UBC Statistics Associate Professor Daniel McDonald is taking the lead on multiple projects within Carnegie Mellon University's Innovators group. These projects are dedicated to innovating new analytical methods and tools that will ultimately be used to provide information to public health decision-makers.
In September 2022, the Centers for Disease Control and Prevention (CDC) selected Carnegie Mellon's Delphi Research Group as a Center of Innovation in Outbreak Analytics and Disease Modeling. The CDC has also pledged $262 million in funding to support the "National Network for Outbreak Response and Disease Modeling."
Daniel's pivotal role in these initiatives reflects his dedication to improving public health analytics. His contributions include creating and enhancing an open-source R package ecosystem for data processing and forecasting; developing a framework for stacking forecasting "layers" or "modules" whose design presents allows a forecaster to improve calibration, smoothing, and adaptation; synthesizing compartmental and real-time deconvolutional statistical models for estimating epidemiological parameters; and creating new approaches for leading indicator analysis.
The impact of this funding also extends to UBC Ph.D. students, Rachel Lobay and Olivia (Jiaping) Liu, who are partially supported.
For more details, please visit:
https://www.cs.cmu.edu/news/2023/delphi-cdc-center
https://www.cdc.gov/media/releases/2023/p0922-disease-modeling.html