Since 2013, the CDC has held a seasonal competition forecasting the current flu season. In the current season (2022-23), the forecasting target is the weekly incidence of hospital admissions for the following four weeks ahead.
Submissions are submitted every week.Here we report the results from our modeling approach.
To study the spatiotemporal spread of the flu, we use the Global Epidemic and Mobility Model (GLEAM), an individual-based, stochastic, and spatial epidemic model [1, 2, 3, 4, 5, 6]. GLEAM uses real-world data to perform in-silico simulations of the spatial spread of infectious diseases at the global level. The data are aggregated to provide the estimates at the US state level. GLEAM generates an ensemble of possible epidemic projections described by the number of newly generated infections, hospitalizations, and deaths. The model is calibrated on weekly hospital admissions data from the US Department of Health and Human Services using an information theoretical approach.
Disclaimer: The presented material is based on modeling scenario assumptions informed by knowledge of the transmission of the influenza virus and subject to change as more data become available.
Acknowledgements: We acknowledge support from grant HHS/CDC 6U01IP001137, HHS/CDC 5U01IP0001137.
Northeastern University/MOBS Lab
• Matteo Chinazzi
• Jessica T. Davis
• Kunpeng Mu
• Ana Pastore y Piontti
• Xinyue Xiong
• Alessandro Vespignani
