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SYSTEMATIC OBSERVATION OF COVID-19 MITIGATION (SOCOM): ASSESSING FACE COVERING AND DISTANCING IN SCHOOLS
Preprint
em Inglês
| medRxiv
| ID: ppmedrxiv-21253522
ABSTRACT
IntroductionDuring the COVID-19 pandemic, some K-12 schools resumed in-person classes with varying degrees of mitigation plans in the fall of 2020. Physical distancing and face coverings can minimize SARS-CoV-2 spread, the virus that causes COVID-19. However, no research has focused on mitigation strategy adherence during school days. Thus, we sought to develop a systematic observation protocol to capture COVID-19 mitigation strategy adherence in school environments The Systematic Observation of COVID-19 Mitigation (SOCOM). MethodsWe extended previously validated and internationally used tools to develop the SOCOM training and implementation protocol to assess physical distancing and face covering behaviors. SOCOM was tested in diverse indoor and outdoor settings (classrooms, lunchrooms, physical education [PE], and recess) among diverse schools (elementary, secondary, and special needs). ResultsFor the unique metrics of physical-distancing and face-covering behaviors, areas with more activity and a maximum of 10-15 students were ideal for accurately capturing data. Overall proportion of agreement was high for physical distancing (90.9%), face covering (88.6%), activity type (89.2%), and physical activity level (87.9%). Agreement was lowest during active recess, PE, and observation areas with [≥]20 students. ConclusionsMillions of children throughout the US are likely to return to school in the months ahead despite the current surge of COVID-19 cases. SOCOM is a relatively inexpensive tool that can be implemented by schools to determine mitigation strategy adherence and assess changes to protocols to help students return to school safely and slow the spread of COVID-19 and can be used for research purposes.
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Texto completo:
Disponível
Coleções:
Preprints
Base de dados:
medRxiv
Tipo de estudo:
Estudo observacional
/
Estudo prognóstico
/
Revisão sistemática
Idioma:
Inglês
Ano de publicação:
2021
Tipo de documento:
Preprint