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Record W3167220201 · doi:10.1101/2021.06.03.21258274

Transmission of SARS-CoV-2 associated with aircraft travel: a systematic review (Version 1)

2021· review· en· W3167220201 on OpenAlexaff
Elena Cecilia Roşca, Carl Heneghan, Elizabeth Spencer, Jon Brassey, Annette Plüddemann, Igho Onakpoya, David H. Evans, JM Conly, Tom Jefferson

Bibliographic record

VenuemedRxiv · 2021
Typereview
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsAlberta Health ServicesUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsTransmission (telecommunications)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Airborne transmissionCrewAir travelCoronavirus disease 2019 (COVID-19)Sars virusPandemicMedicineVirologyAviationAeronauticsComputer scienceTelecommunicationsEngineeringDiseasePathology

Abstract

fetched live from OpenAlex

Abstract Background Air travel may be associated with the spread of viruses via infected passengers and potentially through in-flight transmission. Given the novelty of the SARS-CoV-2 virus, transmission associated with air travel is based on what is known about the dynamics of transmission of other respiratory virus infections, especially those due to other coronaviruses and influenza. Our objective was to provide a rapid summary and evaluation of relevant data on the transmission of SARS-CoV-2 aboard aircraft, report important policy implications, and highlight research gaps requiring urgent attention. Methods This review is part of an Open Evidence Review on Transmission Dynamics of SARS-CoV-2. We searched LitCovid, medRxiv, Google Scholar, and the WHO Covid-19 database from 1 February 2020 to 27 January 2021 and included studies on the transmission of SARS-CoV-2 aboard aircraft. We assessed study quality based on five criteria and reported important findings. Results We included 18 studies on in-flight transmission of SARS-CoV-2, representing 130 unique flights and two studies on wastewater from aircraft. The overall quality of reporting was low. Two wastewater studies reported PCR-positive SARS-CoV-2 samples, but with relatively high Cycle threshold values ranging from 36 to 40. The definition of an index case was very heterogeneous across the studies. The proportion of contacts traced ranged from 0.68% to 100%. In total, the authors successfully traced 2800/19729 passengers, 140/180 crew members, and 8/8 medical staff. Altogether, 273 index cases were reported, with 64 secondary cases. No secondary cases were reported in three studies, each investigating one flight. The secondary attack rate among the studies that followed up >80% of the passengers and crew (including data on 10 flights) varied between 0% and 8.2%. The included studies reported on the possibility of SARS-CoV-2 transmission from asymptomatic, pre-symptomatic, and symptomatic individuals. Viral cultures were performed in two studies, with 10 positive results reported. Genomic sequencing and phylogenetic analysis were performed in individuals from four flights, with the completeness of genomic similarity ranging from 81-100%. Conclusion Current evidence suggests that SARS-CoV-2 can be transmitted during aircraft travel, but the published data do not permit any conclusive assessment of the likelihood and extent. Furthermore, the quality of evidence from most published studies is low. The variation in study design and methodology restricts the comparison of findings across studies. Standardized guidelines for conducting and reporting future studies of transmission on aircrafts should be developed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.076
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0120.016
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.296
GPT teacher head0.442
Teacher spread0.146 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations2
Published2021
Admission routes1
Has abstractyes

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