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Record W2186426280 · doi:10.1155/2013/386018

Emergency Department Surveillance as a Proxy For The Prediction of Circulating Respiratory Viral Disease in Eastern Ontario

2013· article· en· W2186426280 on OpenAlexaffabout
Geoffrey Hall, Thomas Krahn, Anna Majury, Adam van Dijk, Gerald A. Evans, Kieran Moore, Allison Maier

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2013
Typearticle
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsEmergency departmentProxy (statistics)MedicineDiseaseRespiratory systemEmergency medicineInternal medicineIntensive care medicineComputer scienceMachine learning

Abstract

fetched live from OpenAlex

BACKGROUND: Seasonal outbreaks of winter respiratory viruses are responsible for increases in morbidity and mortality in the community. Previous studies have used hospitalizations, intensive care unit and emergency department (ED) visits as indicators of seasonal influenza incidence. OBJECTIVES: To evaluate whether ED visits can be used as a proxy to detect respiratory viral disease outbreaks, as measured by laboratory confirmation. METHODS: An Emergency Department Syndromic Surveillance system was used to collect ED chief complaints in Eastern Ontario from 2006 to 2010. Comparable laboratory-confirmed cases of respiratory viral infections were collected from the Public Health Ontario Laboratory in Kingston, Ontario. Correlations between ED visits and laboratory-confirmed cases were calculated. RESULTS: Laboratory-confirmed cases of selected respiratory viruses were significantly correlated with ED visits for respiratory and fever/influenza-like illness. In particular, respiratory syncytial virus (Spearman's rho = 0.593), rhinovirus (Spearman's rho = 0.280), influenza A (Spearman's rho = 0.528), influenza B (Spearman's rho = 0.426) and pH1N1 (Spearman's rho = 0.470) increased laboratory test levels were correlated with increased volume of ED visits across a number of age demographics. For the entire study population and all studied viruses, the Spearman's rho was 0.702, suggesting a strong correlation with ED visits. Laboratory-confirmed cases lagged in reporting by between one and two weeks for influenza A and pH1N1 compared with ED visit volume. CONCLUSION: These findings support the use of an Emergency Department Syndromic Surveillance system to track the incidence of respiratory viral disease in the community. These methods are efficient and can be performed using automated electronic data entry versus the inherent delays in the primary care sentinel surveillance system, and can aid the timely implementation of preventive and preparatory health 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 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)0.003
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 score0.091
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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

Citations20
Published2013
Admission routes2
Has abstractyes

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