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Record W2055886136 · doi:10.1016/j.ijid.2010.02.571

Redevelopment and evaluation of EpiData: A practical software tool for use in the public health field

2010· article· en· W2055886136 on OpenAlexaffabout
Anne Arthur, Javier Sádaba Garay, B. Guarda, Lee E. Sieswerda, Adam Stevens

Bibliographic record

VenueInternational Journal of Infectious Diseases · 2010
Typearticle
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsThunder Bay Regional Health Sciences CentrePublic Health Agency of CanadaToronto Public Health
Fundersnot available
KeywordsPublic healthAgency (philosophy)MedicinePublic health informaticsMedical educationInternational healthHealth policyNursing

Abstract

fetched live from OpenAlex

Background: EpiData Entry and EpiData Analysis are key tools for case and outbreak data management, both in Canada and internationally. Based on field input and pilot testing, the full scope of EpiData capability has yet to be realized. This project focuses on the development and evaluation of standardized tools used for epidemiological training and field management of outbreaks on an national and international scale. Methods: With funding received by the Public Health Agency of Canada (PHAC), the EpiData Association in Denmark and the Association of Public Health Epidemiologists in Ontario (APHEO) have been collaborating since 2007 on the redevelopment and evaluation of EpiData software applications. EpiData is a free software suite designed to assist epidemiologists, public health investigators and other public health professionals in entering, managing, and analyzing data in the field. The software was created in 1999 and is maintained by the EpiData Association in Denmark. It is also used as a training tool internationally, including the Public Health Agency of Canada's (PHAC) Canadian Field Epidemiology Program. Through in-person meetings, targeted surveys, and solicited feedback from key public health partners, gaps in knowledge and awareness regarding the functionality and use of EpiData have been assessed, and used to define the knowledge products for development. Results: To date, software development has focused on functionality applicable to a range of public health tasks, including the investigation and management of infectious disease outbreaks. Knowledge translation of these advances has been conducted through development of field guides and hands-on workshops. The next phase of the project will focus on developing tools for the use of EpiData in areas outside of communicable disease investigations, including surveys, program evaluation, and management of chronic disease data. Conclusion: This poster provides an overview of the Evaluation and Redevelopment EpiData project, and outlines the initiatives currently underway. Abstracts for SupplementInternational Journal of Infectious DiseasesVol. 14Preview Full-Text PDF Open Archive

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)0.002
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.015
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 head0.060
GPT teacher head0.401
Teacher spread0.341 · 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.

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

Citations2
Published2010
Admission routes2
Has abstractyes

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