School Virus Infection Simulator for customizing school schedules during COVID-19

Satoshi Takahashi; Masaki Kitazawa; Atsushi Yoshikawa

doi:10.1016/j.imu.2022.101084

School Virus Infection Simulator for customizing school schedules during COVID-19

Inform Med Unlocked. 2022:33:101084. doi: 10.1016/j.imu.2022.101084. Epub 2022 Sep 13.

Authors

Satoshi Takahashi¹, Masaki Kitazawa^{2

3}, Atsushi Yoshikawa^{3

4}

Affiliations

¹ College of Science and Engineering, Kanto Gakuin University, 1-50-1 Mutsuura, Kanazawa-ku, Yokohama-shi, Kanagawa, Yokohama, 236-8501, Japan.
² Kitazawa Tech, Fujisawa, Japan.
³ Graduate School of Artificial Intelligence and Science, Rikkyo University, Tokyo, Japan.
⁴ School of Computing, Tokyo Institute of Technology, Yokohama, Japan.

Abstract

Even as the COVID-19 pandemic raged worldwide, schools strived to provide consistent education to their students. In such situations, schools require customized schedules that can address the health concerns and safety of the students to safely reopen and remain open. School schedules can be customized in many ways, and different approaches' impact on education and effectiveness in reducing infectious risks are different. To address this issue, we developed the School Virus Infection Simulation-Model (SVISM) for teachers and education policymakers. By taking into account the students' lesson schedules, classroom volume, air circulation rates in the classrooms, and infectability of the students, SVISM simulates the spread of infection at a school. We demonstrate the impact of several school schedules in self-contained and departmentalized classrooms and evaluate them in terms of the maximum number of students infected simultaneously, and the percentage of face-to-face lessons. The results show that the impact of increasing the classroom ventilation rate is not as stable as that of customizing school schedules. In addition, school schedules can differently impact the maximum number of students infected simultaneously, depending on whether classrooms are self-contained or departmentalized. We found that the maximum number of students infected simultaneously under a certain schedule with 50 percentage of face-to-face lessons in self-contained classrooms is higher than the maximum number of students infected simultaneously having schedules with a higher percentage of face-to-face lessons; this phenomenon was not found in departmentalized classrooms. These results show that the SVISM can help teachers and education policymakers plan school schedules appropriately to reduce the maximum number of students infected simultaneously, while also maintaining a certain rate of face-to-face lessons.

Keywords: COVID-19; Departmentalized classroom; Hybrid learning; School scheduling; Self-contained classroom; Virus infection.