Data sharing during public health emergencies


Richard Neher
Biozentrum, University of Basel


slides at neherlab.org/201709_BaselLife.html

data owner ↔ public interest

2013-2015 West African Ebola virus outbreak

By CDC Global - WHO in PPE
By Chris55
Two years later, we have a detailed understanding of the outbreak. Why did this take so long?

Sharing of Ebola virus sequences

  • Baize et al.: Samples collected in March 2014, sequences in GenBank within a month
  • Gire et al.: released data as it was generated
  • Followed by a long gap...
  • Early insights into transmission dynamics are important
  • Sharing has to be immediate -- not upon publication
Yozwiak et al
Quick et al

Recurring problem

  • 2002 Severe acute respiratory syndrome (SARS)
  • 2003 H5N1 influenza outbreak. Some countries stopped sharing any data
  • 2013-2015 Ebola virus outbreak in West Africa

  • 2014-2016 Zika Virus outbreak: Controversies about attribution and reuse
  • 2014- H7N9 influenza outbreak: Controversies about attribution and reuse

Different disease -- different scientists and institutions.

→Lessons need to be relearned.

Barriers to data sharing: scientists

  • Privacy of study participants
  • Fear of being scooped/ensure maximal return
  • Secondary analysis perceived as freeloading: "data parasites"
  • Don't want to be second guessed
  • Release and curation is laborious
  • Sloppy records
Also see Smith et al, F1000 2016

Barriers to data sharing: organizations and governments

  • Economic consequences of outbreaks (tourism, agriculture)
  • Conflicts between high and low/middle income countries
  • Concerns about IP and commercial exploitation
  • Legislative/regulatory barriers
See also: van Panhius et al, BMC Public health 2014

Overcoming Barriers

Open vs restricted sharing

  • Alternatives to GenBank: GenBank is "public domain", no requirement to credit data producers
  • GISAID/EpiFlu: sign-up and agree to terms and conditions
  • virological.org: Platform for sharing and discussing molecular epidemiology
  • Explicit data reuse terms
  • Outline planned projects in white-paper
  • Caveat: Very difficult to enforce...
See Bogner et al, 2006

Building Trust

  • Peter Bogner coordinated Influenza data sharing
  • Andrew Rambaut coordinated Ebola virus data sharing
  • During the EBV outbreak, WHO and journals explicitly encouraged data sharing
See also Smith et al, F1000 2016

Make sharing easy and provide incentives!

Grubaugh et al, samples from Florida
Metsky et al, sample from the Caribbean

nextstrain.org

nextstrain.org

  • Global analysis provides context for new sequences
  • Once nextstrain became the largest collection of Ebola/Zika sequences, everybody wanted their sequences on nextstrain
  • We take care to highlight the scientists contributing data
  • Link to original source, rather than reshare
Open source: github.com/nextstrain

Outlook

  • Response has to be fast
    → pre-existing trusted framework to share data
  • Wider acceptance of preprints should help
    → establishes priority and a citation hook
  • We need incentives for high quality data sets
  • We need better ways to credit data producers
    → data citations
  • Not only data: Open source code and analysis pipelines

nextstrain.org

  • Trevor Bedford
  • Colin Megill
  • Pavel Sagulenko
  • Sidney Bell
  • James Hadfield
  • Wei Ding