Student close contact behavior and COVID-19 transmission in China's classrooms

Author:

Guo Yong12ORCID,Dou Zhiyang3ORCID,Zhang Nan4,Liu Xiyue4,Su Boni5,Li Yuguo6ORCID,Zhang Yinping12

Affiliation:

1. Department of Building Science, Tsinghua University , Beijing 100084 , China

2. Beijing Key Laboratory of Indoor Air Quality Evaluation and Control , Beijing 100084 , China

3. Department of Computer Science, The University of Hong Kong , Beijing 999077 , China

4. Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology , Beijing 100124 , China

5. Clean Energy Research Institute, China Electric Power Planning and Engineering Institute , Beijing 100120 , China

6. Department of Mechanical Engineering, The University of Hong Kong , Hong Kong SAR 999077 , China

Abstract

Abstract Classrooms are high-risk indoor environments, so analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in classrooms is important for determining optimal interventions. Due to the absence of human behavior data, it is challenging to accurately determine virus exposure in classrooms. A wearable device for close contact behavior detection was developed, and we recorded >250,000 data points of close contact behaviors of students from grades 1 to 12. Combined with a survey on students' behaviors, we analyzed virus transmission in classrooms. Close contact rates for students were 37 ± 11% during classes and 48 ± 13% during breaks. Students in lower grades had higher close contact rates and virus transmission potential. The long-range airborne transmission route is dominant, accounting for 90 ± 3.6% and 75 ± 7.7% with and without mask wearing, respectively. During breaks, the short-range airborne route became more important, contributing 48 ± 3.1% in grades 1 to 9 (without wearing masks). Ventilation alone cannot always meet the demands of COVID-19 control; 30 m3/h/person is suggested as the threshold outdoor air ventilation rate in a classroom. This study provides scientific support for COVID-19 prevention and control in classrooms, and our proposed human behavior detection and analysis methods offer a powerful tool to understand virus transmission characteristics and can be employed in various indoor environments.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

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