Evidence map›Paper›PMID 39574922›Full record

ArticleAtmosphere2024

Resolving the Loss of Intermediate-Size Speech Aerosols in Funnel-Guided Particle Counting Measurement.

Tayeb Kakeshpour, Adriaan Bax

Abstract read
In one paragraph

Article in Atmosphere, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Tayeb KakeshpourLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
Adriaan BaxLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.

Funding

Observation and quantification of respiratory droplets by laser light scatteringZIADK075154 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI BAX, ADRIAAN · 2020 to 2025
$2.5M
Intramural NIH HHS ZIA DK075154
6 · The paper itself

Abstract

Modeling of airborne virus transmission and protection against it requires knowledge of the amount of biofluid emitted into the atmosphere and its viral load. Whereas viral concentrations in biofluids are readily measured by quantitative PCR, the total volume of fluids aerosolized during speaking, as measured by different researchers using different technologies, differs by several orders of magnitude. We compared collection methods in which the aerosols first enter into a low humidity chamber either by direct injection or via commonly used funnel and tubing arrangements, followed by standard optical particle sizer measurement. This "collect first, measure later" approach sacrifices recording of the temporal correlation between aerosol generation and sound types such as plosives and vowels. However, the direct-injection mode prevents inertia deposition associated with the funnel arrangements and reveals far more intermediate size (5-20 μm diameter) particles that can dominate the total mass of the ejected respiratory aerosol. The larger aerosol mass observed with our method partially reconciles the large discrepancy between the SARS-CoV-2 infectious dose estimated from superspreader event analyses and that from human challenge data. Our results also impact measures to combat airborne virus transmission because they indicate that aerosols that settle faster than good room ventilation rates can dominate this process.

Indexed as

airborne transmissioncoarse aerosolinertia depositioninfectious doserespiratory aerosolsuperspreader event

Identifiers

PMID39574922
PMCPMC11581197

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.