Cause-specific student absenteeism monitoring in K-12 schools for detection of increased influenza activity in the surrounding community—Dane County, Wisconsin, 2014–2020

Factors Associated With Transmission Across Three Waves of SARS-CoV-2 in a Prospective Community-Based Study of Households With School-Aged Children-Dane County, Wisconsin, 2020-2022

BACKGROUND

Household transmission of SARS-CoV-2 is a driver of the ongoing COVID-19 pandemic. Understanding factors that contribute to secondary infection risks (SIRs) can define changing trends and inform public health policies.

METHODS

The ORegon CHild Absenteeism due to Respiratory Disease Study (ORCHARDS) prospectively monitors respiratory viruses within the Oregon School District (OSD) in southcentral Wisconsin. Households with students who had ≥ 2 respiratory symptoms were eligible and opted to participate in ORCHARDS. Between October 28, 2020, and May 16, 2022, all household members provided self-collected nasal specimens on days 0, 7, and 14 for SARS-CoV-2 detection using real-time reverse-transcription-polymerase chain reaction. We used logistic regression to investigate individual- and household-level characteristics associated with SARS-CoV-2 transmission.

RESULTS

Overall, 127 households comprising 572 individuals (48% female; 52% male; 0.4% nonbinary; 77% ≥ 18 years) had at least one detection of SARS-CoV-2. The overall SIR was 47% and decreased over time (pre-Delta = 72% [95% CI: 58%-83%]; Delta = 51% [40%-63%]; and Omicron = 41% [36%-47%]). Odds of household transmission were 63% lower during the Omicron period compared with the pre-Delta period (OR = 0.36 [95% CI: 0.13-0.94] p = 0.037). Greater household density (members/bedroom) was significantly associated with household transmission during the Omicron period (OR = 6.8, [2.19-21.37] p = 0.001). Index case age, illness severity, and individual symptoms were not significantly associated with odds of household transmission.

CONCLUSIONS

Greater household density was associated with a higher risk of SARS-CoV-2 transmission, but the risk declined over time with subsequent variants. Interplay between variants, prior infection, and individual/household factors may identify modifiable factors (e.g., behavior and vaccination) to reduce future transmission risk.

Absenteeism and Health Behavior Trends Associated With Acute Respiratory Illness Before and During the COVID-19 Pandemic in a Community Household Cohort, King County, Washington

Introduction

Longitudinal data on how acute respiratory illness (ARI) affects behavior, namely school or work participation, and nonpharmaceutical intervention (NPI) usage before and during the COVID-19 pandemic is limited. The authors assessed how ARIs and specific symptoms affected school, work, and health-related behaviors over time.

Methods

From November 2019 to June 2021, participating households with children in King County, Washington, were remotely monitored for ARI symptoms weekly. Following ARIs, participants reported illness-related effects on school, work, and NPI use. Using logistic regression with generalized estimating equations, the authors examined associations between symptoms and behaviors.

Results

Of 1,861 participants, 581 (31%) from 293 households reported 884 ARIs and completed one-week follow-up surveys. Compared with the prepandemic period, during the period of the pandemic pre-COVID-19 vaccine, ARI-related school (56% vs 10%, p<0.001) absenteeism decreased and masking increased (3% vs 28%, p<0.001). After vaccine authorization in December 2020, more ARIs resulted in masking (3% vs 48%, p<0.001), avoiding contact with non-household members (26% vs 58%, p<0.001), and staying home (37% vs 69%, p<0.001) compared with the prepandemic period. Constitutional symptoms such as fever were associated with work disruptions (OR=1.91; 95% CI=1.06, 3.43), staying home (OR=1.55; 95% CI=1.06, 2.27), and decreased contact with non-household members (OR=1.58; 95% CI=1.05, 2.36).

Conclusions

This remote household study permitted uninterrupted tracking of behavioral changes in families with children before and during the COVID-19 pandemic, identifying increased use of some NPIs when ill but no additional illness-associated work or school disruptions.

School closures due to seasonal influenza: a prospective data collection-based study of eleven influenza seasons-United States, 2011-2022

Background

While numerous studies explore pandemic-associated school closures, literature is scant regarding seasonal influenza-associated closures. We previously reported summaries on COVID-19 pandemic-related school closures in the United States (US), which affected virtually all schools in the nation. The current prospective study aims to address the knowledge gap for seasonal influenza-related closures in the United States.

Methods

We conducted systematic daily online searches from August 1, 2011 to June 30, 2022, to identify public announcements of unplanned school closures in the US lasting ≥1 day, selecting those that mentioned influenza and influenza-like illness (ILI) as reason for school closure (ILI-SCs). We studied ILI-SC temporal patterns and compared them with reported outpatient ILI-related healthcare visits.

Findings

We documented that ILI-SCs occurred annually, with yearly totals ranging from 11 ILI-SCs in both the 2013-2014 and 2020-2021 school years to 2886 ILI-SCs in the 2019-2020 school year among more than 100,000 kindergarten through twelfth grade schools in the US. ILI-SCs occurred concurrently with widespread illness and the strongest correlations were observed during influenza A (H3N2)-dominant seasons, most notably in the 2016-2017 (Spearman rank correlation (rs) = 0.83) and the 2017-2018 (rs = 0.84) school years. ILI-SCs were heavily centered in U.S. Department of Health and Human Services Region 4 (states of Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, and Tennessee) [60% (6040/9166, Region 4/Total school closures)] and disproportionately impacted rural and lower-income communities.

Interpretation

Outside of a pandemic, disease-related school closures are extreme and generally rare events for US schools and communities. Timely compilation of publicly available ILI-SC announcements could enhance influenza surveillance, particularly in severe influenza seasons or pandemics when ILI-SCs are prevalent.

Funding

This work was supported by the U.S. Centers for Disease Control and Prevention. Co-authors (NZ, YZ, HG, AU) were or are US CDC employees, and FJ was a contractor through Cherokee Nation Operational Solutions, LLC, which supported FJ's salary, but had no additional role in the study.

Household transmission of human metapneumovirus and seasonal coronavirus

We analyzed data from a community-based acute respiratory illness study involving K-12 students and their families in southcentral Wisconsin and assessed household transmission of two common seasonal respiratory viruses - human metapneumovirus (HMPV) and human coronaviruses OC43 and HKU1 (HCOV). We found secondary infection rates of 12.2% (95% CI: 8.1%-17.4%) and 19.2% (95% CI: 13.8%-25.7%) for HMPV and HCOV, respectively. We performed individual- and family-level regression models and found that HMPV transmission was positively associated age of the index case (individual model: p = .016; family model: p = .004) and HCOV transmission was positively associated with household density (family model: p = .048). We also found that the age of the non-index case was negatively associated with transmission of both HMPV (individual model: p = .049) and HCOV (individual model: p = .041), but we attributed this to selection bias from the original study design. Understanding household transmission of common respiratory viruses like HMPV and HCOV may help to broaden our understanding of the overall disease burden and establish methods to prevent the spread of disease from low- to high-risk populations.

Descriptive Epidemiology of Pathogens Associated with Acute Respiratory Infection in a Community-Based Study of K-12 School Children (2015-2023)

School-based outbreaks often precede increased incidence of acute respiratory infections in the greater community. We conducted acute respiratory infection surveillance among children to elucidate commonly detected pathogens in school settings and their unique characteristics and epidemiological patterns. The ORegon CHild Absenteeism due to Respiratory Disease Study (ORCHARDS) is a longitudinal, laboratory-supported, school-based, acute respiratory illness (ARI) surveillance study designed to evaluate the utility of cause-specific student absenteeism monitoring for early detection of increased activity of influenza and other respiratory viruses in schools from kindergarten through 12th grade. Eligible participants with ARIs provided demographic, epidemiologic, and symptom data, along with a nasal swab or oropharyngeal specimen. Multipathogen testing using reverse-transcription polymerase chain reaction (RT-PCR) was performed on all specimens for 18 respiratory viruses and 2 atypical bacterial pathogens (Chlamydia pneumoniae and Mycoplasma pneumoniae). Between 5 January 2015 and 9 June 2023, 3498 children participated. Pathogens were detected in 2455 of 3498 (70%) specimens. Rhinovirus/enteroviruses (36%) and influenza viruses A/B (35%) were most commonly identified in positive specimens. Rhinovirus/enteroviruses and parainfluenza viruses occurred early in the academic year, followed by seasonal coronaviruses, RSV, influenza viruses A/B, and human metapneumovirus. Since its emergence in 2020, SARS-CoV-2 was detected year-round and had a higher median age than the other pathogens. A better understanding of the etiologies, presentations, and patterns of pediatric acute respiratory infections can help inform medical and public health system responses.

Effect of planned school breaks on student absenteeism due to influenza-like illness in school aged children-Oregon School District, Wisconsin September 2014-June 2019

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.

Changing pattern of respiratory virus detections among school-aged children in a small community - Dane County, Wisconsin, September to December 2022

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.

Monitoring School Absenteeism for Influenza-Like Illness Surveillance: Systematic Review and Meta-analysis

Background

Influenza causes considerable disease burden each year, particularly in children. Monitoring school absenteeism has long been proposed as a surveillance tool of influenza activity in the community, but the practice of school absenteeism could be varying, and the potential of such usage remains unclear.

Objective

The aim of this paper is to determine the potential of monitoring school absenteeism as a surveillance tool of influenza.

Methods

We conducted a systematic review of the published literature on the relationship between school absenteeism and influenza activity in the community. We categorized the types of school absenteeism and influenza activity in the community to determine the correlation between these data streams. We also extracted this correlation with different lags in community surveillance to determine the potential of using school absenteeism as a leading indicator of influenza activity.

Results

Among the 35 identified studies, 22 (63%), 12 (34%), and 8 (23%) studies monitored all-cause, illness-specific, and influenza-like illness (ILI)–specific absents, respectively, and 16 (46%) used quantitative approaches and provided 33 estimates on the temporal correlation between school absenteeism and influenza activity in the community. The pooled estimate of correlation between school absenteeism and community surveillance without lag, with 1-week lag, and with 2-week lag were 0.44 (95% CI 0.34, 0.53), 0.29 (95% CI 0.15, 0.42), and 0.21 (95% CI 0.11, 0.31), respectively. The correlation between influenza activity in the community and ILI-specific absenteeism was higher than that between influenza activity in community all-cause absenteeism. Among the 19 studies that used qualitative approaches, 15 (79%) concluded that school absenteeism was in concordance with, coincided with, or was associated with community surveillance. Of the 35 identified studies, only 6 (17%) attempted to predict influenza activity in the community from school absenteeism surveillance.

Conclusions

There was a moderate correlation between school absenteeism and influenza activity in the community. The smaller correlation between school absenteeism and community surveillance with lag, compared to without lag, suggested that careful application was required to use school absenteeism as a leading indicator of influenza epidemics. ILI-specific absenteeism could monitor influenza activity more closely, but the required resource or school participation willingness may require careful consideration to weight against the associated costs. Further development is required to use and optimize the use of school absenteeism to predict influenza activity. In particular, the potential of using more advanced statistical models and validation of the predictions should be explored.

Factors influencing sensitivity of a rapid influenza diagnostic test in a community-based population of kindergarten through 12th-grade students: Wisconsin 2015-2020

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.