Biomedical Data Science Seminar: Statistical Modeling and COVID-19

Seminar Speaker: Paul Perrin, PhD, University of Virginia,

This presentation will showcase a diverse set of data science approaches for modeling important features of the COVID-19 pandemic, including analyses of variance, linear regressions, path analyses, and network analyses. Data will be presented documenting and predicting the rollout of telehealth services at the beginning of the pandemic by psychologists and physicians in the United States. Data will then be presented on neurobehavioral symptom magnitude and patterns in Long COVID in diverse global regions.

Paul Perrin, PhD is a Professor of Data Science and Psychology at the University of Virginia. He believes that a combination of data science, modern analytic techniques, and community-based participatory research approaches are key tools for identifying the sources of—and potential solutions to—health disparities. With this aim, his research area of “social justice in disability and health” encompasses three facets: (a) cultural, familial, and international approaches to disability rehabilitation and adjustment, particularly in medically underserved and minority populations with neurological conditions; (b) social determinants of health (e.g., stigma, access to integrated care and telehealth, personal and collective strengths); and (c) social justice approaches to understand and dismantle oppression.

To learn more about the Biomedical Data Science Innovation Lab and Seminar Series, please visit: https://www.innovation.lab.virginia.edu

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