Causal Inference from Real World Data in the Era of Covid-19

See: https://bit.ly/3vMOix5

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