Disease Forecasting Working Group

Established September 2017

The Disease Forecasting Working Group aims to advance our capacity to forecast infectious disease dynamics by developing next generation time series modeling methods, and by developing a forecasting framework to facilitate the efficient and effective forecasting of infectious diseases in real time.

Next generation forecast models. The working group is pioneering approaches blending mechanistic modeling, statistical modeling, and artificial intelligence.  These efforts include semiparametric models and physics-informed neural networks.

Forecast architecture. The forecasting working group is currently developing an open-source forecasting pipeline with the goal of facilitating and automating complete forecasting workflows, including data ingestion, modeling, model evaluation, and visualization.

Forecasting challenges. This working group facilitates coordination between CEID teams and forecasting research groups at other institutions through collaborations and participation in forecasting competitions for infectious disease. The forecasting working group regularly contributes to the CDC’s seasonal Influenza and COVID-19 forecasting challenges.

For information on joining this working group, or partnering for a specific or envisioned project, please contact John Drake (jdrake@uga.edu).

Current working group members:

Nicholas Adam
Budak Arpinar
Avranil Basu
John Drake (Disease Forecasting Working Group Coordinator)
Spencer Fox
Indrajit Ghosh
Mandev Gill
Eddy Gomez
He Li
Éric Marty
John Miller
Sheikh Shahid Nadim
John Nesbit (intern)

Eamon O’Dea
Pejman Rohani
Maya Salcedo
Ninghau Liu
Yang Yang
Ye Shen
Ying Qian
Yuan Ke