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Record W4384926396 · doi:10.1126/science.adg6605

Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1

2023· article· en· W4384926396 on OpenAlexaff
Joseph L.-H. Tsui, John T. McCrone, Ben Lambert, Sumali Bajaj, Rhys Inward, Paolo Bosetti, Rosario Evans Pena, Houriiyah Tegally, Verity Hill, Alexander E. Zarebski, Thomas P. Peacock, Luyang Liu, Neo Wu, Megan Davis, Isaac I. Bogoch, Kamran Khan, Meaghan Kall, Nurin Abdul Aziz, Rachel Colquhoun, Áine O’Toole, Ben Jackson, Abhishek Dasgupta, Eduan Wilkinson, Túlio de Oliveira, Thomas R. Connor, Nicholas J. Loman, Vittoria Colizza, Christophe Fraser, Erik Volz, Xiang Ji, Bernardo Gutiérrez, Meera Chand, Simon Dellicour, Simon Cauchemez, Jayna Raghwani, Marc A. Suchard, Philippe Lemey, Andrew Rambaut, Oliver G. Pybus, Moritz U. G. Kraemer

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of TorontoBlueDot (Canada)
FundersDirectorate for Biological SciencesNational Institutes of HealthUniversity College London Hospitals NHS Foundation TrustUniversity of BrightonEuropean CommissionNatural Environment Research CouncilVlaamse regeringUniversity of OxfordBiotechnology and Biological Sciences Research CouncilWellcome TrustUniversity of SouthamptonUniversity College LondonKing's College LondonUniversity of St AndrewsUniversity of ExeterFonds De La Recherche Scientifique - FNRSUniversity of East AngliaRoyal Marsden NHS Foundation TrustRockefeller FoundationMedical Research CouncilDepartment of Health and Social CareNational Institute of Allergy and Infectious DiseasesAgence Nationale de la RechercheUniversity Hospital Southampton NHS Foundation TrustKing's College Hospital NHS Foundation TrustUK Research and InnovationFogarty International CenterFonds Wetenschappelijk OnderzoekNvidiaAdvanced Micro DevicesNational Institute for Health and Care ResearchBill and Melinda Gates Foundation
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Sars virusCoronavirus disease 2019 (COVID-19)Dynamics (music)Biology2019-20 coronavirus outbreakGeneticsVirologyComputational biologyMedicinePhysicsPathologyDiseaseOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) now arise in the context of heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron BA.1 genomes, we identified >6,000 introductions of the antigenically distinct VOC into England and analyzed their local transmission and dispersal history. We find that six of the eight largest English Omicron lineages were already transmitting when Omicron was first reported in southern Africa (22 November 2021). Multiple datasets show that importation of Omicron continued despite subsequent restrictions on travel from southern Africa as a result of export from well-connected secondary locations. Initiation and dispersal of Omicron transmission lineages in England was a two-stage process that can be explained by models of the country's human geography and hierarchical travel network. Our results enable a comparison of the processes that drive the invasion of Omicron and other VOCs across multiple spatial scales.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.414
Teacher spread0.333 · 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 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

Citations69
Published2023
Admission routes1
Has abstractyes

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