Widespread school closures and other non-pharmaceutical interventions (NPIs), used to limit the spread of SARS-CoV-2, significantly disrupted transmission patterns of seasonal respiratory viruses. As NPIs were relaxed, populations were vulnerable to resurgence. This study within a small community assessed acute respiratory illness among kindergarten through grade 12 students as they returned to public schools from September through December 2022 without masking and distancing requirements. The 277 specimens collected demonstrated a shift from rhinovirus to influenza. With continued circulation of SARS-CoV-2 and return of seasonal respiratory viruses, understanding evolving transmission patterns will play an important role in reducing disease burden.

Background School-aged children and school reopening dates have important roles in community influenza transmission. Although many studies evaluated the impact of reactive closures during seasonal and pandemic influenza outbreaks on medically attended influenza in surrounding communities, few assess the impact of planned breaks (i.e., school holidays) which coincide with influenza seasons, while accounting for differences in seasonal peak timing. Here, we analyze the effects of winter and spring breaks on influenza risk in school-aged children, measured by student absenteeism due to influenza-like illness (a-ILI). Methods We compared a-ILI counts in the two-week periods before and after each winter and spring break over five consecutive years in a single school district. We introduced a “pseudo-break” of 9 days’ duration between winter and spring break each year when school was still in session to serve as a control. The same analysis was applied to each pseudo-break to support any findings of true impact. Results We found strong associations between winter and spring breaks and a reduction in influenza risk, with a nearly 50% reduction in a-ILI counts post-break compared to the period before break, and the greatest impact when break coincided with increased local influenza activity. Conclusions These findings suggest that brief breaks of in-person schooling, such as planned breaks lasting 9-16 calendar days, can effectively reduce influenza in schools and community spread. Additional analyses investigating the impact of well-timed shorter breaks on a-ILI may determine an optimal duration for brief school closures to effectively suppress community transmission of influenza.

Rapid influenza diagnostic tests (RIDTs) have variable sensitivity. In a community-based population of kindergarten through 12th grade (K-12) students, we assessed factors that may influence RIDT performance using 2,368 paired results from Sofia® Influenza A + B fluorescent immunoassay and reverse transcription polymerase chain reaction (RT-PCR). RIDT sensitivity and specificity were 76.1% (95% CI: 72.8—79.1) and 97.2% (96.2—97.9), respectively. Factors associated with sensitivity included runny nose (OR=3.0, p<0.001), nasal congestion (1.59, p=0.045), days from symptom onset (per day; 0.75; p<0.001), myalgia (0.61; p=0.014), age (per 5 years; 0.55; p=0.001), and detection of another virus (0.50; p=0.043). Understanding these factors can aid in interpreting negative results.

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.