DOI QR코드

DOI QR Code

Analysis of Infection Control Effectiveness Based on Policies in Indoor Spaces of Educational Facilities

교육시설 내 실내 공간의 정책에 따른 감염관리 효과 분석

  • Received : 2023.12.06
  • Accepted : 2024.04.18
  • Published : 2024.05.30

Abstract

To address COVID-19 concerns, governments have implemented Non-Pharmacological Interventions (NPIs) and treatment-focused policies, particularly in densely populated areas like schools. These measures, including partial closures and time restrictions, raise concerns about socioeconomic impacts. This investigation aims to identify infection factors in academic settings, develop a pedestrian traffic simulation model, establish risk thresholds for disease spread, and conduct policy experiments and impact analyses. Various intervention methods were assessed, such as classroom zoning and movement restrictions, finding that spatial compartmentalization alone is ineffective. However, limiting free movement reduces contact time and infection risk. Nonetheless, intervention effectiveness varies based on student population and density, highlighting the need for further research to recommend optimal strategies based on school size and enrollment. This study aims to support schools and institutions in improving infection control policies and offer practical guidance for decision-making in this area.

Keywords

Acknowledgement

이 연구는 2024년도 과학기술정보통신부의 재원으로 한국연구재단 연구비 지원에 의한 결과의 일부임. 과제번호 2022R1A2C200299913

References

  1. Alam, M. J., Habib, M. A., & Holmes, D. (2022). Pedestrian movement simulation for an airport considering social distancing strategy. Transportation Research Interdisciplinary Perspectives, 13, 100527. Elsevier. 
  2. Cuevas, E. (2020). An agent-based model to evaluate the COVID-19 transmission risks in facilities. Computers in Biology and Medicine, 121, 103827. Elsevier. 
  3. Engzell, P., Frey, A., & Verhagen, M. D. (2021). Learning loss due to school closures during the COVID-19 pandemic. Proceedings of the National Academy of Sciences, 118(17). 
  4. Falk, G. (2020). Unemployment Rates During the COVID-19 Pandemic. Congressional Research Service. 
  5. Haug, N., Geyrhofer, L., Londei, A., Dervic, E., Desvars-Larrive, A., Loreto, V., & Klimek, P. (2020). Ranking the effectiveness of worldwide COVID-19 government interventions. Nature human behaviour, 4(12), 1303-1312.  https://doi.org/10.1038/s41562-020-01009-0
  6. Li, C. Y., & J. Yin. (2021). A pedestrian-based model for simulating COVID-19 transmission on college campus. Transportmetrica A: Transport Science, 1-25. Taylor & Francis. 
  7. Lipton, A., & de Prado, M. L. (2022). Mitigation strategies for covid-19: Lessons from the K-SEIR Model calibrated to the observable data. Journal of Risk and Financial Management, 15(6), 248. 
  8. Loades, M. E., Chatburn, E., Higson-Sweeney, N., Reynolds, S., Shafran, R., Brigden, A., & Crawley, E. (2020). Rapid systematic review: the impact of social isolation and loneliness on the mental health of children and adolescents in the context of COVID-19. Journal of the American Academy of Child & Adolescent Psychiatry, 59(11), 1218-1239.  https://doi.org/10.1016/j.jaac.2020.05.009
  9. Meyer, B. H., Prescott, B., & Sheng, X. S. (2022). The impact of the COVID-19 pandemic on business expectations. International Journal of Forecasting, 38(2), 529-544.  https://doi.org/10.1016/j.ijforecast.2021.02.009
  10. Panneer, S., Kantamaneni, K., Akkayasamy, V. S., Susairaj, A. X., Panda, P. K., Acharya, S. S., & Pushparaj, R. R. B. (2022). The great lockdown in the wake of COVID-19 and its implications: lessons for low and middle-income countries. International journal of environmental research and public health, 19(1), 610. 
  11. Sparnaaij, M., Y. Yuan, W. Daamen., & D. C. Duives. (2022). A novel activity choice and scheduling model to model activity schedules of customers and staff in Dutch restaurants. arXiv preprint arXiv:2204.06775. 
  12. Wang, J., Tang, H., Wang, J., & Zhong, Z. (2022). An agent-based study on the airborne transmission risk of infectious disease in a fever clinic during COVID-19 pandemic. Building and Environment, 218, 109118. 
  13. Woodhouse, M. J., Aspinall, W. P., & Sparks, S. R. (2021). Analysis of alternative Covid-19 mitigation measures in school classrooms: an agent-based model of SARS-CoV-2 transmission. medRxiv.
  14. Zafarnejad, R., & Griffin, P. M. (2021). Assessing school-based policy actions for COVID-19: An agent-based analysis of incremental infection risk. Computers in Biology and Medicine, 134, 104518.