About the Forum
The COVID-19 pandemic is challenging science and society to an unprecedented degree. Human lives and the future of our society are at stake. Containing the virus and flattening the curve" of the pandemic depend on mounting a strong, coordinated, scientifically-informed public health response which in turn ultimately depends on having complete and accurate data from multiple data sources.
The COVID-19 Data Forum is an ongoing series of multidisciplinary webinars and online meetings for topic experts to discuss data-related aspects of the scientific response to the pandemic. The Forum is a joint project of the R Consortium and the Stanford Data Science Institute. We host recurring topical webinars that are free and open to the public.
The Forum places particular emphasis on being open to all relevant interested groups and including a wide range of expertise. With respect to computing, the Forum considers all useful tools, languages and environments. We hope that the COVID-19 Data Forum discussions can usefully proceed through three stages of questions:
- Where are we now, with respect to resources and needs?
- What immediate steps (e.g. in terms of sharing) would make improvements?
- What potential projects for new tools, standards, or data models might be worth undertaking?
At all stages, there are many specific topics that need discussion. To sort them out, three kinds of activities are useful categories: obtaining the data; using the data; and communicating about the data.
Obtaining Data. COVID-19 data challenges begin with just acquiring data of the range and quality needed. A very wide range of data is needed, in three dimensions: geographical, time, and domain. Depending on the purpose, data may be needed either at very specific local levels or at the widest global level. Both are challenging --- finding reliable local sources and resolving hugely variable international ones, for example. Particularly on the global (or even national) scale, variable quality will often be a challenge. Timeliness of the data is clearly essential, particularly as public health regulations and other societal responses change. But scientific models and analysis may also need to have data over a long time span. The pandemic has touched our lives in many ways: directly in our health but also in nearly all aspects of our economy and society. As the world responds, data science will need to consider all these aspects, requiring data from the microscopic level of the virus to the population data for epidemiology, social science, and economics.
Using Data. The response to the COVID-19 pandemic from the scientific community continues to generate crucial data-based results. Epidemiologists, public health experts, data scientists, and other researchers have produced a large number of predictive models, interactive resource allocation applications, and disease tracking dashboards. Moving ahead, it will be important to have easy, consistent access to the best data for all these efforts. Co-operation and co-ordination among the teams involved can enhance the scope and help ensure that model results and comparisons use consistent, well-defined data sources.
Communicating Data. A key goal of the Data Forum is to improve communication between decision-makers (in public health, government, and elsewhere) and the data science and general research community. Many tools have been developed for visualizing and interacting with data. It's important to understand how these can be used and enhanced for the decision-making community. We look forward to participation in our meetings by interested members of this community. Another important goal is to improve the information flow to the broader community, with emphasis on giving insight and avoiding misdirection.
All events hosted by the Forum adhere to Stanford Data Science's Code of Conduct policy.
Please join us for our second public, virtual event, focused on efforts to improve accessibility of patient-level data for COVID-19.
Beyond case counts: Making COVID-19 clinical data available and useful
August 13, 2020
9:00 AM San Francisco | 16:00 UTC
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.
- Sherri Rose: Moderator
- Associate Professor, Stanford Health Policy
- Jenna Reps:
- Affiliate, OHDSI consortium's patient-level prediction working group
- Member, Janssen R&D
- Andrea Ganna:
- Ken Massey:
- Roni Rosenfeld:
- Lead Researcher, Delphi Covid-19 Response Team
- Professor and Head, Machine Learning Department, School of Computer Science, Carnegie Mellon University
We record our events, and will make them available for replay shortly after they conclude.
Introducing the COVID-19 Data Forum
Thursday, May 14, 2020
19:00 UTC | 12pm PDT | 3pm EDT | 8pm London | 9pm Paris | 3am Beijing
The opening event of the COVID-19 Data Forum was held on May 14 2020 and attracted several hundred attendees for a lively discussion of the current state of COVID-19 data and the challenges researchers face.
- Joseph Rickert: Welcome and opening remarks
- Chair R Consortium Board of Directors, R Consortium
- Alison Hill: Modeling COVID-19 Spread and Control: Data Needs and Challenges
- John Harvard Distinguished Science Fellow, Harvard's Program for Evolutionary Dynamics
- Ryan Hafen: Collecting and Visualizing COVID-19 Case Count Data from Multiple Open Sources (replay)
- Orhun Aydin: Spatial and Space-Time Data on COVID-19 (replay)
- Noam Ross: Data in the COVID-19 Pandemic
- Senior Research Scientist, EcoHealth Alliance
Joseph Rickert - Chair R Consortium Board of Directors
John Chambers - Stanford Department of Statistics and Stanford Data Science
Michael Kane - Assistant Professor, Department of Biostatistics, Yale University
Balasubramanian Narasimhan - Senior Research Scientist, Department of Biomedical Data Sciences, Stanford University
Chris Mentzel - Executive Director, Stanford Data Science
Alison Hill - John Harvard Distinguished Science Fellow, Harvard University