Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19
A new guideline for mitigating indoor airborne transmission of COVID-19 prescribes a limit on the time spent in a shared space with an infected individual (Bazant & Bush, Proceedings of the National Academy of Sciences of the United States of America, vol. 118, issue 17, 2021, e2018995118). He...
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Cambridge University Press (CUP)
2022
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| Online Access: | https://hdl.handle.net/1721.1/145627 |
| _version_ | 1826198197735784448 |
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| author | Bazant, Martin Z Kodio, Ousmane Cohen, Alexander E Khan, Kasim Gu, Zongyu Bush, John WM |
| author2 | Massachusetts Institute of Technology. Department of Mathematics |
| author_facet | Massachusetts Institute of Technology. Department of Mathematics Bazant, Martin Z Kodio, Ousmane Cohen, Alexander E Khan, Kasim Gu, Zongyu Bush, John WM |
| author_sort | Bazant, Martin Z |
| collection | MIT |
| description | A new guideline for mitigating indoor airborne transmission of COVID-19 prescribes a limit on the time spent in a
shared space with an infected individual (Bazant & Bush, Proceedings of the National Academy of Sciences of the
United States of America, vol. 118, issue 17, 2021, e2018995118). Here, we rephrase this safety guideline in terms of
occupancy time and mean exhaled carbon dioxide (CO2) concentration in an indoor space, thereby enabling the use
of CO2 monitors in the risk assessment of airborne transmission of respiratory diseases. While CO2 concentration is
related to airborne pathogen concentration (Rudnick & Milton, Indoor Air, vol. 13, issue 3, 2003, pp. 237–245), the
guideline developed here accounts for the different physical processes affecting their evolution, such as enhanced
pathogen production from vocal activity and pathogen removal via face-mask use, filtration, sedimentation and
deactivation. Critically, transmission risk depends on the total infectious dose, so necessarily depends on both the
pathogen concentration and exposure time. The transmission risk is also modulated by the fractions of susceptible,
infected and immune people within a population, which evolve as the pandemic runs its course. A mathematical
model is developed that enables a prediction of airborne transmission risk from real-time CO2 measurements.
Illustrative examples of implementing our guideline are presented using data from CO2 monitoring in university
classrooms and office spaces. |
| first_indexed | 2024-09-23T11:01:20Z |
| format | Article |
| id | mit-1721.1/145627 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:01:20Z |
| publishDate | 2022 |
| publisher | Cambridge University Press (CUP) |
| record_format | dspace |
| spelling | mit-1721.1/1456272022-10-04T03:32:14Z Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19 Bazant, Martin Z Kodio, Ousmane Cohen, Alexander E Khan, Kasim Gu, Zongyu Bush, John WM Massachusetts Institute of Technology. Department of Mathematics A new guideline for mitigating indoor airborne transmission of COVID-19 prescribes a limit on the time spent in a shared space with an infected individual (Bazant & Bush, Proceedings of the National Academy of Sciences of the United States of America, vol. 118, issue 17, 2021, e2018995118). Here, we rephrase this safety guideline in terms of occupancy time and mean exhaled carbon dioxide (CO2) concentration in an indoor space, thereby enabling the use of CO2 monitors in the risk assessment of airborne transmission of respiratory diseases. While CO2 concentration is related to airborne pathogen concentration (Rudnick & Milton, Indoor Air, vol. 13, issue 3, 2003, pp. 237–245), the guideline developed here accounts for the different physical processes affecting their evolution, such as enhanced pathogen production from vocal activity and pathogen removal via face-mask use, filtration, sedimentation and deactivation. Critically, transmission risk depends on the total infectious dose, so necessarily depends on both the pathogen concentration and exposure time. The transmission risk is also modulated by the fractions of susceptible, infected and immune people within a population, which evolve as the pandemic runs its course. A mathematical model is developed that enables a prediction of airborne transmission risk from real-time CO2 measurements. Illustrative examples of implementing our guideline are presented using data from CO2 monitoring in university classrooms and office spaces. 2022-09-30T16:39:23Z 2022-09-30T16:39:23Z 2021 2022-09-30T16:20:21Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/145627 Bazant, Martin Z, Kodio, Ousmane, Cohen, Alexander E, Khan, Kasim, Gu, Zongyu et al. 2021. "Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19." Flow, 1. en 10.1017/FLO.2021.10 Flow Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Cambridge University Press (CUP) Cambridge University Press |
| spellingShingle | Bazant, Martin Z Kodio, Ousmane Cohen, Alexander E Khan, Kasim Gu, Zongyu Bush, John WM Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19 |
| title | Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19 |
| title_full | Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19 |
| title_fullStr | Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19 |
| title_full_unstemmed | Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19 |
| title_short | Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19 |
| title_sort | monitoring carbon dioxide to quantify the risk of indoor airborne transmission of covid 19 |
| url | https://hdl.handle.net/1721.1/145627 |
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