The DOI matches its Crossref record; 115 of the 117 references it cites were found in a registry or an index.
Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors
Open accessAbstract
We provide research findings on the physics of aerosol and droplet dispersion relevant to the hypothesized aerosol transmission of SARS-CoV-2 during the current pandemic. We utilize physics-based modeling at different levels of complexity, along with previous literature on coronaviruses, to investigate the possibility of airborne transmission. The previous literature, our 0D-3D simulations by various physics-based models, and theoretical calculations, indicate that the typical size range of speech and cough originated droplets (d⩽20μm) allows lingering in the air for O(1h) so that they could be inhaled. Consistent with the previous literature, numerical evidence on the rapid drying process of even large droplets, up to sizes O(100μm), into droplet nuclei/aerosols is provided. Based on the literature and the public media sources, we provide evidence that the individuals, who have been tested positive on COVID-19, could have been exposed to aerosols/droplet nuclei by inhaling them in significant numbers e.g. O(100). By 3D scale-resolving computational fluid dynamics (CFD) simulations, we give various examples on the transport and dilution of aerosols (d⩽20μm) over distances O(10m) in generic environments. We study susceptible and infected individuals in generic public places by Monte-Carlo modelling. The developed model takes into account the locally varying aerosol concentration levels which the susceptible accumulate via inhalation. The introduced concept, ’exposure time’ to virus containing aerosols is proposed to complement the traditional ’safety distance’ thinking. We show that the exposure time to inhale O(100) aerosols could range from O(1s) to O(1min) or even to O(1h) depending on the situation. The Monte-Carlo simulations, along with the theory, provide clear quantitative insight to the exposure time in different public indoor environments.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1
van Doremalen, N., Bushmaker, T., Morris, D. H., Holbrook, M. G., Gamble, A., Williamson, B. N., Tamin, A., Harcourt, J. L., Thornburg, N. J., Gerber, S. I., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2004973 · Cited by 9,951
Social force model for pedestrian dynamics.
Helbing, D., & Molnár, P. (1995) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.51.4282 · Cited by 7,299
Virological assessment of hospitalized patients with COVID-2019
Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., Niemeyer, D., Jones, T. C., Vollmar, P., Rothe, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2196-x · Cited by 6,661
Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus
Li, W., Moore, M. J., Vasilieva, N., Sui, J., Wong, S. K., Berne, M. A., Somasundaran, M., Sullivan, J. L., Luzuriaga, K., Greenough, T. C., et al. (2003) · Nature · doi:10.1038/nature02145 · Cited by 5,923
A tensorial approach to computational continuum mechanics using object-oriented techniques
Weller, H. G., Tabor, G., Jasak, H., & Fureby, C. (1998) · Computers in Physics · doi:10.1063/1.168744 · Cited by 5,406
SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients
Zou, L., Ruan, F., Huang, M.-X., Liang, L.-J., Huang, H., Hong, Z.-S., Yu, J.-X., Kang, M., Song, Y.-C., Xia, J., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2001737 · Cited by 4,590
Agent-based modeling: Methods and techniques for simulating human systems
Bonabeau, E. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082080899 · Cited by 4,500
Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany
Rothe, C., Schunk, M., Sothmann, P., Bretzel, G., Froeschl, G., Wallrauch, C., Zimmer, T., Thiel, V., Jänke, C., Guggemos, W., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2001468 · Cited by 4,211
Research works printed but not linked: 2
- Macher, J., 1999. Bioaerosols: Assessment and Control. ACGIH (American Conference of Governmental Industrial Hygienists).
- Seymour, M.J., Alani, A., Manning, A., Jiang, J., 2000. Airflow modelling to investigate the effectiveness of control methods intended to prevent the transmission of airborne organisms. In: Awbi, H.B. (Ed.), Air Distribution in Rooms, (ROOMVENT 2000), pp. 77–82.
Cited by
Sorted by citations
Airborne transmission of respiratory viruses
Wang, C. C., Prather, K. A., Sznitman, J., Jimenez, J. L., Lakdawala, S. S., Tüfekçi, Z., & Marr, L. C. (2021) · Science · doi:10.1126/science.abd9149 · Cited by 1,631
An evidence review of face masks against COVID-19
Howard, J., Huang, A., Li, Z., Tüfekçi, Z., Ždímal, V., van der Westhuizen, H., von Delft, A., Price, A. I., Fridman, L., Tang, L., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2014564118 · Cited by 1,577
Gkiotsalitis, K., & Cats, O. (2020) · Transport Reviews · doi:10.1080/01441647.2020.1857886 · Cited by 520
Airborne environmental DNA for terrestrial vertebrate community monitoring
Lynggaard, C., Bertelsen, M. F., Jensen, C. V., Johnson, M. S., Frøslev, T. G., Olsen, M. T., & Bohmann, K. (2022) · Current Biology · doi:10.1016/j.cub.2021.12.014 · Cited by 258
Numerical investigation of aerosol transport in a classroom with relevance to COVID-19
Abuhegazy, M., Talaat, K., Anderoglu, O., & Poroseva, S. (2020) · Physics of Fluids · doi:10.1063/5.0029118 · Cited by 248
Metadata
- Authors
- Vuorinen, V., Aarnio, M., Alava, M., Alopaeus, V., Atanasova, N., Auvinen, M., Balasubramanian, N., Bordbar, H., Erästö, P., Grande, R., Hayward, N., Hellsten, A., Hostikka, S., Hokkanen, J., Kaario, O., Karvinen, A., Kivistö, I., Korhonen, M., Kosonen, R., Kuusela, J., Lestinen, S., Laurila, E., Nieminen, H. J., Peltonen, P., Pokki, J., Puisto, A., Råback, P., Salmenjoki, H., Sironen, T., & Österberg, M.
- Affiliations
- Aalto University (FI)
- Finnish Meteorological Institute (FI)
- CSC - IT Center for Science (Finland) (FI)
- VTT Technical Research Centre of Finland (FI)
- Mikkelin keskussairaala (FI)
- University of Helsinki (FI)
- Corresponding author
- Vuorinen, Ville
- ORCID
- Vuorinen, Ville
- Alava, Mikko
- Alopaeus, Ville
- Atanasova, Nina
- Auvinen, Mikko
- Bordbar, Hadi
- Erästö, Panu
- Grande, Rafael
- Hayward, Nick
- Hellsten, Antti
- Hostikka, Simo
- Kaario, Ossi
- Kivistö, Ilkka
- Korhonen, Marko
- Kosonen, Risto
- Lestinen, Sami
- Laurila, Erkki
- Nieminen, Heikki J.
- Peltonen, Petteri
- Pokki, Juho
- Puisto, Antti
- Råback, Peter
- Salmenjoki, Henri
- Sironen, Tarja
- Österberg, Monika
- Venue
- Safety Science
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 130
- Pages
- 104866
- ISSN
- 0925-7535 (ISSN-L)
- PMC
- PMC7428778
- OpenAlex
- W3029277938
- Cited by
- 472
- References
- 117
- Citations by year
- 2026: 19 · 2025: 39 · 2024: 53 · 2023: 72 · 2022: 100 · 2021: 152 · 2020: 36
- FWCI
- 50.95
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Safety Science (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Aaltodoc (Aalto University) (submittedVersion, cc-by)
- Työväentutkimus Vuosikirja (submittedVersion)
- arXiv (Cornell University) (cc-by)
- Funders
- Academy of Finland (314487, 309570)
- Scientific Advisory Board for Defense (VN/627/2020-PLM-9)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Infection Control and Ventilation
- Health Sciences › Dentistry › General Dentistry › Dental Research and COVID-19
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- SARS-CoV-2, airborne transmission, aerosol transport, droplet dispersion, droplet nuclei, droplet drying, indoor transmission, exposure time, aerosol dilution, computational fluid dynamics, Monte Carlo simulation, COVID-19 pandemic, safety distance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
