RESUMO
Exploring the relative role of different indoor environments in respiratory infections transmission remains unclear, which is crucial for developing targeted nonpharmaceutical interventions. In this study, a total of 2,583,441 influenza-like illness cases tested from 2010 to 2017 in China were identified. An agent-based model was built and calibrated with the surveillance data, to assess the roles of 3 age groups (children <19 years, younger adults 19-60 years, older adults >60 years) and 4 types of indoor environments (home, schools, workplaces, and community areas) in influenza transmission by province with varying urbanization rates. When the urbanization rates increased from 35% to 90%, the proportion of children aged <19 years among influenza cases decreased from 76% to 45%. Additionally, we estimated that infections originating from children decreased from 95.1% (95% confidence interval (CI): 92.7, 97.5) to 59.3% (95% CI: 49.8, 68.7). Influenza transmission in schools decreased from 80.4% (95% CI: 76.5, 84.3) to 36.6% (95% CI: 20.6, 52.5), while transmission in the community increased from 2.4% (95% CI: 1.9, 2.8) to 45.4% (95% CI: 35.9, 54.8). With increasing urbanization rates, community areas and younger adults contributed more to infection transmission. These findings could help the development of targeted public health policies. This article is part of a Special Collection on Environmental Epidemiology. This article is part of a Special Collection on Environmental Epidemiology.
Assuntos
Influenza Humana , Infecções Respiratórias , Viroses , Criança , Humanos , Idoso , Influenza Humana/epidemiologia , Urbanização , China/epidemiologiaRESUMO
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 m3/h/person, the virus exposure could be decreased by 81.1 % compared to the real situation with 1.02 m3/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 %.
Assuntos
COVID-19 , Doenças Transmissíveis , Humanos , SARS-CoV-2 , Universidades , RespiraçãoRESUMO
Close contact routes, including short-range airborne and large-droplet routes, play an important role in the transmission of SARS-CoV-2 in indoor environments. However, the exposure risk of such routes is difficult to quantify due to the lack of data on the close contact behavior of individuals. In this study, a digital wearable device, based on semi-supervised learning, was developed to automatically record human close contact behavior. We collected 337,056 s of indoor close contact of school and university students from 194.5 h of depth video recordings in 10 types of indoor environments. The correlation between aerosol exposure and close contact behaviors was then evaluated. Individuals in restaurants had the highest close contact ratio (64%), as well as the highest probability of face-to-face pattern (78%) during close contact. Accordingly, university students showed greater exposure potential in dormitories than school students in homes, however, a lower exposure was observed in classrooms and postgraduate student offices in comparison with school students in classrooms. In addition, restaurants had the highest aerosol exposure volume for both short-range inhalation and direct deposition on the facial mucosa. Thus, the classroom was established as the primary indoor environment where school students are exposed to aerosols.