Simulation results for 25 class closure patterns.
<p>A: Cumulative number of infected students. B: Total class closures, calculated as class-days. C: Total class closures, calculated as person-days. D: Reduction in absent students per day of class closure. Simulations were performed with five different start times for class closures, based on...
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2025
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| Summary: | <p>A: Cumulative number of infected students. B: Total class closures, calculated as class-days. C: Total class closures, calculated as person-days. D: Reduction in absent students per day of class closure. Simulations were performed with five different start times for class closures, based on the percentage of infected students (i.e., 2.0%, 4.0%, 5.0%, 6.0%, and 8.0%) and five class closure durations (0, 2, 3, 4, and 5 days). A duration of 0 days indicates the strategy of no class closures. Fig 2A shows the average cumulative number of infected students. Fig 2B shows the number of class closure in class-days, calculated by multiplying the number of closed classes by the closure duration for each scenario. Fig 2C shows the number of class closures in person-days, calculated by multiplying the number of infected students by closure duration for each scenario. Fig 2D shows the reduced number of cumulative absent students per day of class closure. This was calculated as follows: ([average number of infected students with no class closure − average number of infected students in each condition] × 5 days) / average number of class-days in each condition. Infected students were assumed to remain absent for five days (Fig 2).</p> |
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