MétaCan
Menu
Back to cohort
Record W4210862572 · doi:10.1038/s41598-022-06159-x

Understanding the dynamics of SARS-CoV-2 variants of concern in Ontario, Canada: a modeling study

2022· article· en· W4210862572 on OpenAlexafffundabout
Anita T. Layton, Mehrshad Sadria

Bibliographic record

VenueScientific Reports · 2022
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSars virusBetacoronavirusDynamics (music)VirologyCoronavirus InfectionsPandemicComputational biologyData scienceMedicineBiologyBioinformaticsComputer scienceOutbreakPsychologyInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

A year after the initial wild-type Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains began their devastation of the world, they were supplanted by new variants of concern (VOC). In Ontario, Canada, the wild type was overtaken first by the Alpha/B1.1.17 variant, and then by the Delta/B.1.617 variant. The principal objective of the present study is to develop and apply a much expanded Susceptible-Infection-Recovered-type model to better understand the spread of multiple VOC, and assess the effectiveness of vaccination and non-pharmaceutical interventions (NPI). The model represents competition among VOC, and reveals their mutual inhibitory effects. By separately tracking asymptomatic and symptomatic infections, model simulations identify a significant role of vaccine breakthrough in the spread of Delta. Furthermore, the severity of a Delta outbreak depends not only on the NPI and vaccination rate but also on the vaccine types. Alarmingly, despite Ontario's existing NPI and relatively successful vaccine rollout, a future, more dangerous VOC could potentially infect a significant fraction of the province's population and overwhelm the health care system. To stop that VOC, the province may need the simultaneous and rapid deployment of a third booster vaccine and stringent NPI.

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)0.006
metaresearch head score (Gemma)0.002
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 score0.819
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
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 science0.0000.001
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 head0.494
GPT teacher head0.399
Teacher spread0.094 · 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

Citations36
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueScientific ReportsSame topicCOVID-19 epidemiological studiesFrench-language works237,207