Predicting virologically-confirmed influenza using school absences in
Allegheny County, Pennsylvania, USA during the 2007-2015 influenza
Background Children are important in community-level influenza
transmission. School-based monitoring may inform influenza surveillance.
Methods We used reported weekly confirmed influenza in Allegheny County
during the 2007, and 2010-2015 influenza seasons using Pennsylvania’s
Allegheny County Health Department all-age influenza cases from health
facilities, and all-cause and influenza-like illness (ILI)-specific
absences from nine county school districts. Negative binomial regression
predicted influenza cases using all-cause and illness-specific absence
rates, calendar week, average weekly temperature and relative humidity,
using four cross-validations. Results School districts reported
2,184,220 all-cause absences (2010-2015). Three one-season studies
reported 19,577 all-cause and 3,012 ILI-related absences (2007, 2012,
2015). Over seven seasons, 11,946 confirmed influenza cases were
reported. Absences improved seasonal model fits and predictions.
Multivariate models using elementary school absences outperformed middle
and high school models (relative mean absolute error (relMAE)=0.94,
0.98, 0.99). K-5 grade-specific absence models had lowest mean absolute
errors (MAE) in cross-validations. ILI-specific absences performed
marginally better than all-cause absences in two years, adjusting for
other covariates, but markedly worse one year. Conclusions Our findings
suggest seasonal models including K-5th grade absences predict all-age
confirmed influenza and may serve as a useful surveillance tool.