Causal Inference from Real World Data in the Era of Covid-19
Virtual - November 5, 2021
Albert Hofman, Chair, Department of Epidemiology
10:40am The CAUSALab: A Center to Learn What Works
Miguel Hernán, Director of the CAUSALab
11:00am The CAUSALab’s Response to Covid-19: Data science for decision making
Vaccines for Covid-19 prevention: Comparative effectiveness and safety
Drug repurposing for COVID-19 prevention: The effects of old drugs on a new disease
Nonpharmacological interventions for the treatment and prevention of Covid-19
12:45pm Lunch served for in-person attendees
1:30pm Causal inference without randomized experiments: How do we know we are right?
-James Robins, Mitchell L. and Robin LaFoley Dong Professor of Epidemiology
Panel and discussion with the audience
-Issa Dahabreh, Miguel Hernán, Sara Lodi, and James Robins
-Moderated by Andrew Beam
3:00pm Reception for in-person attendees
The CAUSALab uses data to investigate what works in medicine, public health, and policy. We generate, analyze, and interpret data so that decision makers—patients, clinicians, regulators, policy makers…—can make better decisions. By combining sound methodology with high-quality data, we produce actionable causal inference with real-world impact. We also train the next generation of investigators.
Our methodological research focuses on developing a methodological framework for causal inference research based on observational health databases (e.g., administrative claims, electronic health records, biobanks) and pragmatic randomized trials. Our areas of work include causal inference and AI, transportability, instrumental variable estimation based on genetic variants (aka, Mendelian randomization), g-methods for sustained treatment strategies, and benchmarking of observational studies with randomized trials.
Our applied research focuses on implementing the frameworks to determine comparative effectiveness and safety of health and policy interventions. Our areas of work include infectious diseases, cardiovascular diseases, cancer, mental Health, and pregnancy.