About: Revealing COVID-19 Transmission by SARS-CoV-2 Genome Sequencing and Agent Based Modelling

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Revealing COVID-19 Transmission by SARS-CoV-2 Genome Sequencing and Agent Based Modelling
Creator	Kok, Jen Eden, John-Sebastian Sorrell, Tania Sintchenko, Vitali Chen, Sharon C-A Holmes, Edward Basile, Kerri Byun, Roy Carter, Ian Dwyer, Dominic Maddocks, Susan O'sullivan, Matthew Rockett, Rebecca Prokopenko, Mikhail Gall, Mailie Gray, Karen-Ann Lam, Connie Sadsad, Rosemarie Timms, Verlaine Draper, Jenny Arnott, Bachmann, Nathan Chang, Sheryl Sim, Eby
Source	BioRxiv
abstract	Community transmission of the new coronavirus SARS-CoV-2 is a major public health concern that remains difficult to assess. We present a genomic survey of SARS-CoV-2 from a during the first 10 weeks of COVID-19 activity in New South Wales, Australia. Transmission events were monitored prospectively during the critical period of implementation of national control measures. SARS-CoV-2 genomes were sequenced from 209 patients diagnosed with COVID-19 infection between January and March 2020. Only a quarter of cases appeared to be locally acquired and genomic-based estimates of local transmission rates were concordant with predictions from a computational agent-based model. This convergent assessment indicates that genome sequencing provides key information to inform public health action and has improved our understanding of the COVID-19 evolution from outbreak to epidemic.
has issue date	2020-04-24(xsd:dateTime)
bibo:doi	10.1101/2020.04.19.048751
has license	biorxiv
sha1sum (hex)	e3c03a0cf150672d2cfdf960a3dbde9d5782b6e2
schema:url	https://doi.org/10.1101/2020.04.19.048751
resource representing a document's title	Revealing COVID-19 Transmission by SARS-CoV-2 Genome Sequencing and Agent Based Modelling
schema:publication	bioRxiv
resource representing a document's body	covid:e3c03a0cf150672d2cfdf960a3dbde9d5782b6e2#body_text
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