Causal Inference from Real World Data in the Era of Covid-19
Details
Online Registration: https://bit.ly/3mdIFFg
ZOOM LINK WILL BE DISTRIBUTED DURING THE WEEK OF THE EVENT.
Program
10:30am Welcome
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
-Barbra Dickerman
Drug repurposing for COVID-19 prevention: The effects of old drugs on a new disease
-Xabier García-Albéniz
-Katherine Li
Nonpharmacological interventions for the treatment and prevention of Covid-19
-Arin Madenci
-José Zubizarreta
12:45pm Break (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