Publications (6)
Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States
Evan L. Ray, Logan C. Brooks, Jacob Bien +12
The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensembl…
Information leakage from data revisions in retrospective forecasts
Johannes Bracher, Sebastian Funk
Aygün et al (2026, https://doi.org/10.1038/s41586-026-10658-6) claim that their AI-driven Empirical Research Assistance (ERA) system produces COVID-19 hospitalisation forecasts whi…
Key Questions for Modelling COVID-19 Exit Strategies
Robin N Thompson, T Deirdre Hollingsworth, Valerie Isham +40
Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to impl…
Evaluating Forecasts with scoringutils in R
Nikos I. Bosse, Hugo Gruson, Anne Cori +3
Evaluating forecasts is essential to understand and improve forecasting and make forecasts useful to decision makers. A variety of R packages provide a broad variety of scoring rul…
Collaborative estimation and evaluation of SARS-CoV-2 variant nowcasting in the United States
Isaac MacArthur, Thomas Robacker, Bren Case +27
The ability to estimate and predict pathogen variant dynamics can inform public health responses, including planning for increased transmission or severity, shifts in population im…
Best practices for estimating and reporting epidemiological delay distributions of infectious diseases using public health surveillance and healthcare data
Kelly Charniga, Sang Woo Park, Andrei R Akhmetzhanov +11
Epidemiological delays, such as incubation periods, serial intervals, and hospital lengths of stay, are among key quantities in infectious disease epidemiology that inform public h…