Skip to main content
search
Tag

Stanford

Aug 17
Love0

Thank you to our Speakers and Participants – COVID-19 Data Forum II

By Blog

The second COVID-19 Data Forum, co-sponsored by the Stanford Data Science Institute and the R Consortium, was held August 13, 2020. This series of forums brings together experts working to collect and curate data needed to drive scientific research and formulate effective public health responses to the pandemic.

The forum utilized Zoom as the video platform and allowed keynote speakers to present, as well as interact during a Q&A session.

The moderator was Sherri Rose, an associate professor at Stanford University in the Center for Health Policy and Center for Primary Care and Outcomes Research and Co-Director of the Health Policy Data Science Lab. 

Speakers covered topics such as current issues facing researchers during the COVID-19 pandemic such as data sharing or research duplication, how phenotype impacts severity of cases, and data inequality for under-serviced communities. Speakers also answered questions from the moderator and the chat about their work and ways individuals can get involved at all R literacy levels.

Speakers

See the COVID-19 Data Forum site to learn more about future Data Forum series virtual events!

Jul 23
Love0

Beyond Case Counts: Making COVID-19 Clinical Data Available and Useful – Aug 13, 2020

By Blog, Events

Thurs, August 13th, 9am PDT/12pm EDT/18:00 CEST – Register now!

Hosted by the COVID-19 Data Forum/Stanford Data Science Initiative/R Consortium

COVID-19 is the first pandemic to occur in the age of open data. Public health agencies around the world are releasing case counts to the public, and scientists are providing analyses and forecasts in real-time. However, the content of this data has so far been limited to simple metrics like cases, deaths, and hospitalizations at coarse geographic and demographic scales. To drive the next phase of COVID-19, scientists need access to higher-dimensional patient-level data, so we can understand how the virus causes disease, why are some more at risk than others, when and how is transmission occurring, what therapeutics are more likely to work, and what healthcare resources are being used. But sharing such data brings up tremendous challenges in terms of patient privacy and data standardization. The COVID-19 Data Forum, a collaboration between Stanford University and the R Consortium, is hosting the event “Beyond case counts: Making COVID-19 clinical data available and useful” to push the conversation forward on these issues. The event will include talks by representatives from international collaborative teams who are working to collect and share detailed clinical and biological data from individuals with COVID-19. The event will be open to the public, and is part of a continuing series focusing on data-related aspects of the scientific response to the pandemic.


Speakers include:

  • Jenna Reps, Observational Health Data Sciences & Informatics (OHDSI) Consortium /Janssen R&D
  • Andrea Ganna, COVID-19 Host Genetics Initiative/Harvard Medical School/Finland Institute for Molecular Medicine
  • Ken Massey, EndPandemic National Data Consortium/Saama Technologies
  • Ryan Tibshirani, DELPHI epidemic forecasting group/Dept of Statistics, Carnegie Mellon University

Registration and more info: https://covid19-data-forum.org

May 18
Love0

COVID-19 Data Forum – Co-Sponsored with Stanford Data Science Institute – Heavily Attended

By Blog

The first COVID-19 Data Forum, co-sponsored by the Stanford Data Science Institute and the R Consortium, was held May 14, 2020. The forum used Zoom as a way to connect remote specialists, present information, and conduct a Q&A session so that participants could ask questions and give opinions.

UPDATED – Full video recording here

Close to 200 people attended, watching a range of experts cover a level of detail around COVID-19 that is not available through newspapers, and asking questions covering science and policy.

From the COVID-19 Data Forum site:

The COVID-19 pandemic has challenged science and society to an unprecedented degree. Human lives and the future of our society depend on the response. That response, in turn, depends critically on data. This data must be as complete and accurate as possible; easily and flexibly accessible, and equipped to communicate effectively with decision-makers and the public.

The COVID-19 Data Forum is a project to bring together those involved with relevant data in a series of multidisciplinary online meetings discussing current resources, needed enhancements, and the potential for co-operative efforts.

Speakers (full slides for each presentation available soon)

  • Orhun Aydin, Researcher and Product Engineer, ESRI
  • Ryan Hafen, data scientist consultant with Preva Group, and adjunct assistant professor, Purdue University
  • Alison L. Hill, Research Fellow and independent principal investigator at Harvard’s Program for Evolutionary Dynamics.
  • Noam Ross, Senior Research Scientist, EcoHealth Alliance

See the COVID-19 Data Forum site for information on upcoming Data Forum series virtual events!

May 07
Love0

Stanford Data Science Institute Joins R Consortium in Sponsoring COVID-19 Data Forum – Join Us!

By Announcement, Blog

The Stanford Data Science Institute, which aims to give Stanford faculty and students the tools, skills and understanding they need to do cutting-edge research, is joining with the R Consortium to build the COVID-19 Data Forum series.

The first meeting is May 14, 12:00 pm PT, California time.

UPDATED: Full video recording available here:

The COVID-19 Data Forum series is an ongoing set of online meetings that connect multidisciplinary topic experts to focus on data-related aspects of the COVID-19 pandemic modeling process such as data access and sharing, essential data resources for modeling and how we can best support decision making. 

The first half of the meeting is a public webinar and all are welcome to attend.

Connect with R Consortium via email (info@rconsortium.org) or on Twitter @RConsortium

COVID-19 Data Forum

Close Menu