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medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.11.30.20241166

ABSTRACT

Background Until pharmaceutical measures are widely available to slow the spread of SARS-CoV-2, social distancing strategies are key to avert overwhelmed health systems. Since schools host large numbers of students in enclosed spaces, they are feared to produce infection clusters. With school closures coming at high social and economic costs, social distancing measures within schools are needed to make them as safe as possible. One widely discussed distancing measure in the school context is to use cohorting strategies, i.e., to split larger clusters such as classrooms into smaller groups that are instructed separately. In addition to facilitating social distancing within these cohorts, cohorting strategies also aim to prevent transmission across cohorts. However, little is known about which cohorting strategies are particularly effective to prevent disease transmission between cohorts in schools. Methods Using nationally representative data on adolescents in classrooms in four European countries, we simulate how four different cohorting strategies can mitigate the spread of SARS-CoV-2 in high schools. We model the effect of forming two cohorts randomly, splitting cohorts by gender, optimizing cohorts by minimizing students' out-of-school cross-cohort contacts, and approximating this optimization strategy by network chains. The rationale of all non-random cohorting strategies is to prevent the spread of SARS-CoV-2 from one cohort to the other by reducing cross-cohort out-of-school contact. We also compare the overall effect of cohorting to no cohorting and differentiate between a rota-system in which cohorts receive in-person instruction in alternating weeks and a system with separate but same-day in-person instruction for both cohorts. Data were collected between 2010 and 2011 as part of the CILS4EU project, a network panel study of 14-15-year-olds in England, Germany, the Netherlands, and Sweden. Across all four countries, we model the transmission of SARS-CoV-2 in 507 classrooms, capturing a total of 12,291 students. Findings Our simulations suggest that all four cohorting strategies reduce the spread of SARS-CoV-2 in classrooms, but vary in their effectiveness. Relative to random cohorting, all strategies that factor in out-of-school cross-cohort ties have particularly strong effects on the frequency of cross-cohort transmission but also substantively reduce the total number of infections and the share of students in quarantine when transmission dynamics are strong. Cohorting that explicitly minimizes out-of-school contact between students in different cohorts is most effective, but network-based approximation also breaks many cross-cohort ties and thus performs well. Because adolescents' out-of-school contacts tend to be strongly segregated by gender, dividing classrooms by gender also outperforms random cohorting but is less effective than directly using network information. For all cohorting strategies, rota-systems with instruction in alternating weeks contain outbreaks more effectively than same-day in-person instruction. Interpretation Cohorting of school classes as a social distancing measure can help to effectively curb SARS-CoV-2 outbreaks in the school context. If schools consider splitting up classes into two smaller cohorts, factoring in out-of-school contacts can help achieve a more effective separation of cohorts. The paper proposes effective cohorting strategies that outperform naive random cohorting in preventing the spread of SARS-CoV-2. These strategies may limit outbreaks to one cohort, keep the size of infection clusters low, and reduce the number of students in quarantine if an index case occurs in the student body. Our findings thus suggest that if schools consider cohorting, they should assign students who meet after school to the same cohort. In particular, cohorting on the basis of gender or network chains is effective and may be successfully implemented within the constraints posed by the classroom context.


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