The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causal agent of the coronavirus disease 19 (COVID-19), is highly transmissible and infectious. Schools are one of the hotspots for the spread of this virus, as they bring together children from several different households.
In the United States, K-12 schools have been opened in some counties; however, there is limited data that has determined whether the reopening of schools has contributed to a rise in COVID-19 cases.
Study: The association of opening K–12 schools with the spread of COVID-19 in the United States: County-level panel data analysis. Image Credit: Travelpixs / Shutterstock.com
A new study published in the Proceedings of the National Academy of Sciences finds that counties that opened K–12 schools experienced a significant increase in the growth rate of cases. The current study also documents stronger effects for counties where mask-wearing was not mandatory.
How does the opening of schools relate to the spread of COVID-19 infection? Are barrier strategies, such as mask-wearing at school, effective? These are two highly important questions, especially for countries that have low vaccination rates.
Scientists are studying these questions with renewed rigor, owing to the rapid emergence of highly infectious SARS-CoV-2 variants. If it could be established that school openings causally lead to a surge in cases, school authorities should take immediate steps to rectify the situation, such as implementing social distancing measures and mask mandates. The government could also prioritize vaccination for elderly parents.
In the current study, researchers used U.S. county-level panel data on K-12 school opening plans and mitigation strategies to determine if visits to K–12 schools caused a subsequent increase in COVID-19 cases.
About the study
The sample period for this study was from April 1. 2020 to December 2, 2020. Several outcome variables were used for the analysis, which included weekly cases and deaths, as well as their growth rates. The key independent variables were school openings and data on mitigation measures data.
The dynamic panel data regression model also included other variables, such as the number of tests and non-pharmaceutical policy interventions (NPIs). A seven-day moving average of variables was used to deal with periodic fluctuations.
In the current study. The researchers first conducted a preliminary event study analysis before estimating a dynamic panel regression. The event study results illustrated that the gap in cases/deaths per week per 1,000, between remote opening and full/hybrid opening, grew over time.