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Genomic epidemiology of SARS-CoV-2 in Guangdong Province, China
Preprint
in En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-20047076
Journal article
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A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See journal article
ABSTRACT
COVID-19 is caused by the SARS-CoV-2 coronavirus and was first reported in central China in December 2019. Extensive molecular surveillance in Guangdong, Chinas most populous province, during early 2020 resulted in 1,388 reported RNA positive cases from 1.6 million tests. In order to understand the molecular epidemiology and genetic diversity of SARS-CoV-2 in China we generated 53 genomes from infected individuals in Guangdong using a combination of metagenomic sequencing and tiling amplicon approaches. Combined epidemiological and phylogenetic analyses indicate multiple independent introductions to Guangdong, although phylogenetic clustering is uncertain due to low virus genetic variation early in the pandemic. Our results illustrate how the timing, size and duration of putative local transmission chains were constrained by national travel restrictions and by the provinces large-scale intensive surveillance and intervention measures. Despite these successes, COVID-19 surveillance in Guangdong is still required as the number of cases imported from other countries is increasing. HighlightsO_LI1.6 million molecular diagnostic tests identified 1,388 SARS-CoV-2 infections in Guangdong Province, China, by 19th March 2020 C_LIO_LIVirus genomes can be recovered using a variety of sequencing approaches from a range of patient samples. C_LIO_LIGenomic analyses reveal multiple virus importations into Guangdong Province, resulting in genetically distinct clusters that require careful interpretation. C_LIO_LILarge-scale epidemiological surveillance and intervention measures were effective in interrupting community transmission in Guangdong C_LI
cc_by_nc_nd
Full text:
1
Collection:
09-preprints
Database:
PREPRINT-MEDRXIV
Type of study:
Diagnostic_studies
/
Observational_studies
Language:
En
Year:
2020
Document type:
Preprint