Background: As the COVID-19 pandemic spread, school district administrators in the United States were faced with difficult decisions regarding the implementation of virtual or in-person learning to reduce risk of infection throughout student and staff populations. While a coordinated effort with surrounding districts would be most beneficial when encountering a highly infectious respiratory-based infectious disease, the determinants of type of education delivery is unclear.
Methods: Data from the Missouri Department of Elementary and Secondary Education assessing education delivery method at each school district across the state of Missouri (n = 514) from August 2020 were used. This cross-sectional study, using results from a school district-level survey, local COVID-19 rates, and community-level sociodemographic characteristics, conducted a spatially adjusted analysis of variance (ANOVA) to determine associations between education delivery type and geographic-level sociogeographic characteristics.
Results: Among Missouri school districts, 172 (33.4%) reported starting the 2020-2021 academic year with an in-person policy, 52 (10.1%) with a distant/virtual policy, 242 (47.1%) in-person with a distance option, and 48 (9.3%) with a blended policy. This study found districts with lower household income levels were less likely to offer students any virtual learning options. Additionally, community COVID-19 infection rates were not associated with the selection of virtual or in-person education delivery.
Conclusions: These findings suggest the presence of a specific school policy was spatially random in regard to neighboring community policies, even when accounting for community characteristics. The efficacy of policy is likely to benefit upon application of a spatial framework when addressing a crisis fundamentally tied to location. Future planning that highlights and focuses on regional coordination for community resilience in the face of a pandemic should incorporate data sources that inform decisions made for families, students, and communities.
Keywords: data-driven decision-making in school health; school climate, ie, social and emotional; school health program planning.
© 2022 American School Health Association.