Modeling the effect of temperature and relative humidity on exposure to SARS‐CoV ‐2 in a mechanically ventilated room
Article Swipe
Timothy Foat
,
Benjamín Higgins
,
Charlotte Abbs
,
Tom Maishman
,
Simon Coldrick
,
Adrian Kelsey
,
M.J. Ivings
,
Simon T. Parker
,
Catherine J. Noakes
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1111/ina.13146
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1111/ina.13146
Computational fluid dynamics models have been developed to predict airborne exposure to the SARS-CoV-2 virus from a coughing person in a mechanically ventilated room. The models were run with three typical indoor air temperatures and relative humidities (RH). Quantile regression was used to indicate whether these have a statistically significant effect on the airborne exposure. Results suggest that evaporation is an important effect. Evaporation leads to respiratory particles, particularly those with initial diameters between 20 and 100 μm, remaining airborne for longer, traveling extended distances and carrying more viruses than expected from their final diameter. In a mechanically ventilated room, with all of the associated complex air movement and turbulence, increasing the RH may result in reduced airborne exposure. However, this effect may be so small that other factors, such as a small change in proximity to the infected person, could rapidly counter the effect. The effect of temperature on the exposure was more complex, with both positive and negative correlations. Therefore, within the range of conditions studied here, there is no clear guidance on how the temperature should be controlled to reduce exposure. The results highlight the importance of ventilation, face coverings and maintaining social distancing for reducing exposure.
Related Topics
Concepts
Relative humidity
Environmental science
Evaporation
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Atmospheric sciences
Humidity
Ventilation (architecture)
Coronavirus disease 2019 (COVID-19)
Range (aeronautics)
Air movement
Respirator
Turbulence
Meteorology
Chemistry
Materials science
Physics
Medicine
Composite material
Pathology
Infectious disease (medical specialty)
Organic chemistry
Disease
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/ina.13146
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ina.13146
- OA Status
- hybrid
- Cited By
- 12
- References
- 39
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4310249072
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4310249072Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1111/ina.13146Digital Object Identifier
- Title
-
Modeling the effect of temperature and relative humidity on exposure to
SARS‐CoV ‐2 in a mechanically ventilated roomWork title - Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-01Full publication date if available
- Authors
-
Timothy Foat, Benjamín Higgins, Charlotte Abbs, Tom Maishman, Simon Coldrick, Adrian Kelsey, M.J. Ivings, Simon T. Parker, Catherine J. NoakesList of authors in order
- Landing page
-
https://doi.org/10.1111/ina.13146Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ina.13146Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ina.13146Direct OA link when available
- Concepts
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Relative humidity, Environmental science, Evaporation, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Atmospheric sciences, Humidity, Ventilation (architecture), Coronavirus disease 2019 (COVID-19), Range (aeronautics), Air movement, Respirator, Turbulence, Meteorology, Chemistry, Materials science, Physics, Medicine, Composite material, Pathology, Infectious disease (medical specialty), Organic chemistry, DiseaseTop concepts (fields/topics) attached by OpenAlex
- Cited by
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12Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2024: 4, 2023: 4, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
39Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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