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
GGATAATTCTATTAACCATGAAGACTATCATTGCTTT...

A/Brisbane/1000/2015
GGATAATTCTATTAACCATGAAGACTATTATTGCTTT...

A/Brisbane/1/2017
GGATAATTCTATTAACCATGAAGACTATCATTGCTTT...

... 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 M√∂glichkeiten, 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