Company: Columbia University and C4R
Company background: C4R studies the impact of the COVID-19 pandemic across 14 long-term NIH-funded cohort studies via questionnaires, a serosurvey, and COVID-related events adjudication. C4R also harmonizes decades of research-quality data on cardiometabolic, pulmonary, and neurocognitive health. Our aim is to support robust epidemiology on risk and resilience factors for severe COVID-19 and post-acute sequelae or “long COVID,” plus investigations into marked disparities in the pandemic’s impact across the US.
Contact: Elizabeth C. Oelsner
Title: Assistant Professor of Medicine
Country: USA
Award Category: Community Uplift Award
Tell how you've used SAS to have a positive impact on your community?
SAS was implemented in our cloud-based consortium workspace, the C4R Analysis Commons on BioData Catalyst, to support data harmonization and highly regulated access to C4R data for analysis using SAS. We have trained hundreds of investigators from across the country in use of SAS on the C4R Analysis Commons to answer urgent questions on acute and post-acute sequelae of COVID-19. This approach now serves as a model for data sharing and analysis in other major consortia.
What SAS products are you using and how are you using them?
We have used SAS Studio on the cloud-based C4R Analysis Commons to harmonize >1,000 variables on pre-pandemic and pandemic-era health across >49,000 participants. These include data on SARS-CoV-2 infection, COVID-19 illness, “Long COVID,” psychosocial effects of the pandemic period, and pre-pandemic heart, metabolic, lung, and brain health. We are using the cloud-based SAS Studio to perform longitudinal analysis for over 50 C4R-approved scientific proposals.
What was your most surprising discovery about your work?
We have been overwhelmed by the enthusiasm and generosity of >200 collaborators in making the C4R Analysis Commons a resource for data harmonization and analysis using SAS, which has been instrumental to all aspects of the project. Cross-cohort collaborations have previously occurred, but datasharing limitations and the need for harmonization were significant obstacles. The COVID-19 public health emergency motivated an incredible group effort to establish this unique resource with tremendous opportunities to answer key scientific questions on the health impact of the COVID-19 pandemic.
