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Population-based epidemiology of invasive pneumococcal infection in children in nine urban centers in Canada, 1994 through 1998

2002· article· en· W2331459211 on OpenAlexaffabout
Gordean Bjornson, David W. Scheifele, Scott A. Halperin

Bibliographic record

VenueThe Pediatric Infectious Disease Journal · 2002
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsImpactUniversity of British ColumbiaDalhousie University
Fundersnot available
KeywordsEpidemiologyMedicineBacteremiaIncidence (geometry)PopulationPediatricsPneumoniaMeningitisVaccinationPneumococcal infectionsDemographyStreptococcus pneumoniaeImmunologyEnvironmental healthInternal medicineBiology

Abstract

fetched live from OpenAlex

PURPOSE: To describe the epidemiology of invasive pneumococcal infections in Canadian children 0 to 12 years old. METHODS: At each of nine urban centers, active surveillance was conducted to identify all cases of invasive pneumococcal infection in children during 1994 to 1998. Postal codes were used to distinguish cases resident in defined urban areas from referral cases. Census data were obtained for each defined area to calculate age-specific incidence rates. Features of population-based cases were described. RESULTS: From an average defined population of approximately 1 million children, 937 eligible cases arose. Those 6 to 17 months old had the highest average incidence rate of 98.6/100 000/year. The average cumulative risk of infection was 1 in 460 between birth and 59 months, by which age 92% of cases had occurred. Among cases younger than 2 years of age, simple bacteremia accounted for 66%, pneumonia with bacteremia accounted for 14.7% and meningitis accounted for 11% (average incidence rate, 9.0/100 000/year). An underlying illness was present in 16% of all cases. The mortality rate was 1.8%. CONCLUSIONS: Invasive pneumococcal infections are relatively common in early childhood, based on 5 years of data from nearly 20% of the Canadian population ages 0 to 12 years. These data will be valuable for calculating the economic case for universal infant vaccination with newly available vaccines.

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)0.001
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 score0.023
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.250
Teacher spread0.234 · 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

Citations20
Published2002
Admission routes2
Has abstractyes

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