Predicting the infection probability distribution due to airborne and droplet transmission

Miguel Yamamoto; Akihiro Kawamura; Hisashi Hasebe; Nobuhiro Miura; Takashi Kurihara; Kengo Tomita; Keichi Suzuki; Shin Ichi Tanabe; Satoshi Hori

Predicting the infection probability distribution due to airborne and droplet transmission

Miguel Yamamoto^*, Akihiro Kawamura, Hisashi Hasebe, Nobuhiro Miura, Takashi Kurihara, Kengo Tomita, Keichi Suzuki, Shin Ichi Tanabe, Satoshi Hori

^*Corresponding author for this work

School of Creative Science and Engineering

Research output: Contribution to conference › Paper › peer-review

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.

Original language	English
Publication status	Published - 2022
Event	17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022 - Kuopio, Finland Duration: 2022 Jun 12 → 2022 Jun 16

Conference

Conference	17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022
Country/Territory	Finland
City	Kuopio
Period	22/6/12 → 22/6/16

Keywords

CO2 concentration
COVID-19
Wells-Riley model
social distancing
ventilation

ASJC Scopus subject areas

Pollution

Cite this

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title = "Predicting the infection probability distribution due to airborne and droplet transmission",

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.",

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note = "Publisher Copyright: {\textcopyright} 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.; 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022 ; Conference date: 12-06-2022 Through 16-06-2022",

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language = "English",

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TY - CONF

T1 - Predicting the infection probability distribution due to airborne and droplet transmission

AU - Yamamoto, Miguel

AU - Kawamura, Akihiro

AU - Hasebe, Hisashi

AU - Miura, Nobuhiro

AU - Kurihara, Takashi

AU - Tomita, Kengo

AU - Suzuki, Keichi

AU - Tanabe, Shin Ichi

AU - Hori, Satoshi

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - CO2 concentration

KW - COVID-19

KW - Wells-Riley model

KW - social distancing

KW - ventilation

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M3 - Paper

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T2 - 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022

Y2 - 12 June 2022 through 16 June 2022

ER -

Predicting the infection probability distribution due to airborne and droplet transmission

Abstract

Conference

Keywords

ASJC Scopus subject areas

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