TL;DR
This paper introduces SVIS, a simulation tool that helps educators and policymakers design school schedules to minimize COVID-19 infection spread while maintaining face-to-face lessons.
Contribution
The paper presents SVIS, a novel simulation model that considers classroom and schedule variables to optimize school reopening strategies during COVID-19.
Findings
Increasing ventilation reduces infection spread but is less stable than schedule customization.
School schedule design significantly impacts maximum infection numbers.
Balancing face-to-face lessons and infection control is achievable with optimized schedules.
Abstract
During the Coronavirus 2019 (the covid-19) pandemic, schools continuously strive to provide consistent education to their students. Teachers and education policymakers are seeking ways to re-open schools, as it is necessary for community and economic development. However, in light of the pandemic, schools require customized schedules that can address the health concerns and safety of the students considering classroom sizes, air conditioning equipment, classroom systems, e.g., self-contained or compartmentalized. To solve this issue, we developed the School-Virus-Infection-Simulator (SVIS) for teachers and education policymakers. SVIS simulates the spread of infection at a school considering the students' lesson schedules, classroom volume, air circulation rates in classrooms, and infectability of the students. Thus, teachers and education policymakers can simulate how their school…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
