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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) that 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 2‐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 with the period before break, and the greatest impact when break coincided with increased local influenza activity while accounting for possible temporal and community risk confounders. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 2368 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. [ABSTRACT FROM AUTHOR]

Background Concurrent detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and another respiratory virus in individuals can document contemporaneous circulation. We used an ongoing, community-based study of school-aged children and their households to evaluate SARS-CoV-2 codetections with other respiratory viruses in a non–medically attended population over a 2-year period. Methods Household enrollment was predicated on an acute respiratory illness in a child residing in that household who was also a kindergarten through 12th-grade student in the participating school district. Demographic, symptom, and household composition data and self-collected nasal specimens were obtained on the recruitment day, and 7 and 14 days later, from the index child and all other household members. All specimens were tested for SARS-CoV-2 and influenza A/B by reverse-transcription polymerase chain reaction. Day 0 specimens from the index children were simultaneously tested for 16 pathogens using a commercial respiratory pathogen panel (RPP). To assess viral codetections involving SARS-CoV-2, all household specimens were tested via RPP if the index child's day 0 specimen tested positive to any of the 16 pathogen targets in RPP and any household member tested positive for SARS-CoV-2. Results Of 2109 participants (497 index children in 497 households with 1612 additional household members), 2 (0.1%) were positive for both SARS-CoV-2 and influenza A; an additional 11 (0.5%) were positive for SARS-CoV-2 and another RPP-covered respiratory virus. Codetections predominantly affected school-aged children (12 of 13 total) and were noted in 11 of 497 households. Conclusions SARS-CoV-2 codetections with other respiratory viruses were uncommon and predominated in school-aged children. [ABSTRACT FROM AUTHOR]

Background: Schools are primary venues of influenza amplification with secondary spread to communities. We assessed K-12 student absenteeism monitoring as a means for early detection of influenza activity in the community. Materials and methods: Between September 2014 and March 2020, we conducted a prospective observational study of all-cause (a-TOT), illness-associated (a-I), and influenza-like illness–associated (a-ILI) absenteeism within the Oregon School District (OSD), Dane County, Wisconsin. Absenteeism was reported through the electronic student information system. Students were visited at home where pharyngeal specimens were collected for influenza RT-PCR testing. Surveillance of medically-attended laboratory-confirmed influenza (MAI) occurred in five primary care clinics in and adjoining the OSD. Poisson general additive log linear regression models of daily counts of absenteeism and MAI were compared using correlation analysis. Findings: Influenza was detected in 723 of 2,378 visited students, and in 1,327 of 4,903 MAI patients. Over six influenza seasons, a-ILI was significantly correlated with MAI in the community (r = 0.57; 95% CI: 0.53–0.63) with a one-day lead time and a-I was significantly correlated with MAI in the community (r = 0.49; 0.44–0.54) with a 10-day lead time, while a-TOT performed poorly (r = 0.27; 0.21–0.33), following MAI by six days. Discussion: Surveillance using cause-specific absenteeism was feasible and performed well over a study period marked by diverse presentations of seasonal influenza. Monitoring a-I and a-ILI can provide early warning of seasonal influenza in time for community mitigation efforts. [ABSTRACT FROM AUTHOR]