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Record W1987658481 · doi:10.2105/ajph.2012.300814

The Social Determinants of Health and Pandemic H1N1 2009 Influenza Severity

2012· article· en· W1987658481 on OpenAlex
Elizabeth C. Lowcock, Laura C. Rosella, Julie Foisy, Allison McGeer, Natasha S. Crowcroft

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Journal of Public Health · 2012
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsPublic Health Ontario
FundersUniversity of TorontoOntario Ministry of Health and Long-Term CarePublic Health Agency of CanadaUniversity Health Network
KeywordsPandemicMedicineLogistic regressionSocial determinants of healthDemographyEnvironmental healthH1N1 influenzaMultivariate analysisPublic healthCoronavirus disease 2019 (COVID-19)DiseaseInternal medicineInfectious disease (medical specialty)Nursing

Abstract

fetched live from OpenAlex

OBJECTIVES: We explored the effects of social determinants of health on pandemic H1N1 2009 influenza severity and the role of clinical risk factors in mediating such associations. METHODS: We used multivariate logistic regression with generalized estimating equations to examine the associations between individual- and ecological-level social determinants of health and hospitalization for pandemic H1N1 2009 illness in a case-control study in Ontario, Canada. RESULTS: During the first pandemic phase (April 23-July 20, 2009), hospitalization was associated with having a high school education or less and living in a neighborhood with high material or total deprivation. We also observed the association with education in the second phase (August 1-November 6, 2009). Clinical risk factors for severe pandemic H1N1 2009 illness mediated approximately 39% of the observed association. CONCLUSIONS: The main clinical risk factors for severe pandemic H1N1 2009 illness explain only a portion of the associations observed between social determinants of health and hospitalization, suggesting that the means by which the social determinants of health affect pandemic H1N1 2009 outcomes extend beyond clinically recognized risk factors.

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.

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)0.016
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation 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 score0.428
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.404
GPT teacher head0.518
Teacher spread0.113 · 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