The development of data science in biomedical research has shifted the ways in which we develop epidemiologic knowledge. In some instances, like health insurance claims or hospital data, this was merely an outgrowth of existing trends. However, increasingly, there is interest in merging these data with other data sources, such as measures of weather or environmental exposures. Diseases previously not recognized as weather-related have detectable weather patterns. The large and static populations followed in these databases may provide a method for combining high-throughput work in laboratories to humans where the potential for medication repurposing is discovered. Wearable devices and video capture allow for out-of-the-clinic or at-home monitoring of patients, critical for rehabilitation following hospitalization, disease prevention, and management of diseases to keep people out of the hospital.
My background is a MS in epidemiology at the College of Public Health at Iowa and a PhD in Health Services Research at the College of Pharmacy. I worked at U Iowa Health Ventures as a data scientist after completing my PhD and a post-doc with Alberto Segre and the CompEpi group in 2018. I joined the faculty in the Department of Internal Medicine, Division of Pulmonary, Critical Care, and Occupational Medicine in 2019. One of my primary goals was to make data science expertise more tightly integrated into the research team than possible under a statistical consulting model. My work has largely focused on understanding environmental exposures, chiefly weather, and infectious disease outcomes. Recently, I have been working closely with neurologists and neuroscientists interested in preventing and providing more timely therapy for people with neurodegenerative diseases, like Parkinson's Disease, Lewy Body Dementia, and Alzheimer's disease.
In-person colloquia this Fall will also be streamed on Zoom. Interested parties may contact us for Zoom url.