Optimization of school closures during an Omicron epidemic in Hong Kong: a modelling study.

Closing schools has been a prominent public health control measure for respiratory virus pandemics. However, during the COVID-19 pandemic, they were more contentious, as children were at a lower risk of severe disease while prolonged closures could have affected children's development. Hong Kong experienced a large Omicron epidemic in the spring of 2022, and face-to-face classes were halted and reopened after the peak with daily rapid-antigen test screening. Using counterfactual simulations, we developed a susceptible-exposed-infectious-recovered model calibrated to severe disease data to estimate the impact of the school closures and screening measures. We estimated that the school closures and screening measures prevented an excess of 35.0% (33.2%, 38.8%) more deaths and 17.4% (15.0%, 19.9%) more hospitalizations in a counterfactual scenario without those interventions. In terms of the impact on disease burden, the closure of primary schools outperformed both the closure of secondary schools and rapid antigen testing. Rapid-antigen screening alone was also an effective measure while minimizing the disruption associated with school closures. This demonstrates that implementing school-non-pharmaceutical intervention requires input from community priorities, balancing the population-wide burden of disease (infections, hospitalizations or mortalities) or educational disruptions (missed school days) and economic repercussions (e.g. the cost of daily rapid-antigen screening).