Influenza predictions comparing all-cause and influenza-like illness-specific absences from cohort data
Using school-based cohort studies, we compared the performance of all-cause absences to ILI-specific absences, a better proxy for influenza infection. Because the cohorts had short time-series (i.e., one influenza season), we were unable to examine models containing all seasonal variables and to include average temperature in some models. Multivariate ILI absence models had higher R2estimates and lower relMAEs than all-cause absence models in analyses using PIPP, 2012-2013 SMART, and pooled absence data (Table 2). From the 2015-2016 SMART2 data, the all-cause absence model had a lower relMAE (relMAE: 0.59) than the ILI-specific model (relMAE: 2.17), but similar R2 estimates (Table 2). Pooling across studies, the ILI-specific absence model had a lower relMAE (relMAE:0.99) than the all-cause absence model (relMAE: 1.02), and similar R2 estimates (all-cause R2: 0.30 and ILI-specific R2: 0.37) (Table 2).