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Low but highly variable mortality among nurses and physicians during the influenza pandemic of 1918-1919

2011· article· en· W1551536499 on OpenAlexaboutno aff
G. Dennis Shanks, Alison MacKenzie, Michael Waller, John F. Brundage

Bibliographic record

VenueInfluenza and Other Respiratory Viruses · 2011
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicInfluenza pandemicMedicineFamily medicineMortality rateDemographyEmergency medicineCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: During the 1918-1919 influenza pandemic, nurses and physicians were intensively exposed to the pandemic A/H1N1 strain. There are few published summaries of the mortality experiences of nurses and physicians during the pandemic. METHODS: Mortality records from U.S. and British Armies during the First World War and obituary notices in national medical association journals were reviewed to ascertain death notices of nurses and physicians likely to have died of influenza. RESULTS: Illness-related mortality among U.S. military nurses (1·05%) was one and one-half times higher than among U.S. medical officers (0·68%), nearly two times higher than among British medical officers (0·55%), and nine times higher than among British nurses (0·12%). Among U.S. nursing officers, mortality was approximately twice as high among those assigned in the United States than in Europe. Among civilian physicians, mortality during the influenza pandemic was markedly increased in Canada, New Zealand, South Africa and the United States but not Australia. CONCLUSIONS: During the 1918 pandemic, mortality among nurses and physicians was relatively low compared to their patients and significantly varied across locations and settings. Medical-care providers (particularly U.S. nursing officers) who were new to their assignments when pandemic-related epidemics occurred may have had higher risk of influenza-related mortality because of occupational exposures to bacterial respiratory pathogens that they had not previously encountered.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.034
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.083
GPT teacher head0.331
Teacher spread0.248 · 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

Citations26
Published2011
Admission routes1
Has abstractyes

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