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Record W2071166771 · doi:10.1097/inf.0b013e318199cefd

Seasonality of Respiratory Viral Identification Varies With Age and Aboriginality in Metropolitan Western Australia

2009· article· en· W2071166771 on OpenAlexaff
Hannah C. Moore, Nicholas de Klerk, Peter Richmond, Anthony D. Keil, Katie Lindsay, Aileen J. Plant, Deborah Lehmann

Bibliographic record

VenueThe Pediatric Infectious Disease Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsVirusVirologyMedicineSeasonalityRespiratory systemRespiratory tract infectionsImmunologySeasonal influenzaViral diseaseBiologyCoronavirus disease 2019 (COVID-19)Internal medicineDiseaseEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Viral respiratory infections are a major cause of pediatric illness. It is not known whether seasonality of viruses differs between Aboriginal and non-Aboriginal children of varying ages. METHODS: We extracted data on respiratory syncytial virus (RSV), influenza viruses A and B, parainfluenza virus types 1, 2, and 3 and adenovirus identified through cell culture or direct immunofluorescence between 1997 and 2005 from nasopharyngeal or throat specimens at Western Australia's only pediatric hospital. We used harmonic analysis in generalized linear models to examine the variations in seasonality of these viruses with Aboriginality and age. RESULTS: A respiratory virus was identified in 32% of 32 741 specimens. RSV (18.6%), influenza virus A (5.1%), and parainfluenza virus 3 (4.0%) were most common. The median age at time of identification was lower in Aboriginal children than non-Aboriginal for all viruses except RSV. Seasonality differed between all viruses and varied with age for RSV, influenza viruses and adenovirus. Influenza viruses A and B activity peaked earlier in Aboriginal than non-Aboriginal children during 1997, 1998, and 2002. CONCLUSIONS: All viruses showed distinct seasonality. Variability with age and different seasonal patterns for influenza viruses in Aboriginal children compared with non-Aboriginal children has to be taken into account when identifying target groups and timing for vaccination and other interventions.

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)0.001
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 score0.003
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.368
Teacher spread0.331 · 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

Citations23
Published2009
Admission routes1
Has abstractyes

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