key: cord-0947679-dokn0ntf authors: Michelson, Kenneth A; Samuels-Kalow, Margaret E title: Association of Elementary School Reopening Status and County COVID-19 Incidence date: 2021-09-20 journal: Acad Pediatr DOI: 10.1016/j.acap.2021.09.006 sha: 0716acc2d95474cb5405d09fd27cdbdcdf7730d0 doc_id: 947679 cord_uid: dokn0ntf OBJECTIVE: To examine the association between elementary school opening status (ESOS) and changes in pediatric COVID-19 incidence. METHODS: We conducted a cross-sectional study of US counties with school districts with ≥500 elementary school students. The main exposure was ESOS in September, 2020. The outcome was county incidence of COVID-19. Age-stratified negative binomial regression models were constructed using county adult COVID-19 incidence. RESULTS: Among 3,220 US counties, 618 (19.2%) were remote, 391 (12.1%) were hybrid, 2,022 (62.8%) were in-person. In unadjusted models, COVID-19 incidence after school started was higher among children in hybrid or in-person counties compared with remote counties. After adjustment for local adult incidence, among children aged 0-9, the incidence rate ratio of COVID-19 (IRR) compared with remote counties was 1.01 (95% confidence interval [CI] 0.93-1.08) in hybrid counties and 0.79 (95% CI 0.75-0.84) in in-person counties. CONCLUSIONS: Counties with in-person learning did not have higher rates of COVID-19 after adjustment for local adult rates. Optimal strategies for school reopening related to COVID-19 remain uncertain. 1 Virtual or hybrid instruction has been associated with increased rates of mental health risk and stress for parents, 2 but significant concerns remain regarding COVID-19 transmission from in-person instruction, with mixed reports on household transmission from in-person and hybrid schooling. 1, 3 British data suggest that that reopening high schools may be associated with higher community COVID-19 transmission than reopening elementary schools. 4 To help resolve these conflicting findings, the goal of this study was to examine the association between school district opening status and changes in pediatric COVID-19 incidence. We conducted a retrospective, cross-sectional study of US and Puerto Rico counties. The primary outcome was the county-level incidence of COVID-19 measured as cases per 100 susceptible person-years. Daily susceptible persons by age were calculated as the county population minus all prior COVID-19 cases in the age group. The main exposure variable was county-level ESOS, defined as remote, hybrid, or in-person. Counties with multiple school districts were defined using the modal ESOS by district land area within the county, so that counties could have only one ESOS assignment. Additional covariates were age group, defined as 0-9 years, 10-19 years, 20-59 years, and 60+ years; county socioeconomic status (SES), defined as counties' quintile of US Census Small Area Income and Poverty Estimates, incorporating data from the Internal Revenue Service, state/county Supplemental Nutrition Assistance Program benefits; and state/county poverty data files. We first determined the daily incidence of COVID-19 by age group and ESOS. We plotted daily COVID-19 rates before and after school opening in each age group by ESOS, using 7/1/2020-8/16/2020 as the before period, 8/17/2020-9/7/2020 as a middle wash-in period (a period in which schools started at varying times), and 9/8/2020-11/30/2020 as the after period. The wash-in period in was selected based on the weeks in which 82% of districts start. 8 To compare rates by time, we created age-stratified negative binomial regression models including time period (excluding the wash-in period), ESOS, and a time-ESOS interaction term. The interaction term evaluated the extent to which ESOS was associated with the degree of progression of COVID-19 rates over time. To assess the association between ESOS and pediatric COVID-19 rates, we constructed negative binomial regression models using COVID-19 incidence as the outcome. These models were designed to address confounding by transmission to children from adults and the effects of SES (which is independently associated with COVID-19 rates) on transmission. 9 Among 3,220 US counties, 618 (19.2%) were remote, 391 (12.1%) were hybrid, 2,022 (62.8%) were in-person, and 189 (5.9%) did not have an ESOS because no school districts with more than ≥500 elementary students were present (Supplemental Figure 1 ). Among children 0-9 years, COVID-19 incidence in counties with remote learning increased after school started (56%, 95% CI 32-85). Compared with remote learning, increases were 48% (95% CI 12-94) steeper in hybrid counties and 60% (95% CI 32-95) steeper in in-person counties. Among children 10-19 years, the incidence in counties with remote learning increased 71% (95% CI 46-101). Increases were steeper by 41% (95% CI 9-83) in hybrid counties and 75% (95% CI 45-110) steeper in in-person counties (Supplemental Figure 2 ). Similar results occurred in adults 20-59 years and ≥60 years. In unadjusted models, counties with hybrid or in-person ESOS, COVID-19 incidences in persons aged 0-9 years or 10-19 years were higher after school started compared with counties with remote learning (Table) . After adjustment for counties' adult COVID-19 rates, hybrid learning was not associated with differing rates of COVID-19 in children aged 0-9 but remained associated with modestly higher rates in persons aged [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] years. In-person learning was associated with decreased COVID-19 rates in children ages 0-9 but increased rates in persons ages 10-19, after adjustment for counties' rates of COVID-19 in adults. The addition of SES to the model did not change the interpretation from the adult-adjusted model. Sensitivity analyses reinterpreting counties' ESOS as the most locally permissive did not alter the association. When restricting to the 2,250 (69.9%) counties with only one ESOS, results were similar to the main analysis (Supplemental Table) . Our data demonstrated considerable variation in school opening status, similar to prior reports. 2 Hybrid and in-person ESOS was associated with higher COVID-19 incidence in unadjusted models, showing that areas with more permissive ESOS have more cases of COVID-19. Even with adjustment for local adult COVID-19 incidence and SES, hybrid and in-person learning were associated with higher rates of COVID-19 among individuals aged 10-19. However, the opposite was true in children aged 0-9, in whom in-person learning was associated with lower COVID-19 rates after adjustment for local adult rates and SES. There are several potential reasons for the differences observed between younger and older children. Studies have shown age-related differences in transmission risk within households, 9 and an increased risk of COVID-19 transmission from secondary schools versus primary schools. 4 We speculate that younger children may be more likely than older children to contract COVID-19 at home than school. Children attending in-person school settings may be exposed to fewer adults than those in remote settings due to adhoc childcare coverage. In contrast, older children may be more likely to transmit to peers and adults 10 thus making in-person schooling higher risk in the older age group. Locations outside of the home and school, including celebrations, are likely an important location of transmission for children, and could vary by age. 11 Children of different ages may also have variable adherence to mitigation measures such as social distancing and masking. These age-related differences could explain why unadjusted models of COVID-19 incidence, which reflect overall transmission within counties, differ from adjusted models, which reflect transmission independent of adults. This study had several limitations. First, some counties may have changed ESOS during the study period. Second, there are several hybrid models; we treated all hybrid models as the same because no single model was prevalent enough to analyze separately. Third, applying these findings to high school reopening decisions should be undertaken with caution, since we did not evaluate high school reopening status, nor were vaccines available to children during the study period. However, opening status was nearly always a district-wide policy and thus this was unlikely to affect our study results. 12 Fourth, we did not take specific mitigation measures into account, although adjusting for adult rates would be expected to partially account for this since adult rates are tied to local mitigation strategies. Fifth, counties can be heterogeneous in terms of characteristics and COVID-19 approaches, so our findings should be regarded as county-averaged associations. Sixth, due to data limitations we could not separate elementary students from preschool children by age, include small school districts, or include non-public schools. Finally, as a cross-sectional study, we were limited in our ability to evaluate causality of ESOS and COVID-19 rates. In conclusion, hybrid and in-person ESOS were associated with higher COVID-19 incidence in unadjusted models. Adjustment for local adult transmission negated the association for children 0-9 but not for those [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] . This finding suggests that additional investigation into the effects of school reopening should evaluate outcomes by age. Household COVID-19 risk and in-person schooling. Science (80-) Association of Children's Mode of School Instruction with Child and Parent Experiences and Well-Being During the COVID-19 COVID-19 Infections Among Students and Staff in New York City Public Schools Implications of the school-household network structure on SARS-CoV-2 transmission under school reopening strategies in England Back to school' means anytime from late July to after Labor Day Differential impact of mitigation policies and socioeconomic status on COVID-19 prevalence and social distancing in the United States Contact Tracing during Coronavirus Disease Outbreak, South Korea Assessing the Association Between Social Gatherings and COVID-19 Risk Using Birthdays Districts' Reopening Plans: A Snapshot. Education Week This work was supported by the Agency for Healthcare Research and Quality [grant number K08HS026503].