The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Cough aerosol in healthy participants: fundamental knowledge to optimize droplet-spread infectious respiratory disease management
Open accessAbstract
BACKGROUND: The Influenza A H1N1 virus can be transmitted via direct, indirect, and airborne route to non-infected subjects when an infected patient coughs, which expels a number of different sized droplets to the surrounding environment as an aerosol. The objective of the current study was to characterize the human cough aerosol pattern with the aim of developing a standard human cough bioaerosol model for Influenza Pandemic control. METHOD: 45 healthy non-smokers participated in the open bench study by giving their best effort cough. A laser diffraction system was used to obtain accurate, time-dependent, quantitative measurements of the size and number of droplets expelled by the cough aerosol. RESULTS: Voluntary coughs generated droplets ranging from 0.1 - 900 microns in size. Droplets of less than one-micron size represent 97% of the total number of measured droplets contained in the cough aerosol. Age, sex, weight, height and corporal mass have no statistically significant effect on the aerosol composition in terms of size and number of droplets. CONCLUSIONS: We have developed a standard human cough aerosol model. We have quantitatively characterized the pattern, size, and number of droplets present in the most important mode of person-to-person transmission of IRD: the cough bioaerosol. Small size droplets (< 1 μm) predominated the total number of droplets expelled when coughing. The cough aerosol is the single source of direct, indirect and/or airborne transmission of respiratory infections like the Influenza A H1N1 virus. STUDY DESIGN: Open bench, Observational, Cough, Aerosol study.
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
Review of Aerosol Transmission of Influenza A virus
Tellier, R. (2006) · Emerging Infectious Diseases · doi:10.3201/eid1211.060426 · Cited by 803
The size distribution of droplets in the exhaled breath of healthy human subjects
PAPINENI, R. S., & ROSENTHAL, F. S. (1997) · Journal of Aerosol Medicine · doi:10.1089/jam.1997.10.105 · Cited by 690
Inhaling to mitigate exhaled bioaerosols
Edwards, D. A., Man, J. C., Brand, P., Katstra, J. P., Sommerer, K., Stone, H. A., Nardell, E., & Scheuch, G. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0408159101 · Cited by 362
Cited by
Airborne transmission of respiratory viruses
Wang, C. C., Prather, K. A., Sznitman, J., Jimenez, J. L., Lakdawala, S. S., Tufekci, Z., & Marr, L. C. (2021) · Science · doi:10.1126/science.abd9149 · Cited by 1,543
Aerosol Emission and Superemission during Human Speech Increase with Voice Loudness
Asadi, S., Wexler, A. S., Cappa, C. D., Barreda, S., Bouvier, N. M., & Ristenpart, W. D. (2019) · Scientific Reports · doi:10.1038/s41598-019-38808-z · Cited by 919
Violent expiratory events: on coughing and sneezing
Bourouiba, L., Dehandschoewercker, E., & Bush, J. W. M. (2014) · Journal of Fluid Mechanics · doi:10.1017/jfm.2014.88 · Cited by 828
The fluid dynamics of disease transmission
Bourouiba, L. (2021) · Annual Review of Fluid Mechanics · doi:10.1146/annurev-fluid-060220-113712 · Cited by 366
Visualization of sneeze ejecta: steps of fluid fragmentation leading to respiratory droplets
Scharfman, B. E., Techet, A. H., Bush, J. W. M., & Bourouiba, L. (2016) · Experiments in Fluids · doi:10.1007/s00348-015-2078-4 · Cited by 287
Metadata
- Authors
- Zayas, G., Chiang, M. C., Wong, E., MacDonald, F., Lange, C. F., Senthilselvan, A., & King, M.
- Venue
- BMC Pulmonary Medicine
- Published
- 2012-03-21
- Volume
- 12
- Issue
- 1
- Pages
- 11-11
- ISSN
- 1471-2466 (ISSN-L)
- OpenAlex
- W2064935442
- Cited by
- 227
- References
- 3
- FWCI
- 2.85
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Cough aerosol in healthy participants: fundamental knowledge to optimize droplet-spread infectious respiratory disease management. https://app.cochat.ai/papers/10.1186/1471-2466-12-11
- The paper
- Zayas, G., Chiang, M. C., Wong, E., MacDonald, F., Lange, C. F., Senthilselvan, A., & King, M. (2012). Cough aerosol in healthy participants: fundamental knowledge to optimize droplet-spread infectious respiratory disease management. BMC Pulmonary Medicine. https://doi.org/10.1186/1471-2466-12-11
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.