematical modelling study 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
has title	Changing transmission dynamics of COVID-19 in China: a nationwide population-based piecewise mathematical modelling study
Creator	Jin, Zhen Chen, Yue Su, Qing Zhao, Zheng Lin, Wei Ward, Michael Huang, Jiaqi Hong, Dong, Bowen Hou, Jiawen Hu, Jian Ji, Boyun Tu, Wei Wang, Wenge Xiao, Shuang Zhang, Zhijie
Source	MedRxiv
abstract	Background: The first case of COVID-19 atypical pneumonia was reported in Wuhan, China on December 1, 2019. Since then, at least 33 other countries have been affected and there is a possibility of a global outbreak. A tremendous amount of effort has been made to understand its transmission dynamics; however, the temporal and spatial transmission heterogeneity and changing epidemiology have been mostly ignored. The epidemic mechanism of COVID-19 remains largely unclear. Methods: Epidemiological data on COVID-19 in China and daily population movement data from Wuhan to other cities were obtained and analyzed. To describe the transmission dynamics of COVID-19 at different spatio-temporal scales, we used a three-stage continuous-time Susceptible-Exposed-Infectious-Recovered (SEIR) meta-population model based on the characteristics and transmission dynamics of each stage: 1) local epidemic from December 1, 2019 to January 9, 2020; 2) long-distance spread due to the Spring Festival travel rush from January 10 to 22, 2020; and 3) intra-provincial transmission from January 23, 2020 when travel restrictions were imposed. Together with the basic reproduction number (R_0) for mathematical modelling, we also considered the variation in infectivity and introduced the controlled reproduction number (R_c) by assuming that exposed individuals to be infectious; we then simulated the future spread of COVID across Wuhan and all the provinces in mainland China. In addition, we built a novel source tracing algorithm to infer the initial exposed number of individuals in Wuhan on January 10, 2020, to estimate the number of infections early during this epidemic. Findings: The spatial patterns of disease spread were heterogeneous. The estimated controlled reproduction number (R_c) in the neighboring provinces of Hubei province were relatively large, and the nationwide reproduction number (except for Hubei) ranged from 0.98 to 2.74 with an average of 1.79 (95% CI 1.77-1.80). Infectivity was significantly greater for exposed than infectious individuals, and exposed individuals were predicted to have become the major source of infection after January 23. For the epidemic process, most provinces reached their epidemic peak before February 10, 2020. It is expected that the maximum number of infections will be approached by the end of March. The final infectious size is estimated to be about 58,000 for Wuhan, 20,800 for the rest of Hubei province, and 17,000 for the other provinces in mainland China. Moreover, the estimated number of the exposed individuals is much greater than the officially reported number of infectious individuals in Wuhan on January 10, 2020. Interpretation: The transmission dynamics of COVID-19 have been changing over time and were heterogeneous across regions. There was a substantial underestimation of the number of exposed individuals in Wuhan early in the epidemic, and the Spring Festival travel rush played an important role in enhancing and accelerating the spread of COVID-19. However, China's unprecedented large-scale travel restrictions quickly reduced R_c. The next challenge for the control of COVID-19 will be the second great population movement brought by removing these travel restrictions.
has issue date	2020-03-30(xsd:dateTime)
bibo:doi	10.1101/2020.03.27.20045757
has license	medrxiv
sha1sum (hex)	c53ee84efe42f2a1273d654cdb30a2cf5f14ecd0
schema:url	https://doi.org/10.1101/2020.03.27.20045757
resource representing a document's title	Changing transmission dynamics of COVID-19 in China: a nationwide population-based piecewise mathematical modelling study
resource representing a document's body	covid:c53ee84efe42f2a1273d654cdb30a2cf5f14ecd0#body_text
is schema:about of	named entity 'temporal' named entity 'UNCLEAR' named entity 'WUHAN' named entity 'UNDERSTAND' named entity 'COVID-19' named entity 'nationwide' named entity 'COVID-19' named entity 'atypical pneumonia' named entity 'COVID-19' named entity 'Wuhan' named entity 'COVID-19' named entity 'piecewise' named entity 'mathematical modelling' named entity 'COVID-19' named entity 'epidemic' named entity 'central China' named entity 'MERS' named entity 'correlation' named entity 'medRxiv' named entity 'Wuhan' named entity 'Wuhan' named entity 'medRxiv' named entity 'preprint' named entity 'preprint' named entity 'preprint' named entity 'March 30, 2020' named entity 'Hubei' named entity 'time evolution' named entity 'Wuhan' named entity 'epidemic' named entity 'copyright holder' named entity 'Wuhan' named entity 'preprint' named entity 'asymptomatic' named entity 'infection' named entity 'epidemic' named entity 'March 30, 2020' named entity 'SARS-CoV-2' named entity 'Hubei Province' named entity 'correlation' named entity 'medRxiv' named entity 'preprint' named entity 'Wuhan' named entity 'COVID' named entity 'COVID' named entity 'Wuhan' named entity 'copyright holder' named entity 'Lunar New Year' named entity 'travel ban' named entity 'Wuhan' named entity 'March 30, 2020' named entity 'notifiable infectious disease' named entity 'preprint' named entity '95% CI' named entity 'preprint' named entity 'Wuhan' named entity 'March 30, 2020' named entity 'Wuhan' named entity 'Wuhan' named entity 'coronavirus' named entity 'lockdown' named entity 'Wuhan' named entity 'public health surveillance' named entity 'March 30, 2020' named entity 'medRxiv' named entity 'Wuhan' named entity 'differential equations' named entity 'Macau' named entity 'Taiwan' named entity 'CC-BY-NC-ND 4.0'

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 © 2009-2024 OpenLink Software