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The opening of schools in late summer of 2009 may have triggered the fall wave of pandemic influenza A(H1N1) in the United States. We found that elevated percent of outpatient visits for influenza-like illness (ILI%) occurred an average of 14 days after schools opened in a state in the fall of 2009. The timing of these events was highly correlated (Spearman’s correlation coefficient=0.62, p < 1.0 × 10−5). This result provides evidence that transmission in schools catalyzes community-wide transmission. School opening dates can be useful for future pandemic planning, and influenza mitigation strategies should be targeted at school populations before the influenza season.
Fall school openings have been consistently associated with an increase in the transmission of respiratory agents, including occasionally influenza . It is difficult to measure the contribution of schools to influenza transmission in a community. School holidays and other closures have been used to estimate the impact of closing schools on reducing seasonal influenza transmission . Such studies may provide the best insight into the role of schools in community-wide transmission, but these natural experiments generally occur in the midst of widespread transmission. With the recent pandemic influenza A(H1N1) (pandemic H1N1) epidemic in the United States, we have the unique opportunity to observe the effect of opening schools on the beginning of an epidemic.
We hypothesize that the opening of schools in the fall of 2009 led to regional surges in pandemic influenza A (H1N1) in the United States. Pandemic H1N1 arrived in the USA in the spring of 2009 and continued to circulate outside the influenza season . Out-of-season outbreaks occurred in summer camps and other settings. Because the US was heavily seeded with cases through the summer, some researchers had predicted an early peak (October) for pandemic H1N1, as was the case for Asian influenza A(H2N2) in 1957–1958 [4; 5]. The opening of schools might have been sufficient to trigger the observed state-wide outbreaks. Typically, influenza season in the temperate Northern hemisphere is between November and March, well after schools are open, so the effect of school openings at the onset of an influenza epidemic is seldom observed. Here, we study the temporal relationship between the opening of public schools in the United States and the observed increase of influenza-like illness.
Influenza activity in each state can be monitored by the percentage of outpatient visits for influenza-like illness (ILI%) as reported by the US Outpatient Influenza-like Illness Surveillance Network (ILINet) each week . ILI is defined as “fever and a cough or a sore throat in the absence of a known cause other than influenza.” The United States Centers for Disease Control and Prevention (CDC) reports ILI% data both as a national average (http://www.cdc.gov/flu/weekly/weeklyarchives2009-2010/data/senAllregt02.htm, accessed January 20, 2010) and by multi-state U. S. Department of Health and Human Services regions (http://www.cdc.gov/flu/weekly/regions2009-2010/hhssenusmap.htm, accessed January 20, 2010).
We defined the onset of elevated ILI activity to be the first date on which the ILI% exceeded baseline levels. Because of regional differences in ILI%, the CDC defined independent baselines for the ten multi-state regions in the United States . The CDC defines the baseline level of ILI% to be “the mean percentage of patient visits for ILI during non-influenza weeks for the previous three seasons plus two standard deviations.”
Because the CDC reports ILI% by large geographic regions only, we used Google Flu Trends for ILI% at the state level . Google Flu Trends provides up-to-date estimates of ILI% in the United States at the state and national levels. The state-level ILI% data used in this report were obtained from http://www.google.org/flutrends/us/ on January 20, 2010. In our analyses, we used the appropriate regional baseline as the baseline level for each state.
Public school opening dates for nineteen states and the District of Columbia were available from their respective departments of education. States would report these dates either by district or by individual school. For the remaining twenty-nine states in the continental United States, we obtained opening dates from 25 randomly sampled school districts per state. We defined a state’s school opening date to be the median of the first day of classes in its school districts (or individual schools). Results were not appreciably different when the first or third quartiles of the opening dates were used instead. Although the districts can vary greatly in size, the use of random sampling should produce an unbiased estimate of the median. The median opening dates for each state were between August 6 and September 9, 2009. The average variance of school or district openings within a state was 18 days (range of 0 to 114 days). The mean standard deviation was 3.8 days, ranging from 0.0 to 10.7 days.
The public school opening date for each Department of Health and Human Services region was estimated by randomly sampling with replacement 10,000 opening dates from the appropriate states’ data (described above), with the sampling weight proportional to the state’s population estimate in 2009 (from http://www.census.gov/popest/states/NST-ann-est.html, accessed November 10, 2009).
To quantify the relationship between school opening dates and elevated ILI%, we used linear regression and the Spearman correlation test. We computed the 95% confidence envelope using R’s predict function. ILI% is reported weekly, so linear interpolation was used to estimate the day on which the ILI% first crossed the regional baseline in the summer or fall of 2009. Analyses were performed using the R statistical package version 2.9.2 .
Up until late summer 2009, the ILI% for each state was below the corresponding regional baseline established by the CDC. Between August 9 and September 24, the ILI% for each state surpassed the regional baselines (Figure 1a). Most of the elevated ILI activity in the fall of 2009 in the USA can be attributed to pandemic H1N1 because most sub-typed influenza A isolates have been pandemic H1N1 .
We found that the ILI% in each state did not exceed regional baselines until after schools opened except for one state (Minnesota) (Figure 1b). This occurred 1 to 32 days after the median school opening date in each state (mean of 14 days), except for Minnesota, where the regional baseline was surpassed five days before its median school opening date. The beginning of elevated influenza activity was highly correlated with the median school opening date (Figure 2, Spearman’s correlation coefficient = 0.62, p < 1.0 × 10−5). The expected increase in influenza activity would be about 19 days after the beginning of the first school openings (8/6/2009) or only 9 days after the beginning of the latest school openings (9/9/2009).
Using ILI% data from the CDC, which is aggregated by multi-state region, elevated ILI% activity and median school opening dates did not have a statistically significant relationship (result not shown). However, the slope of the regression line was not statistically different than the slope from the state-level analysis. The small number of data points (ten regions) and the large size of the regions made it difficult to discern the relationship between elevated ILI% and school opening dates by region.
Detectable widespread transmission of pandemic H1N1 appears to occur two weeks after the schools in a state open. This information should be useful for future pandemic planning and control. When there is a pandemic influenza threat, vaccines and other control measures should be in place at least two weeks before schools open [5; 9]. For seasonal influenza, school-based vaccination should be carried out before or shortly after schools open.
The results of this study could be refined with data at finer spatial and temporal resolutions. The CDC ILI% data was aggregated by multi-state region, which makes it difficult to determine the timing of outbreaks on the school district level. In addition, the regional ILI% baseline values we used may not have captured the variation in baselines that could exist within a region. We therefore used Google Flu Trends’ state-level data, which could not be validated against actual ILI% data by state but had had been validated against data provided by the state of Utah in the original description . ILI% data is reported weekly, so we had to use linear interpolation to estimate daily values. Ideally, a consistent definition of community-wide transmission at a fine geographic resolution should be used.
The lag between median school opening date and elevated ILI% shrank from August to September, from 19 to 9 days. Our analyses assumed that the transmissibility was constant from late summer to early fall. Many factors that are believed to affect influenza transmission, such as weather, may have changed during this time . In addition, transmission from adjacent states with earlier influenza epidemics could have lead to earlier epidemics in states with late school start dates.
Computer simulations can be used to explore the interactions between school closures and other mitigation strategies [11; 12]. Epidemic simulations and models require a variety of data for calibration, and observations of the dynamics of pandemic H1N1 complement the available data. Including school opening dates in models might be su cient to reproduce the differences in regional peaks of influenza activity in the United States and possibly other countries in the Northern hemisphere observed in the 2009–2010 influenza season.
Our findings are unique in that they suggest that a delay in the opening of schools could delay the onset of an impending epidemic. This effect probably depends on the relatively high prevalence of the virus before the beginning of the school year. There are no strict guidelines on the strategic use of school closures for epidemic mitigation or prevention . Although closures can be used for short periods of time to stop outbreaks in schools , widespread transmission may resume once schools are re-opened. Currently, the CDC does not generally recommend reactive dismissals (http://www.cdc.gov/h1n1flu/schools/technicalreport.htm, accessed 1/25/2010). School dismissals may protect the staff and children at high risk, but are not likely to reduce community transmission. They may be used in conjunction with other mitigation strategies, such as vaccination. The cost of closing schools is high and might not be the most cost-effective option . However, community mitigation measures may be the only way to gain enough time to produce vaccine tailored to the epidemic strain or to increase hospital capacity to accommodate severe cases .
We thank Valerie Obenchain from the Fred Hutchinson Cancer Research Center, Robin Webb and Diane Wagener from RTI International, and Karen Lane from the Indiana Department of Education for assistance in gathering school opening data.
This work was partially supported by the National Institute of General Medical Sciences MIDAS grant U01-GM070749.
Previous presentation of this material:
This material has not been presented at meetings.
Conflict of interest statement:
The authors do not have any conflicts of interest to declare.
Changes in author affiliations: No changes since completion of the study.