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Household effects of school closure during pandemic
(H1N1) 2009, Pennsylvania, USA.
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| Subject: |
Epidemics
(Analysis) Epidemics (Health aspects) Epidemics (Surveys) Influenza (Analysis) Influenza (Health aspects) Influenza (Surveys) |
| Authors: |
Gift, Thomas L. Palekar, Rakhee S. Sodha, Samir V. Kent, Charlotte K. Fagan, Ryan P. Archer, W. Roodly Edelson, Paul J. Marchbanks, Tiffany Bhattarai, Achuyt Swerdlow, David Ostroff, Stephen Meltzer, Martin I. |
| Pub Date: | 08/01/2010 |
| Publication: | Name: Emerging Infectious Diseases Publisher: U.S. National Center for Infectious Diseases Audience: Academic; Professional Format: Magazine/Journal Subject: Health Copyright: COPYRIGHT 2010 U.S. National Center for Infectious Diseases ISSN: 1080-6040 |
| Issue: | Date: August, 2010 Source Volume: 16 Source Issue: 8 |
| Product: | Product Code: 9124220 Centers for Disease Control NAICS Code: 92312 Administration of Public Health Programs |
| Organization: | Government Agency: United States. Centers for Disease Control and Prevention; United States. Centers for Disease Control and Prevention |
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| Accession Number: | 237533369 |
| Full Text: |
Some studies have suggested that school-age children are
influential in the ongoing transmission of influenza (1,2). Closing
schools may potentially reduce the spread of influenza (3,4). In mid-May
2009, an elementary school (kindergarten-4th grade) in a semirural area
of Pennsylvania closed for 1 week after an abrupt increase in
absenteeism due to influenza-like illness (ILI) and the confirmation of
influenza A pandemic (H1N1) 2009 virus infection in 1 student. Other
schools in the district remained open. From May 26 through June 2, 2009,
investigators from the Pennsylvania Department of Health and the Centers
for Disease Control and Prevention surveyed households with students at
the school by telephone to assess influenza symptoms, childcare
arrangements, movements of affected children during the school closure
period, and household demographics and socioeconomic status. This study
did not address the transmission effects, but assessed the potential
disruption to households resulting from school closure. The Investigation The survey was considered a public health response. School administrators provided contact information for households with children attending the school. Investigators asked to speak to an adult in the household. If an adult was available and consented, the survey was administered. For each day of school closure, respondents were asked for the following information: where the student spent most of the day; whether the student went elsewhere (prompted by specific venues), who watched the student; and whether the person watching the student missed work. Questions were asked regarding the oldest student if multiple children attended the school. Respondents were also asked, for each household member, whether the person had symptoms of ILI (defined as fever with cough and/or sore throat) between May 1, 2009, and the time of the survey. Children were defined as persons <18 years of age, and those [greater than ore equal to]18 years of age were considered adults. The online Technical Appendix (www.cdc.gov/EID/content/16/8/1315-Techapp.pdf) describes the process followed to calculate variables used in the analysis. The locations where students spent most of the day and other venues visited were tabulated. Significant differences in venues visited by students with and without ILI were determined by using the Fisher exact test. We computed unadjusted and adjusted odds ratios (ORs) for the following characteristics versus whether the household reported missing >1 workdays: whether the oldest student reported ILI (repeated for whether any adult, any student at the closed school, or any child in the household reported ILI), whether the household had a single child, whether the household had just 1 adult, whether all adults in the household worked outside the home, and whether household income was above the median (online Technical Appendix). Adjusted ORs were computed in a logistic regression model for variables that had unadjusted ORs significant at p<0.10 by the Fisher exact test. Surveys were completed for 214 (59%) of 364 households (59%), and accounted for 269 (59%) of the 456 students enrolled at the school. Table 1 shows the demographics of surveyed households. Most households had at least 2 adults, at least 2 wage earners, and [greater than or equal to]2 children. Households with incomes [greater than or equal to]$60,000 were at or above the median income. Because some of the oldest students spent days in multiple locations during the 5 days of school closure, we calculated the number of student-days at each venue (number of students at each type of venue multiplied by the number of days spent there). Home was the primary location during the school closure for 77% of the student-days (online Technical Appendix Figure 1). The next most common location was another family member's home. Sixty-nine percent of students visited other venues during school closure (online Technical Appendix Figure 2). Those reported as having ILI were more likely to have visited a healthcare provider than those without ILI (p<0.01), but no other statistically significant differences were found in terms of venues visited between those with ILI and those without ILI. Seventy-nine percent of households reported zero missed workdays (Table 1); of the remaining households in which work was missed, [approximately equal to]40% missed work during all 5 days of school closure. The only household characteristics for which the OR for missing any workdays was significantly different from 1 at p<0.10 were single child, all adults work, and household income is greater than or equal to median income (Table 2). When adjusted ORs were calculated, household income greater than or equal to median was significant at p<0.05, but because income data were only available for 184 households (vs. 214 for the other factors), the sample on which the adjusted ORs were calculated was somewhat different. All adults in the household working was significantly associated with household income greater than or equal to the median (p<0.01). Conclusions Estimating the economic effects of school closure can provide useful information to aid in estimating whether it is likely to achieve the intended goals. Households that reported missed work incurred costs, even if those costs were only in terms of lost vacation or sick time. In our study, only 22% of households reported missing any work to watch the students, fewer than during the closure in Australia (7). However, in ?40% of households in which work was missed, an adult missed work for all 5 days of closure, indicating a relatively large effect on those households (Table 1). A limitation is that the question regarding missed work was narrowly worded (online Technical Appendix) and did not explore whether an adult missed work for other reasons. As shown in Table 2, adult ILI was not significantly associated with missing work. Some adults with ILI may have stayed at home to watch students but determined that they would have stayed home because of their own illness had the school not been closed and answered "no." In the Kentucky school closure situation, 29% of households had working adults who provided childcare. In 16% of households, adults missed work and lost pay (6). Closures for >1 week may result in more households that report missing work days. The factors "all adults working" and "having a household income equal to or greater than the median" were associated with missed workdays, as were fewer children (other children in the home may have made it possible for some households to avoid having an adult miss work to watch students whose school was closed). These findings add to the body of literature on the effects of school closure on households. They can be used by decision makers, as well as parents, to assess the potential social disruption of school closure in the context of future influenza outbreaks. Members of the Pennsylvania H1N1 Working Group: from the Centers for Disease Control and Prevention, W. Roodly Archer, Frederick J. Angulo, John Beltrami, Achuyt Bhattarai, Paul J. Edelson, Ryan P. Fagan, Anthony Fiore, Thomas L. Gift, George S. Han, Charlotte K. Kent, Rebecca Leap, Amanda M. McWhorter, Martin I. Meltzer, Michael D. Nguyen, Benjamin L. Nygren; from the Pennsylvania Department of Health, Phyllis Britz, Brent Ennis, James Lute, Tiffany Marchbanks, Maria Moll, Steven Ostroff, Owen Simwale; and from the Pan American Health Organization, Rakhee S. Palekar. Acknowledgments We thank Harrell Chesson for helpful comments regarding the survey design and data analysis, and the Conrad Weiser Area School District for participating in the survey. This study/report was supported in part by an appointment to the Applied Epidemiology Fellowship Program administered by the Council of State and Territorial Epidemiologists and funded by CDC Cooperative Agreement U60/CCU007277. Dr Gift is an economist at the Centers for Disease Control and Prevention, Atlanta, Georgia. His research focuses on cost-effectiveness analysis of disease prevention interventions. References (1.) Monto AS, Davenport FM, Napier JA, Francis T Jr. Effect of vaccination of a school-age population upon the course of an A2/Hong Kong influenza epidemic. Bull World Health Organ. 1969;41: 537-42. (2.) Reichert TA, Sugaya N, Fedson DS, Glezen WP, Simonsen L, Tashiro M. The Japanese experience with vaccinating schoolchildren against influenza. N Engl J Med. 2001;344:889-96. DOI: 10.1056/NEJM200103223441204 (3.) Cauchemez S, Ferguson NM, Wachtel C, Tegnell A, Saour G, Duncan B, et al. Closure of schools during an influenza pandemic. Lancet Infect Dis. 2009;9:473-81. DOI: 10.1016/S1473-3099(09)70176-8 (4.) Wu JT, Cowling BJ, Lau EHY, Ip DK, Ho L-M, Tsang T, et al. School closure and mitigation of pandemic (H1N1) 2009, Hong Kong. Emerg Infect Dis. 2010;16:538-41. DOI: 10.3201/eid1603.091216 (5.) Johnson AJ, Moore ZS, Edelson P, Kinnane L, Davies M, Shay DK, J, et al. Household responses to school closure resulting from outbreak of influenza B, North Carolina. Emerg Infect Dis. 2008;14:1024-30. DOI: 10.3201/eid1407.080096 (6.) Centers for Disease Control and Prevention. Impact of seasonal influenza-related school closures on families--southeastern Kentucky, February, 2008. MMWR Morb Mortal Wkly Rep. 2009;58:1405-9. (7.) Effler PV, Carcione D, Giele C, Dowse GK, Goggin L, Mak DB. Household responses to pandemic (H1N1) 2009-related school closures, Perth, Western Australia. Emerg Infect Dis. 2010;16:205-11. Thomas L. Gift, Rakhee S. Palekar, Samir V. Sodha, Charlotte K. Kent, Ryan P. Fagan, W. Roodly Archer, Paul J. Edelson, Tiffany Marchbanks, Achuyt Bhattarai, David Swerdlow, Stephen Ostroff, and Martin I. Meltzer, for the Pennsylvania H1N1 Working Group1 Author affiliations: Centers for Disease Control and Prevention, Atlanta, Georgia, USA (T.L. Gift, S.V. Sodha, C.K. Kent, R.P. Fagan, W.R. Archer, P.J. Edelson, A. Bhattarai, D. Swerdlow, M.I. Meltzer); Pan American Health Organization, Washington, DC, USA (R.S. Palekar); and Pennsylvania Department of Health, Harrisburg, Pennsylvania, USA (T. Marchbanks, S. Ostroff) (1) Members of the Pennsylvania H1N1 Working Group are listed at the end of this article. Address for correspondence: Thomas L. Gift, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Mailstop E80, Atlanta, GA 30333, USA; email: tgift@cdc.gov DOI: 10.3201/eid1608.091827 Table 1. Demographic variables of households affected by school
closure during pandemic (H1N1) 2009, Pennsylvania, USA *
No. (%)
households
Variable ([dagger])
No. adults (>18 y)
1 25 (11.7)
2 157 (73.4)
>2 32 (15.0)
No. children (<18 y)
1 44 (20.6)
2 92 (43.0)
3 53 (24.8)
>3 25 (11.7)
Households with [greater than 34 (15.9)
or equal to]1 adult with ILI
Households with [greater than 88 (41.1)
or equal to]1 child with ILI
Households with the oldest 67 (31.3)
student with ILI
Household income (US$)
0-29,999 27 (12.6)
30,000-59,999 65 (30.4)
60,000-89,999 51 (23.8)
[greater than or equal 42(19.6)
to]90,000
Don't know/refused/missing 29 (13.6)
No. wage earners
1 64 (29.9)
2 135 (63.1)
[greater than or equal to]3 12 (5.6)
Don't know/refused/missing 3(1.4)
Time adult in household missed
work to watch oldest
student, d
0 168 (78.5)
1 13 (6.1)
2 7 (3.3)
3 4 (1.9)
4 4 (1.9)
5 18 (8.4)
% Adults in household who work
33 5 (2.3)
40 1 (0.5)
50 44 (20.6)
67 16 (7.5)
75 3 (1.4)
100 142 (66.4)
Don't know/refused/missing 3 (1.4)
* ILI, influenza-like illness.
([dagger]) Categories are mutually exclusive and exhaustive,
but percentages may not sum to 100% due to rounding.
Table 2. Predictors of households reporting days of work
missed to watch children during school closure for pandemic
(H1N1) 2009, Pennsylvania, USA* ([dagger])
Adjusted OR
Variable OR ([double dagger])
Oldest student with ILI 1.22
Any student with ILI 1.20
Any child with ILI 1.16
Any adult with ILI 1.67
Single adult 1.50
Single child 2.02 ([section]) 2.02 ([section])
All adults work 2.35 ([paragraph]) 2.08
Household income above 2.62 ([paragraph]) 2.31 ([paragraph])
median income
* OR, odds ratio; ILI, influenza-like illness.
([dagger]) When a household had >1 child attending the school
that was closed, we asked about time taken from work to watch the
oldest child.
([double dagger]) Adjusted OR estimated by logistic regression.
([section]) p<0.10.
([paragraph]) p<0.05. |
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