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基于真实的人类近距离接触行为分析大学教室内的 SARS-CoV-2 传播。

Analysis of SARS-CoV-2 transmission in a university classroom based on real human close contact behaviors.

机构信息

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

China Electric Power Planning & Engineering Institute, Beijing, China.

出版信息

Sci Total Environ. 2024 Mar 20;917:170346. doi: 10.1016/j.scitotenv.2024.170346. Epub 2024 Jan 27.

Abstract

Due to high-population density, frequent close contact, possible poor ventilation, university classrooms are vulnerable for transmission of respiratory infectious diseases. Close contact and long-range airborne are possibly main routes for SARS-CoV-2 transmission. In this study, taking a university classroom in Beijing for example, close contact behaviors of students were collected through a depth-detection device, which could detect depth to each pixel of the image, based on semi-supervised learning. Finally, >23 h of video data were obtained. Using Computational Fluid Dynamics, the relationship between viral exposure and close contact behaviors (e.g. interpersonal distance, relative facial orientations, and relative positions) was established. A multi-route transmission model (short-range airborne, mucous deposition, and long-range airborne) of infectious diseases considering real close contact behaviors was developed. In the case of Omicron, the risk of infection in university classrooms and the efficacy of different interventions were assessed based on dose-response model. The average interpersonal distance in university classrooms is 0.9 m (95 % CI, 0.5 m-1.4 m), with the highest proportion of face-to-back contact at 87.0 %. The risk of infection of susceptible students per 45-min lesson was 1 %. The relative contributions of short-range airborne and long-range airborne transmission were 40.5 % and 59.5 %, respectively, and the mucous deposition was basically negligible. When all students are wearing N95 respirators, the infection risk could be reduced by 96 %, the relative contribution of long-range airborne transmission increases to 95.6 %. When the fresh air per capita in the classroom is 24 m/h/person, the virus exposure could be decreased by 81.1 % compared to the real situation with 1.02 m/h/person. In a classroom with an occupancy rate of 50 %, after optimized arrangement of student distribution, the infection risk could be decreased by 62 %.

摘要

由于人口密度高、频繁的近距离接触以及可能通风不良,大学教室容易传播呼吸道传染病。密切接触和长程空气传播可能是 SARS-CoV-2 传播的主要途径。在这项研究中,以北京的一个大学教室为例,通过深度检测设备收集学生的密切接触行为,该设备可以基于半监督学习检测图像中每个像素的深度。最终,获得了超过 23 小时的视频数据。使用计算流体动力学,建立了病毒暴露与密切接触行为(例如人际距离、相对面部方向和相对位置)之间的关系。建立了一种考虑真实密切接触行为的传染病多途径传播模型(短程空气传播、黏液沉积和长程空气传播)。在 Omicron 情况下,基于剂量反应模型评估了大学教室中的感染风险和不同干预措施的效果。大学教室中的平均人际距离为 0.9 米(95%置信区间,0.5 米-1.4 米),面背面接触的比例最高,为 87.0%。易感学生每 45 分钟课程的感染风险为 1%。短程空气传播和长程空气传播的相对贡献分别为 40.5%和 59.5%,黏液沉积基本可以忽略不计。当所有学生都佩戴 N95 口罩时,感染风险可降低 96%,长程空气传播的相对贡献增加到 95.6%。当教室中的人均新风量为 24 立方米/小时/人时,与 1.02 立方米/小时/人相比,病毒暴露量可减少 81.1%。在一个占用率为 50%的教室中,通过优化学生分布的安排,感染风险可降低 62%。

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