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Virtual Seminar: COVID Data Science: Evaluating and Aggregating Emerging Knowledge in the Pandemic

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Jeffrey S. Morris, Ph.D.

Professor of Biostatistics
Director, Biostatistics Division
Department of Biostatistics, Epidemiology & Informatics
Perelman School of Medicine
University of Pennsylvania

COVID Data Science: Evaluating and Aggregating Emerging Knowledge in the Pandemic

Sept. 24, 2021 

12:00 p.m. to 1:00 p.m.

How to attend: This is a virtual event presented live on Zoom. Registration is required.

About this Seminar

The novel virus SARS-CoV-2 has produced a global pandemic, forcing doctors and policymakers to “fly blind,” trying to deal with a virus and disease they knew virtually nothing about. Sorting through the information in real time has been a daunting process—processing data, media reports, commentaries, and research articles. In the USA this is exacerbated by an ideologically divided society that has difficulty with mutual trust, or even agreement on common facts. The skills underlying statistical data scientists are central to this knowledge discovery process, filtering out biases, aggregating disparate data sources together, dealing with measurement error and missing data, identifying key insights while quantifying the uncertainty in these insights, and then communicating the results in an accessible balanced way. As a result, scientists have had a central role to play in society to bring our perspective and expertise to bear on the pandemic to help ensure knowledge is efficiently discovered and put into practice. Dr. Morris has authored a website and blog, covid-datascience.com, that represents his own personal efforts to disseminate information he has found reliable and insightful regarding the pandemic, accounting for subtle scientific and data analytical issues and uncertainties about our current knowledge, and seeking to filter out political and other subjective biases.

Using experiences with his blog as a backdrop, Dr. Morris will highlight how statistical and data scientific issues have been central in understanding the emerging knowledge in the pandemic. He will discuss various broad issues he has seen impede the knowledge discovery process, including subjective bias causing individuals to ignore some information and magnify others, viral misinformation spread on social media platforms, danger of rushed and inadequately reviewed scientific studies, conflating of political concerns and scientific messaging, and incomplete and messaging from scientific leaders to the broader community. He will discuss these concepts in various specific contexts, including identification of key modes of spread and effective mitigation strategies, vaccine safety and efficacy, durability of immune protection and risk of reinfections or breakthrough infections, and the emergence of variants of concern and how this affects the pandemic moving forward. He will give a particular example of Simpson’s Paradox, a statistical principle appearing in many observational study contexts but not well understood by the pubic, showing how vaccine efficacy vs. severe disease may appear much lower than it is because of major confounding with age. Throughout, Dr. Morris will mention the political and sociological dynamics that have shaped the ability (and inability) to reach consensus on emerging knowledge and put it to work for effect (or ineffective) pandemic management.

Additional Details

This is a free event hosted by iTHRIV.  The integrated Translational Health Research Institute of Virginia (iTHRIV) is part of the Clinical and Translational Science Award (CTSA) partnership between Virginia Tech, the University of Virginia, Carilion Clinic, and Inova Health System. iTHRIV aims to promote interdisciplinary research projects that help bring scientific innovations from the lab into clinical practice. iTHRIV also strives to address social equity, with the goal of implementing research that will benefit underserved populations across Virginia. The iTHRIV Scholars Program is supported in part by the National Center For Advancing Translational Sciences of the National Institutes of Health.

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