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Cocirculation of varying influenza types, strains, and lineages allows coinfection and intra‐season sequential infection, although a same‐strain sequential infection has not been previously described. This case report describes the first known case of sequential laboratory‐confirmed influenza A (H3N2) infections in a child within one season. [ABSTRACT FROM AUTHOR]

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: 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 3012 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. [ABSTRACT FROM AUTHOR]

Background: The prevalence, symptom course, and shedding in persons infected with the 4 most common human coronaviruses (HCoV)‐229E, HKU1, NL63, and OC43 are poorly described. Objectives: We estimate their prevalence and associated symptoms among college students identified via a social network study design. Patients/Methods: We collected 1‐3 samples (n = 250 specimens) from 176 participants between October 2012 and January 17, 2013: participants with acute respiratory infection (ARI; cough and body aches or chills or fever/feverishness) and their social contacts. Virus was detected using RT‐PCR. Results: 30.4% (76/250) of specimens tested positive for any virus tested, and 4.8% (12/250) were positive for 2 or more viruses. Human coronaviruses (HCoVs [22.0%; 55/250]), rhinovirus (7.6%; 19/250), and influenza A (6.4%; 16/250) were most prevalent. Symptoms changed significantly over time among ARI participants with HCoV: the prevalence of cough and chills decreased over 6 days (P = .04, and P = .01, respectively), while runny nose increased over the same period (P = .02). HCoV‐NL63 was the most frequent virus detected 6 days following symptom onset (8.9%), followed by rhinovirus (6.7%). Conclusions: During a 3‐month period covering a single season, HCoVs were common, even among social contacts without respiratory symptoms; specific symptoms may change over the course of HCoV‐associated illness and were similar to symptoms from influenza and rhinovirus. [ABSTRACT FROM AUTHOR]