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Record W4394688408 · doi:10.1038/s41467-024-47118-6

The genomic evolutionary dynamics and global circulation patterns of respiratory syncytial virus

2024· article· en· W4394688408 on OpenAlexaff
Annefleur C. Langedijk, Bram Vrancken, Robert Jan Lebbink, Deidre Wilkins, Elizabeth J. Kelly, Eugenio Baraldi, Abiel Homero Mascareñas de los Santos, Daria Danilenko, Eun Hwa Choi, María Angélica Palomino, Hsin Chi, Christian Keller, Robert Cohen, Jesse Papenburg, Jeffrey M. Pernica, Anne Greenough, Peter Richmond, Federico Martinón‐Torres, Terho Heikkinen, Renato T. Stein, Mitsuaki Hosoya, Marta C. Nunes, Charl Verwey, Anouk Evers, Leyla Kragten‐Tabatabaie, Marc A. Suchard, Sergei L. Kosakovsky Pond, Chiara Poletto, Vittoria Colizza, Philippe Lemey, Louis Bont

Bibliographic record

VenueNature Communications · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsMcMaster UniversityMcGill University Health Centre
FundersAstraZeneca
KeywordsPandemicBiologyViral phylodynamicsEvolutionary biologyPhylogeographyGenomeEvolutionary dynamicsVirusPhylogeneticsPhylogenetic treeGenomicsVirologyComputational biologyGeneticsCoronavirus disease 2019 (COVID-19)GeneMedicineEnvironmental healthDiseasePopulation

Abstract

fetched live from OpenAlex

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection in young children and the second leading cause of infant death worldwide. While global circulation has been extensively studied for respiratory viruses such as seasonal influenza, and more recently also in great detail for SARS-CoV-2, a lack of global multi-annual sampling of complete RSV genomes limits our understanding of RSV molecular epidemiology. Here, we capitalise on the genomic surveillance by the INFORM-RSV study and apply phylodynamic approaches to uncover how selection and neutral epidemiological processes shape RSV diversity. Using complete viral genome sequences, we show similar patterns of site-specific diversifying selection among RSVA and RSVB and recover the imprint of non-neutral epidemic processes on their genealogies. Using a phylogeographic approach, we provide evidence for air travel governing the global patterns of RSVA and RSVB spread, which results in a considerable degree of phylogenetic mixing across countries. Our findings highlight the potential of systematic global RSV genomic surveillance for transforming our understanding of global RSV spread.

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)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.384
Teacher spread0.348 · 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

Citations28
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicRespiratory viral infections researchFrench-language works237,207