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MIT COVID-19 Datathon: data without boundaries
  1. Eva M Luo1,2,
  2. Sarah Newman3,
  3. Maelys Amat4,
  4. Marie-Laure Charpignon5,
  5. Erin R Duralde4,
  6. Shrey Jain6,
  7. Aaron R Kaufman7,
  8. Igor Korolev8,
  9. Yuan Lai9,
  10. Barbara D Lam4,
  11. Megan Lipcsey4,
  12. Alfonso Martinez10,
  13. Oren J Mechanic1,11,
  14. Jack Mlabasati4,
  15. Liam G McCoy6,
  16. Freddy T Nguyen12,
  17. Matthew Samuel13,
  18. Eric Yang10,
  19. Leo Anthony Celi1,4,14
  1. 1 Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center Inc, Boston, Massachusetts, USA
  2. 2 OB/GYN, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
  3. 3 metaLAB, Berkman Klein Center, Harvard University, Cambridge, Massachusetts, USA
  4. 4 Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
  5. 5 Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  6. 6 Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
  7. 7 New York University—Abu Dhabi Campus, Abu Dhabi, UAE
  8. 8 HealthDSA: Health Data Science and Analytics Community, Boston, Massachusetts, USA
  9. 9 Urban Science and Planning, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  10. 10 Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  11. 11 Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
  12. 12 Massachusetts Institute of Technology, Boston, Massachusetts, USA
  13. 13 Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
  14. 14 Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  1. Correspondence to Dr Eva M Luo, OB/GYN, Harvard Medical Faculty Physicians at Beth Israel Deaconess Medical Center Inc, Boston, MA 02215, USA; eluo1{at}bidmc.harvard.edu

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The COVID-19 virus is a formidable global threat, impacting all aspects of society and exacerbating the existing inequities of our current social systems.1 2 As we battle the virus across multiple fronts, data are critical for understanding this disease and for coordinating an effective global response. Given the current digitisation of so many aspects of life, we are amassing data that can be extrapolated and analysed for the effective forecasting, prevention and treatment of COVID-19. With responsible stewardship, the tools and data-driven solutions currently in development for the COVID-19 pandemic will serve in the present while providing a much-needed foundation for a data-based response to future outbreaks and disasters.

In response to COVID-19, and using data generated thus far, groups at the Massachusetts Institute of Technology (MIT) in partnership with the American Civil Liberties Union (ACLU) of Massachusetts, Google Cloud, Beth Israel Deaconess Medical Center (BIDMC) Innovations Group and Harvard Medical Faculty Physicians at BIDMC came together to host the MIT Challenge COVID-19 Datathon (COVID-19 Datathon) from 10–16 May 2020. A ‘datathon’ adopts the ‘hackathon’ model, with a focus on data and data science methodologies, which promotes collaboration, design thinking and problem solving.3 In a typical hackathon, participants with disparate but complementary backgrounds work together in small groups for a prescribed and intensive ‘sprint’, typically over the course of one weekend, to develop a new concept, product or business idea. Subject matter expert ‘mentors’' oversee and advise the teams. At the conclusion of the event, the teams present to a panel of judges. Winners are selected and are typically awarded seed funding. …

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Footnotes

  • Twitter @EvaMLuo, @@shreydjain13, @freddytn

  • Contributors All authors listed meet ICMJE criteria for authorship. All authors listed contributed to the planning, writing and editing of this manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Map disclaimer The depiction of boundaries on the map(s) in this article do not imply the expression of any opinion whatsoever on the part of BMJ (or any member of its group) concerning the legal status of any country, territory, jurisdiction or area or of its authorities. The map(s) are provided without any warranty of any kind, either express or implied.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.