Shut and re-open: the role of schools in the spread of COVID-19 in Europe

Abstract

We investigate the effect of school closure and subsequent reopening on the transmission of COVID-19, by considering Denmark, Norway, Sweden and German states as case studies. By comparing the growth rates in daily hospitalizations or confirmed cases under different interventions, we provide evidence that school closures contribute to a reduction in the growth rate approximately 7 days after implementation. Limited school attendance, such as older students sitting exams or the partial return of younger year groups, does not appear to significantly affect community transmission. In countries where community transmission is generally low, such as Denmark or Norway, a large-scale reopening of schools while controlling or suppressing the epidemic appears feasible. However, school reopening can contribute to statistically significant increases in the growth rate in countries like Germany, where community transmission is relatively high. In all regions, a combination of low classroom occupancy and robust test-and-trace measures were in place. Our findings underscore the need for a cautious evaluation of reopening strategies. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Keywords: COVID-19; non-pharmaceutical interventions; school closure; school reopening.

Figure 1.

Modelled and observed cases in (a) Baden-Württemberg, (b) Hesse, (c) Lower Saxony, and (d) Rhineland-Palatinate. Hesse and Rhineland-Palatinate (b,d), where final year high school exams took place in late March, saw a similar response to interventions to other German states with moderate incidence (c) where exams did not take place at that time. While there is insufficient scope in the data to assess the effect of the full examination period, we should in principle be able to detect a signal related to the beginning of the examination period. Assuming stability and homogeneity across states, and given the lack of such a signal, it is unlikely that these exams significantly contributed to the overall outbreak. (Online version in colour.)

Figure 2.

Modelled and observed daily cases in Sweden. (Online version in colour.)

Figure 3.

Confirmed cases in staff (red) and students (blue) in schools, kindergartens, holiday camps and other educational facilities for under-18s (age distribution not known) in Germany. (a) Daily new confirmed cases; (b) instantaneous growth rate (shaded regions are 95% confidence intervals). Solid vertical lines indicate when students returned to school, and dashed lines indicate other changes to public measures. In April and early May with small numbers of primary school or exam students returning, there was no notable difference between the incidence among students and staff. Accounting for the lag time, the incidence among students was higher than that of staff following 18 May.

Figure 4.

Daily hospital admissions with COVID-19 in Germany, excluding those working in education, front-line healthcare workers, carers, catering and hospitality, thus representing transmission in the general, average-exposure population. (a) Daily admissions; (b) instantaneous growth rate (shaded regions are 95% confidence intervals). The continuing decline in admissions suggests that the return of younger (and exam) students did not present a statistically significant impact on the general hospitalized population. It is worth bearing in mind that hospital admissions lag further behind than confirmed cases. Additionally, since very few young people have been hospitalized, an additional generation time of 6 days [27] may need to be added to this lag to account for students infecting older age groups. (Online version in colour.)

Figure 5.

Daily hospitalizations with COVID-19 in Denmark. Admissions are shown in (a), and (b) shows the instantaneous growth rate (shaded regions are 95% confidence intervals). A longer lag time of 10–14 days is in effect from infection to hospitalization [18], with a further 6 days’ generation time [27] to account for subsequent infection generations owing to the low hospitalization rate among children. Solid vertical lines indicate when students returned to school, and dashed lines indicate other interventions. (Online version in colour.)

Figure 6.

Daily confirmed cases in Norway. (a) New cases; (b) instantaneous growth rate (shaded regions are 95% confidence intervals). Solid vertical lines indicate when students returned to school, and dashed lines indicate other interventions. (Online version in colour.)