Predicting the infection probability distribution due to airborne and droplet transmission
17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2327188
ABSTRACT
In this study, a method was proposed to predict the infection probability distribution rather than the room-averaged value. The infection probability by airborne transmission was predicted based on the CO2 concentration. The infection probability by droplet transmission was predicted based on occupant position information. Applying the proposed method to an actual office confirmed that it could be used for quantitatively predicting the infection probability by integrating the ventilation efficiency and distance between occupants. The infection probability by airborne transmission was relatively high in a zone where the amount of outdoor air supply was relatively small. The infection probability by droplet transmission varied with the position of the occupants. The ability of the proposed method to analyze the relative effectiveness of countermeasures for airborne transmission and droplet transmission was verified in this study. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
CO2 concentration; COVID-19; social distancing; ventilation; Wells-Riley model; Air quality; Carbon dioxide; Drops; Forecasting; Indoor air pollution; Probability distributions; Transmissions; Air supply; Airborne transmission; Effectiveness of countermeasures; Outdoor air; Position information; Probability: distributions; Ventilation efficiency; Well-riley model
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Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022
Year:
2022
Document Type:
Article
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