Class-specific school closures for seasonal influenza: Optimizing timing and duration to prevent disease spread and minimize educational losses - Masumoto, Yukiko; Kawasaki, Hiromi; Matsuyama, Ryota; Tsunematsu, Miwako; Kakehashi, Masayuki (PLOS ONE, 2025)
School closures are a safe and important strategy for preventing infectious diseases in schools. However, the effects of school closures have not been fully demonstrated, and prolonged school closures have a negative impact on students and communities. This study evaluated class-specific school closure strategies to prevent the spread of seasonal influenza and determine the optimal timing and duration. We constructed a new model to describe the incidence of influenza in each class based on a stochastic susceptible-exposed-infected-removed model. We collected data on the number of infected absentees and class-specific school closures due to influenza from four high schools and the number of infected cases from the community in a Japanese city over three seasons (2016–2017, 2017–2018, and 2018–2019). The parameters included in the model were estimated using epidemic data. We evaluated the effects of class-specific school closures by measuring the reduced cumulative incidence of class closures per day. The greatest reduction in the cumulative absences per day was observed in the four-day class closure. When class-specific school closures lasted for four days, the reduction in the cumulative number of infections per class closure day was greater when the closure was timed earlier. The highest reduction in the number of class closures per person-day occurred when the threshold was around 5.0%. Large variations in the reduction of cumulative incidence were noted owing to stochastic factors. Reactive, class-specific school closures for seasonal influenza were most efficient when the percentage of newly infected students exceeded around 5.0%, with a closure duration of four days. The optimal strategy of class-specific school closure provides good long-term performance but may be affected by random variations.