1 citations · 1 across the 6 of their papers we have counts for
6 papers
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…
modelimportance: An R package for evaluating model importance within a multi-model ensemble
Minsu Kim, Li Shandross, Evan L. Ray +1
Ensemble forecasts are commonly used to support decision-making and policy planning across various fields because they often offer improved accuracy and stability compared to indiv…
Comparison of probabilistic nowcasts and forecasts of SARS-CoV-2 variant proportions made by hierarchical multinomial linear regression models
Isaac MacArthur, Thomas Robacker, Evan L. Ray +3
Nowcasting and forecasting of infectious diseases have become increasingly important since the SARS-CoV-2 pandemic. In particular, methods for modeling the composition of circulati…
Beyond forecast leaderboards: Measuring individual model importance based on contribution to ensemble accuracy
Minsu Kim, Evan L. Ray, Nicholas G. Reich
Ensemble forecasts often outperform forecasts from individual standalone models, and have been used to support decision-making and policy planning in various fields. As collaborati…
Flusion: Integrating multiple data sources for accurate influenza predictions
Evan L. Ray, Yijin Wang, Russell D. Wolfinger +1
Over the last ten years, the US Centers for Disease Control and Prevention (CDC) has organized an annual influenza forecasting challenge with the motivation that accurate probabili…
Mixture distributions for probabilistic forecasts of disease outbreaks
Spencer Wadsworth, Jarad Niemi, Nick Reich
Collaboration among multiple teams has played a major role in probabilistic forecasting events of influenza outbreaks, the COVID-19 pandemic, other disease outbreaks, and in many o…