ArticleJournal of building engineering2022
A practical approach for preventing dispersion of infection disease in naturally ventilated room.
Article in Journal of building engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Intelligent operation, maintenance, and control system for public building: Towards infection risk mitigation and energy efficiency.Sustainable cities and society · 2023Article
- The impact of retrofitted ventilation approaches on long-range airborne infection risk for lecture room environments: design stage methodology and application.Journal of building engineering · 2023Article
- Investigation on the cross-infection control performance of interactive cascade ventilation in multi-scenario of winter.Journal of building engineering · 2023Article
- Impact of ionizers on prevention of airborne infection in classroom.Building simulation · 2023Article
- Effects of Radiant Floor Heating Integrated with Natural Ventilation on Flow and Dispersion in a Newly Decorated Residence.International journal of environmental research and public health · 2022Article
- Ventilation strategies to reduce airborne transmission of viruses in classrooms: A systematic review of scientific literature.Building and environment · 2022Review
- Ventilation impacts on infection risk mitigation, improvement of environmental quality and energy efficiency for subway carriages.Building and environment · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the ongoing COVID-19 pandemic period, the airborne transmission of viruses has raised widespread concern as daily activities are resumed in public buildings. It is essential to develop mitigation strategies of infection disease transmission (e.g., increase of ventilation rate) in different scenarios to reduce the infection risk. For classrooms in schools, natural ventilation is generally used to provide outdoor air into rooms. However, the supply air volume depends strongly on the local conditions, e.g., window opening size and outdoor wind speed. In this study, the optimal design of classroom window openings is investigated, based on which low-cost window-integrated fans are then employed to enhance the efficiency of natural ventilation and infection disease control. Taking infected students as pollutant sources, numerical simulations are carried out to predict the pollutant concentration under various scenarios of pollutant sources and window opening modes (with/without fans), and to calculate the infection risk. It is found that by redesigning window openings, the airflow distribution performance index (ADPI) can be increased by 17% with corresponding infection likelihood decreased by 27%. The window-integrated fan has a significant effect on improving ventilation performance and prevention of infection disease transmission, leading to an ADPI of 99% and minimum infection probability of 11% for students sitting near the windows. This work can help to develop low-cost and effective mitigating measures of infection disease in classrooms by using hybrid ventilation systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.