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.
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.
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.
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.
We analyzed 4,352 participant- and staff-collected respiratory specimens from 2,796 subjects in the Oregon Child Absenteeism due to Respiratory Disease Study. Trained staff collected oropharyngeal ...specimens from school-aged children with acute respiratory illness while household participants of all ages collected their own midturbinate nasal specimens in year one and anterior nasal specimens in year two. Human ribonuclease P levels were measured using RT-PCR for all staff- and participant-collected specimens to determine adequacy, defined as Cycle threshold less than 38. Overall, staff- and participant-collected specimens were 99.9% and 96.4% adequate, respectively. Participant-collected midturbinate specimens were 95.2% adequate in year one, increasing to 97.2% in year two with anterior nasal collection. The mean human ribonuclease P Cycle threshold for participant-collected specimens was 31.18 in year one and 28.48 in year two. The results from this study suggest that community-based participant collection of respiratory specimens is comparable to staff-collected oropharyngeal specimens, is feasible, and may be optimal with anterior nasal collection.
Rapid influenza diagnostic tests (RIDT) demonstrate varying sensitivities, often necessitating reverse transcriptase polymerase chain reaction (RT-PCR) to confirm results. The two methods generally ...require separate specimens. Using the same anterior nasal swab for both RIDT and molecular confirmation would reduce cost and waste and increase patient comfort. The aim of this study was to determine if RIDT residual nasal swab (rNS) specimens are adequate for RT-PCR and whole genome sequencing (WGS). We performed RT-PCR and WGS on paired rNS and nasopharyngeal or oropharyngeal (NP/OP) swab specimens that were collected from primary care patients across all ages. We randomly selected 199 and 40 paired specimens for RT-PCR and WGS, respectively, from the 962 paired surveillance specimens collected during the 2014-2015 influenza season. Sensitivity and specificity for rNS specimens were 81.3% and 96.7%, respectively, as compared to NP/OP specimens. The mean cycle threshold (Ct) value for the NP/OP specimen was significantly lower when the paired specimens were both positive than when the NP/OP swab was positive and the nasal swab was negative (25.5 vs 29.5; p<0.001). Genomic information was extracted from all 40 rNS specimens and 37 of the 40 NP/OP specimens. Complete WGS reads were available for 67.5% (14 influenza A; 13 influenza B) of the rNS specimens and 59.5% (14 influenza A; 8 influenza B) of the NP/OP specimens. It is feasible to use a single anterior nasal swab for RIDT followed by RT-PCR and/or WGS. This approach may be appropriate in situations where training and supplies are limited. Additional studies are needed to determine if residual nasal swabs from other rapid diagnostic tests produce similar results.
Background
Influenza viruses pose significant disease burdens through seasonal outbreaks and unpredictable pandemics. Existing surveillance programs rely heavily on reporting of medically attended ...influenza (MAI). Continuously monitoring cause‐specific school absenteeism may identify local acceleration of seasonal influenza activity. The Oregon Child Absenteeism Due to Respiratory Disease Study (ORCHARDS; Oregon, WI) implements daily school‐based monitoring of influenza‐like illness‐specific student absenteeism (a‐ILI) in kindergarten through Grade 12 schools and assesses this approach for early detection of accelerated influenza and other respiratory pathogen transmission in schools and surrounding communities.
Methods
Starting in September 2014, ORCHARDS combines automated reporting of daily absenteeism within six schools and home visits to school children with acute respiratory infection (ARI). Demographic, epidemiological, and symptom data are collected along with respiratory specimens. Specimens are tested for influenza and other respiratory viruses. Household members can opt into a supplementary household transmission study. Community comparisons are possible using a pre‐existing and highly effective influenza surveillance program, based on MAI at five family medicine clinics in the same geographical area.
Results
Over the first 5 years, a‐ILI occurred on 6634 (0.20%) of 3,260,461 student school days. Viral pathogens were detected in 64.5% of 1728 children with ARI who received a home visit. Influenza was the most commonly detected virus, noted in 23.3% of ill students.
Conclusion
ORCHARDS uses a community‐based design to detect influenza trends over multiple seasons and to evaluate the utility of absenteeism for early detection of accelerated influenza and other respiratory pathogen transmission in schools and surrounding communities.
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
Background
Schools are purported to be primary venues of influenza transmission and 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. Methods. We conducted a 3-year, 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, Oregon, WI (OSD: enrollment = 3,900 students). Absenteeism reporting was facilitated by automated processes within OSD’s electronic student information system. Students were screened for ILI, and, if eligible, visited at home, where pharyngeal specimens were collected for influenza RT-PCR (IVD CDC Human Influenza Virus RT-PCR Diagnostic Panel) and multipathogen testing (Luminex NxTAG RPP). The study definition of a-ILI was validated for 700 children with acute respiratory infections using binomial logistic regression. Surveillance of medically attended laboratory-confirmed influenza (MAI) occurred in five primary care clinics in and adjoining OSD as part of the Wisconsin Influenza Incidence Surveillance Project using the same laboratory testing. Poisson general additive log linear regression models of daily counts of absenteeism and MAI were compared using correlation analysis. Results. Influenza A and B were detected in 54 and 51 of the 700 visited students, respectively. Influenza was significantly associated with a-ILI status (OR = 4.74; 95% CI: 2.78—8.18; P < 0.001). Of MAI patients, 371 had influenza A and 143 had influenza B. a-I was significantly correlated with MAI in the community (r = 0.472; P < 0.001) with a 15-day lead time. a-ILI was significantly correlated with MAI in the community (r = 0.480; P < 0.001) with a 1-day lead time. a-TOT performed poorly (r = 0.278; P < 0.001), following MAI by 9 days (Figure 1). Conclusion. Surveillance using cause-specific absenteeism was feasible to implement in OSD and performed well over a 3-year period marked by diverse presentations of seasonal influenza. Monitoring a-I and a-ILI can detect influenza outbreaks in the community, providing early warning in time for community mitigation efforts for seasonal and pandemic influenza.
Disclosures
All authors: No reported disclosures.
ObjectiveThe Oregon Child Absenteeism due to Respiratory Disease Study (ORCHARDS) was implemented to assess the relationships between cause-specific absenteeism within a school district and medically ...attended influenza visits within the same community.IntroductionTransmission and amplification of influenza within schools has been purported as a driving mechanism for subsequent outbreaks in surrounding communities. However, the number of studies assessing the utility of monitoring school absenteeism as an indicator of influenza in the community is limited. ORCHARDS was initiated to evaluate the relationships between all-cause (a-Tot), illness-related (a-I), and influenza-like illness (ILI)-related absenteeism (a-ILI) within a school district and medically attended influenza A or B visits within the same community.MethodsORCHARDS was based at the Oregon School District (OSD), which enrolls 3,640 students at six schools in south-central Wisconsin. Parents reported influenza-like symptoms on an existing phone-based absenteeism reporting system. Attendance staff identified ILI using a simple case definition. Absenteeism was logged into the OSD’s existing electronic information system (Infinite Campus), and an automated process extracted counts of a-Tot, a-I, and a-ILI each school day from 9/02/14 through 6/08/17.Parents of students with acute respiratory infections (ARI) were invited to contact study staff who assessed the students’ eligibility for the study based on presence of ILI symptoms. From 1/05/15 through 6/08/17, data and nasal swabs were collected from eligible OSD students whose parents volunteered to have a study home visit within 7 days of ILI onset. Specimens were tested for influenza A and B at the Wisconsin State Laboratory of Hygiene using the CDC Human Influenza Virus Real-time RT-PCR Diagnostic Panel.For community influenza, we used data from the Wisconsin Influenza Incidence Surveillance Project (WIISP) that monitors medically attended influenza using RT-PCR at five primary care clinics surrounding the OSD.Data analysis: Over-dispersed Poisson generalized additive log-linear regression models were fit to the daily number of medically attended influenza cases and daily absenteeism counts from three sources (a-Tot, a-I, and a-ILI) with year and season (calendar day within year) as smooth functions (thin plate regression splines). Two subgroups of a-ILI representing kindergarten through 4th grade (K-4) and 5th-12th grade (5-12) were also evaluated.ResultsDuring the study period, 168,859 total absentee days (8.57% of student days), 36,104 illness days (1.83%), and 4,232 ILI days (0.21%) were recorded. Home visits were completed on 700 children mean age = 10.0 ± 3.5 (sd) years. Influenza RT-PCR results were available for 695 (99.3%) children: influenza A was identified in 54 (13.3%) and influenza B in 51 (12.6%) specimens. There were one large and early outbreak of influenza A (H3N2) followed by B in 2014/15, an extremely late combined outbreak of influenza A (H1N1) and B in 2015/16, and a combined outbreak of influenza A/(H3N2) and B in 2016/17. PCR detection of influenza A or B, as compared to no influenza, was strongly associated with a child with a-ILI-positive status (OR=4.74; 95% CI: 2.78-8.18; P<0.001).Nearly 2,400 medically attended ARI visits were reported during the study period. Of these, 514 patients were positive for influenza (21.5%): 371 (15.5%) influenza A and 143 (6.0%) influenza B. The temporal patterns of medically attended influenza were very similar to influenza cases in OSD students.Comparisons of the regression models demonstrated the highest correlation between absenteeism and medically attended influenza for 5th-12th grade students absent with ILI with a -1 day time lag and for all students with a-ILI with a -1 day lag (Table); a-I also had moderate correlation with a -15 day lag period.ConclusionsCause-specific absenteeism measures (a-I and a-ILI) are moderately correlated with medically attended influenza in the community and are better predictors than all-cause absenteeism. In addition, a-I preceded community influenza cases by 15 days. The monitoring system was easily implemented: a-I surveillance was fully automated and a-ILI required only minor review by attendance staff. The resulting correlations were likely lowered by the presence of other viruses that resulted in a-ILI (e.g., adenovirus) and by breaks in the school year during which absenteeism data did not accrue.Automated systems that report cause-specific absenteeism data may provide a reliable method for the early identification of influenza outbreaks in communities. From a preparedness perspective, 15-day advance warning is significant. The addition of a laboratory component could increase usefulness of the cause-specific student absenteeism monitoring as an early-warning system during influenza pandemics.
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