MétaCan
Menu
Back to cohort
Record W4413299194 · doi:10.1038/s44298-025-00143-8

Survival and transmission fitness of SARS-CoV-2 over the time-of-flight in an aerosolization chamber

2025· article· en· W4413299194 on OpenAlexafffund
Yiying Zhang, Justin M. Donovan, Dylan W. Weninger, Victor L. Lam, Richard M. Gibson, Daniel Paquette, Alex Lescanec, Christopher T. DeGroot, Jessica L. Prodger, Franco Berruti, Eric Savory, Eric J. Arts

Bibliographic record

Venuenpj Viruses · 2025
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsCenterLine (Canada)Western University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsRoche Canada
KeywordsAerosolizationTransmission (telecommunications)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)BiologyVirusReplicateVirologyMedicineInfectious disease (medical specialty)Inhalation

Abstract

fetched live from OpenAlex

The impact of various environmental factors on SARS-CoV-2 transmission remains debated, partly due to limited physical experiments with infectious virus that closely replicate real-world conditions. Using a novel, self-contained containment level 3 chamber, we aerosolized the virus in different environmental conditions then collected droplets on nasal tissue, cell lines, or different materials to measure the transmission of infectious SARS-CoV-2. We found that SARS-CoV-2 survival was much shorter than previously reported for the potential of fomite transmission. Temperature, relative humidity and the presence of incinerated tobacco, cannabis, or vape products had no discernible impact on SARS-CoV-2 transmission through aerosolized droplets, but affected the survival of VSV, a non-respiratory enveloped virus. When compared to USA-WA1/2020 and the Omicron variant, Delta SARS-CoV-2 had the greatest survival during aerosolization. These findings suggest that respiratory enveloped viruses like SARS-CoV-2 may have and may be continuing to evolve higher transmission fitness through droplets.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.144

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.336
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuenpj VirusesSame topicInfection Control and VentilationFrench-language works237,207