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Record W4288034315 · doi:10.1126/science.abp8715

The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic

2022· article· en· W4288034315 on OpenAlexafffund
Michael Worobey, Joshua I. Levy, Lorena M. Malpica Serrano, Alexander Crits‐Christoph, Jonathan E. Pekar, Stephen A. Goldstein, Angela L. Rasmussen, Moritz U. G. Kraemer, Chris Newman, Marion Koopmans, Marc A. Suchard, Joel O. Wertheim, Philippe Lemey, David L. Robertson, Robert F. Garry, Edward C. Holmes, Andrew Rambaut, Kristian G. Andersen

Bibliographic record

VenueScience · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of Saskatchewan
FundersEuropean and Developing Countries Clinical Trials PartnershipNational Cancer InstituteNational Center for Advancing Translational SciencesWellcome TrustNational Human Genome Research InstituteNational Institute of Allergy and Infectious DiseasesMedical Research CouncilCenters for Disease Control and PreventionEuropean CommissionCanadian Institutes of Health ResearchU.S. National Library of MedicineU.S. Department of Veterans AffairsInnovation SaskatchewanGilead SciencesNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsCoronavirus disease 2019 (COVID-19)PandemicEpicenter2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)BusinessOutbreakVirologyBiologyMedicineEngineeringInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 is critical to preventing future zoonotic outbreaks before they become the next pandemic. The Huanan Seafood Wholesale Market in Wuhan, China, was identified as a likely source of cases in early reports, but later this conclusion became controversial. We show here that the earliest known COVID-19 cases from December 2019, including those without reported direct links, were geographically centered on this market. We report that live SARS-CoV-2-susceptible mammals were sold at the market in late 2019 and that within the market, SARS-CoV-2-positive environmental samples were spatially associated with vendors selling live mammals. Although there is insufficient evidence to define upstream events, and exact circumstances remain obscure, our analyses indicate that the emergence of SARS-CoV-2 occurred through the live wildlife trade in China and show that the Huanan market was the epicenter of the COVID-19 pandemic.

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 score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.064
GPT teacher head0.280
Teacher spread0.217 · 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

Citations432
Published2022
Admission routes2
Has abstractyes

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