VP Research and Analysis,
Dr. Andrew Schroeder is the Vice President of Research and Analysis for Direct Relief. He leads Direct Relief’s work in GIS mapping, data collection, epidemiological research and humanitarian informatics. His work has been featured or cited by publications including Science, The Lancet, The New York Times, The Washington Post, Fast Company, Motherboard Vice, The New Humanitarian, Prehospital & Disaster Medicine, and the International Journal of Cancer. Dr. Schroeder earned his Ph.D. in Social and Cultural Analysis from New York University and his Masters of Public Policy (MPP) from the Gerald R. Ford School of Public Policy at the University of Michigan specializing in social analytic methods, information technology policy and international development. In addition to his work for Direct Relief he is the co-founder of the non-profit WeRobotics.org which builds local capacity in robotics for humanitarian aid, development and global health.
WATCH LIVE: November 2nd at 10:00 am
The Covid-19 pandemic has significantly accelerated the use of large-scale private data sources for real-time response to emergencies. For example, aggregated mobility data, derived from social media platforms and mobile devices, has been of enormous value to monitor and model non-pharmaceutical interventions including physical distancing continuously at population scale and in privacy-protected manner. This same set of data sources, methods and networks have broad applicability to public health emergency response in general. The CrisisReady Network, which emerged from the collaborative efforts of infectious disease epidemiologists and public health responders to the pandemic, is extending and sustaining the use of large-scale private data flows for emergency response by focusing on three dimensions of “readiness”: data, methods and translation. In combination, data readiness, methods readiness and translational readiness promote a new model of scalable expertise which transforms how we prepare for and respond to emergency events through applied data science, epidemiology and distributed collaboration.