Information from the abstract
The rapid spread of highly contagious respiratory diseases has overwhelmed hospital capacities worldwide, making home isolation a critical strategy for managing infected individuals. However, unprepared home isolation can increase the risk of infection among co-residents. This study aims to design an efficient home isolation room to mitigate these risks using Computational Fluid Dynamics (CFD) simulations. The Eulerian-Lagrangian method was employed to predict airflow and aerosol distribution from respiration, with validation through experimental aerosol measurements using an Optical Particle Counter (OPC) and SARS-CoV-2 surface contamination detection via RT-PCR. The simulation results closely matched experimental data, showing an inverse correlation between aerosol number concentrations and RT-PCR cycle threshold (Ct) values. Simulations of quarantine rooms revealed that turning on air conditioning increased turbulence and aerosol dispersion, while opening windows resulted in less turbulence but led to higher aerosol concentrations and greater dispersion beyond the quarantine room. In both 1-story and 2-story houses, airflow and aerosol dispersion patterns were similar, with open windows causing more aerosol spread into corridors compared to air conditioning. Installing an exhaust fan outside the quarantine room reduced aerosol concentrations in the corridor, with the optimal placement being on the wall adjacent to the door. Moreover, the exhaust fans installed inside the quarantine room significantly minimized aerosol escape, with placement above the exit door proving to be the most effective. Additionally, a ventilation rate of at least 10 ACH was determined to be optimal for reducing aerosol transmission beyond the quarantine room.
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This record has an Impact Signal of 72/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.
Related topics: Infection Control and Ventilation · Indoor Air Quality and Microbial Exposure · Wind and Air Flow Studies
Thai researcher and institutional participation
Nontakorn Udompol · Racha Dejchanchaiwong · Perapong Tekasakul · Thammasin Ingviya · Chanon Kongkamol · Parinya Khongprom · Prince of Songkla University
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