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Record W4379615702 · doi:10.1016/j.cell.2023.06.001

Dispersal patterns and influence of air travel during the global expansion of SARS-CoV-2 variants of concern

2023· article· en· W4379615702 on OpenAlexaff
Houriiyah Tegally, Eduan Wilkinson, Joseph L.-H. Tsui, Monika Moir, Darren Martin, Anderson F. Brito, Marta Giovanetti, Kamran Khan, Carmen Huber, Isaac I. Bogoch, James Emmanuel San, Jenicca Poongavanan, Joicymara S. Xavier, Darlan da S. Candido, Filipe Romero, Cheryl Baxter, Oliver G. Pybus, Richard Lessells, Nuno R. Faria, Moritz U.G. Kraemer, Túlio de Oliveira

Bibliographic record

VenueCell · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsBlueDot (Canada)University of Toronto
FundersH2020 Fast Track to InnovationNational Institute of Biomedical Imaging and BioengineeringFogarty International CenterNational Institutes of HealthOxford Martin School, University of OxfordFundação de Amparo à Pesquisa do Estado de São PauloNational Institute of Allergy and Infectious DiseasesHorizon 2020Medical Research CouncilSouth African Medical Research CouncilDepartment of Science and Innovation, South AfricaBill and Melinda Gates FoundationWorld Bank GroupWellcome TrustRockefeller FoundationBranco Weiss Fellowship – Society in Science
KeywordsBiological dispersalBiologyTransmissibility (structural dynamics)Air travelSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Phylogenetic treeCoronavirus disease 2019 (COVID-19)PhylogeographyEcologyEconomic geographyDemographyGeographyGeneticsPopulationInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The Alpha, Beta, and Gamma SARS-CoV-2 variants of concern (VOCs) co-circulated globally during 2020 and 2021, fueling waves of infections. They were displaced by Delta during a third wave worldwide in 2021, which, in turn, was displaced by Omicron in late 2021. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of VOCs worldwide. We find that source-sink dynamics varied substantially by VOC and identify countries that acted as global and regional hubs of dissemination. We demonstrate the declining role of presumed origin countries of VOCs in their global dispersal, estimating that India contributed <15% of Delta exports and South Africa <1%-2% of Omicron dispersal. We estimate that >80 countries had received introductions of Omicron within 100 days of its emergence, associated with accelerated passenger air travel and higher transmissibility. Our study highlights the rapid dispersal of highly transmissible variants, with implications for genomic surveillance along the hierarchical airline network.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.247

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 head0.041
GPT teacher head0.336
Teacher spread0.295 · 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 designBench or experimental
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

Citations71
Published2023
Admission routes1
Has abstractyes

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