SARS-CoV-2 und COVID19 -- genomische Epidemilogie in Echtzeit
Richard Neher
Biozentrum, University of Basel
slides at
neherlab.org/202011_DigitalHumanities.html
BBC
Data summarized by Ian MacKay
Data summarized by Ian MacKay
Data summarized by Ian MacKay
Data summarized by Ian MacKay
Data summarized by Ian MacKay
by Trevor Bedford
by Trevor Bedford
Tracking diversity and spread of SARS-CoV-2 in Nextstrain
Virus genomes change rapidly through time
A/Brisbane/100/2014
GGATAATTCTATTAACCATGAAGACTAT
C
ATTGCTTT...
A/Brisbane/1000/2015
GGATAATTCTATTAACCATGAAGACTAT
T
ATTGCTTT...
A/Brisbane/1/2017
GGATAATTCTATTAACCATGAAGACTAT
C
ATTGCTTT...
... hundreds of thousands of sequences...
Genome sequences record the spread of pathogens
in SARS-CoV-2 a new mutation accumulates about every 2 weeks
images by Trevor Bedford
Available data on Jan 26
Early genomes differed by only a few mutations, suggesting very recent emergence
nextstrain.org/ncov/2020-01-26
→ the closest to "real-time" we have experienced so far...
Figure by James Hadfield/Emma Hodcroft
Turning data into actionable insights
hundreds of new sequences every day
more than 200k sequences right now
comprehensive analysis require hours to days to complete
→ requires continuous analysis and easy dissemination
→ interpretable and intuitive visualization
nextstrain.org
joint project with Trevor Bedford & his lab
Diversified into multiple global variants. Groups 20A/B/C have taken over.
Large scale spread of the virus
Regional variants emerged over the summer
Spread of a variant through travel and tourism
Genomic analysis as complement to contact tracing
Genomic analysis as complement to contact tracing
Investigation of hospital outbreaks
Lucey et al, Clinical Infectious Diseases, 2020
Influenza vaccine strain selection schedule
Klingen and McHardy, Trends in Microbiology
Herausforderungen und Zusammenfassung
Offener Datenaustausch und Urheberschaft stehen immer wieder im Konflikt
Analysen sind nicht einfach zu interpretieren
Grosse Datenmengen, anspruchsvolle Methoden
Zeitnahe und automatisierte Analysen sind essentiell
Dennoch: Wir sollten Möglichkeiten, nicht Herausfordungen, sehen!
Integration in die Routine-Surveillance
Acknowledgments
Trevor Bedford and his lab -- terrific collaboration since 2014
especially James Hadfield, Emma Hodcroft, Ivan Aksamentov, Moira Zuber, and Tom Sibley
Data we analyze are contributed by scientists from all over the world
Data are shared and curated by GISAID
Acknowledgments
Emma Hodcroft
Moira Zuber
Inaki Comas
Fernando Gonzales
Tanja Stadler
Sarah Nadeau
Tim Vaughan
Jesse Bloom
David Veesler