Addressing delayed case reporting in infectious disease forecast modeling
Fig 5
Performance of proposed methods for handling reporting delay in 2009 across 100 simulated datasets using ARMA models1.
1 Results are aggregated across all 50 weeks in 100 replicate seasons. Each result, therefore, represents aggregates 5000 nowcasts or forecasts. When reporting factors varied across seasons, π2007 = π2008 = (0.01, 0.05, 0.55, 0.85, 0.95, 0.98, 1) and π2009 = (0.04, 0.54, 0.84, 0.0.94, 0.97, 0.99, 1). The ensemble method corresponds to an equal-weight linear combination of all methods except validation data analysis and exclusions of 4 and 5 weeks’ data. “Model” indicates that reporting factors were estimated via regression and allowed to vary by t and s. “Lag” indicates that reporting factors were estimated via Eq 6. “Local” indicates that reporting factors were estimated via Eq 8. Relative absolute biases are calculated relative to the largest value in each column. Model-based πts(d) estimation assumes reporting factors vary across weeks but incorrectly models how reporting factors vary across weeks.