ABSTRACT
BACKGROUND: As coronavirus disease 2019 (COVID-19) transmission depends on factors such as demography, comorbidity, and patterns of daily activity, a better understanding of the societal factors of the infection among students would be useful in planning prevention strategies. However, no studies to date have focused on societal factors associated with COVID-19 transmission among students. PURPOSE: This study aimed to characterize the factors of a student population associated with COVID-19 transmission in the metropolitan city of Seoul, South Korea. METHODS: We analyzed the epidemiological data for laboratory-confirmed (reverse transcription polymerase chain reaction) COVID-19 cases collected by the Korea Disease Control and Prevention Agency and Ministry of Education from January 2020 to October 2021. We calculated the global Moran's index, local Moran's index, and Getis-Ord's index. A spatial regression analysis was performed to identify sociodemographic predictors of COVID-19 at the district level. RESULTS: The global spatial correlation estimated by Moran's index was 0.082 for the community population and 0.064 for the student population. The attack rate of adults aged 30- 59 years (P=0.049) was associated with an increased risk of COVID-19 attack rates in students, whereas the number of students per primary- (P=0.003) and middle- (P=0.030) school class was inversely associated with risk of COVID-19 attack among students. CONCLUSION: We found that COVID-19 transmission was more attributable to the community-level burden in students than adults. We recommend that public health initiatives target initiatives that protect students from COVID-19 when the community carries a high burden of infection.
ABSTRACT
Identification of geographical areas with high burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in schools using spatial analyses has become an important tool to guide targeted interventions in educational setting. In this study, we aimed to explore the spatial distribution and determinants of coronavirus disease 2019 (COVID-19) among students aged 3-18 years in South Korea. We analysed the nationwide epidemiological data on laboratory-confirmed COVID-19 cases in schools and in the communities between January 2020 and October 2021 in South Korea. To explore the spatial distribution, the global Moran's I and Getis-Ord's G using incidence rates among the districts of aged 3-18 years and 30-59 years. Spatial regression analysis was performed to find sociodemographic predictors of the COVID-19 attack rate in schools and in the communities. The global spatial correlation estimated by Moran's I was 0.647 for the community population and 0.350 for the student population, suggesting that the students were spatially less correlated than the community-level outbreak of SARS-CoV-2. In schools, attack rate of adults aged 30-59 years in the community was associated with increased risk of transmission (P < 0.0001). Number of students per class (in kindergartens, primary schools, middle schools and high schools) did not show significant association with the school transmission of SARS-CoV-2. In South Korea, COVID-19 in students had spatial variations across the country. Statistically significant high hotspots of SARS-CoV-2 transmission among students were found in the capital area, with dense population level and high COVID-19 burden among adults aged 30-59 years. Our finding suggests that controlling community-level burden of COVID-19 can help in preventing SARS-CoV-2 infection in school-aged children.