January 26, 2022
Join the UNC Program for Precision Medicine in Health Care (PPMH) for Precision Medicine Approaches to Addressing COVID-19, a free virtual mini-symposium from 1:00-3:00pm on Wednesday February 23, 2022. Presenters will explore how data has informed our response to the COVID-19 pandemic: the collection, analysis, and interpretation of COVID-related data.
COVID-19 has presented enormous challenges to society. Scientists and clinicians across many disciplines have worked to mitigate the spread and effects of COVID-19. This mini-symposium will feature 3 presentations focusing on how data has informed our response to the COVID-19 pandemic: the collection, analysis, and interpretation of COVID-related data.
Join the UNC Program for Precision Medicine in Healthcare (PPMH) for Precision Health @UNC: Precision Medicine Approaches to Addressing COVID-19, a free virtual mini-symposium on Wednesday February 23, 2022 from 1:00 to 3:00pm ET. At this interactive event, you will engage in discussion with leading Precision Medicine researchers at UNC.
Jeremy Wang PhD, Assistant Professor, Department of Genetics
Presentation Title: Real-time genomic surveillance of SARS-CoV-2 in an academic medical center
This presentation will describe a collaboration between research genomics lab and clinical microbiology lab developing rapid surveillance for COVID strain variation monitoring. We will discuss our approach to rapid-turnaround genomic surveillance during the SARS-CoV-2 pandemic, including tools, challenges, and outcomes for public health.
Ryan Kelly, Principal Data Scientist, ISD Enterprise Analytics & Data Sciences (EADS), UNC Health Shared Services
Presentation Title: Predicting the unprecedented: An ongoing saga to forecast the impacts of COVID-19 on UNC Health and the communities we serve
When COVID-19 emerged in North Carolina in March 2020, UNC Health leadership quickly recognized the need for reliable forecasts of the pandemic’s trajectory to inform critical decisions. The breakneck foray into real-time, action-oriented epidemiological modeling that ensued was the stuff of a data science thriller novel—if only the genre existed! Here we discuss lessons learned from that ongoing journey, which spans two years and >80 model versions, from wildly diverging “best guess” simulations initially to the hierarchical Bayesian formulation still in use—and continually evolving—today.
Emily Pfaff PhD, Assistant Professor, Department of Medicine
Presentation Title: What Can We Learn from 3.6 Million COVID-19 Cases?
This presentation covers the creation, curation, and use of the National COVID Cohort Collaborative (N3C), a nation-spanning electronic health record dataset sourced from nearly 70 health care organizations. We will cover how the dataset was constructed, delve into a specific use-case for the data (long-haul COVID research), and discuss how you can use N3C in your own research.
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