Rotation-based schedules in elementary schools to prevent COVID-19 spread: a simulation study

Area of Science:

• Epidemiology and Public Health
• Computational Modeling
• Infectious Disease Dynamics

Background:

• COVID-19 pandemic necessitated non-pharmacological interventions in educational settings.
• Understanding transmission dynamics within schools is crucial for effective control strategies.

Purpose of the Study:

• To investigate the impact of different rotation and testing schedules as non-pharmacological interventions for COVID-19 in schools.
• To model the spread of COVID-19 within a school environment using agent-based and SEIR models.

Main Methods:

• Developed an agent-based model simulating interactions among 624 schoolchildren and 55 teachers in an elementary school.
• Utilized a modified SEIR model on a multi-graph structure representing social contacts (classroom, cafeteria, etc.).
• Calibrated model parameters using data from the Czech Republic's spring 2020 COVID-19 outbreak.

Main Results:

• Weekly rotations of in-class and distance learning reduced COVID-19 spread by 75-81%.
• Antigen testing twice weekly or PCR testing weekly significantly reduced infections, even with lower sensitivity tests.
• Teacher networks are denser, acting as bridges and contributing significantly to infections (8-18% depending on school level).

Conclusions:

• Weekly school rotations combined with regular testing are highly effective non-pharmacological interventions against COVID-19 spread.
• These strategies are vital for maintaining school operations during epidemics.
• Social contact structures, particularly teacher networks, significantly influence disease transmission in schools.