Fig. 4

Mean difference in WIS for incident cases (A) and deaths (B) at the US national level between a chimeric ensemble and a computational ensemble paired across six different surveys from Jan 2021 to June 2021 for two strategies to impute missing values (“spotty memory” and “defer to the crowd”) and, within each strategy, 5 different techniques to impute missing forecasts. A chimeric ensemble—a combination of computational and human judgment models—improves WIS scores when the target is cases but weakens or maintains similar WIS scores when the target is deaths. There are negligible differences in mean WIS between a “defer to the crowd” and “spotty memory” imputation strategy for prediction of cases and a defer to the crowd approach appears to improve predictions compared to a spotty memory approach for predictions of incident deaths. Bayesian Ridge Regression (BR) and Median imputation (MI) are promising strategies to impute missing forecasts for incident cases