Inla Forecasting Paper

Our work on seasonal respiratory disease forecasting has been published in Nature Communications Medicine! We propose a flexible hierachical model incorporting seasonal and short-term spatiotemporal effects with regional correlations, and show it can accurately predict influenza, COVID-19, and RSV hospitalizations. The model was the top individual forecast model during the 2023-24 and 2025-26 CDC FluSight challenges, and is currently the top individual model in the CDC COVID-19 Forecast Hub. Find the manuscript in press here.