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Record W2587516628 · doi:10.1097/phh.0000000000000517

An Evaluation of Provincial Infectious Disease Surveillance Reports in Ontario

2017· article· en· W2587516628 on OpenAlexaffabout
Ellen Chan, Morgan Barnes, Omar Sharif

Bibliographic record

VenueJournal of Public Health Management and Practice · 2017
Typearticle
Languageen
FieldMedicine
TopicData-Driven Disease Surveillance
Canadian institutionsPublic Health Ontario
Fundersnot available
KeywordsInfectious disease (medical specialty)Environmental healthDisease surveillanceData scienceMedicineDiseaseComputer sciencePathology

Abstract

fetched live from OpenAlex

CONTEXT: Public Health Ontario (PHO) publishes various infectious disease surveillance reports, but none have yet been formally evaluated. OBJECTIVE: PHO evaluated its monthly and annual infectious disease surveillance reports to assess public health stakeholders' current perception of the products and to develop recommendations for improving future products. DESIGN: An evaluation consisting of an online survey and a review of public Web sites of other jurisdictions with similar annual reports. SETTING: For the online survey, stakeholder organizations targeted were the 36 local public health units and the Health health ministry in Ontario, Canada. PARTICIPANTS: Survey participants included epidemiologists, managers, directors, and other public health practitioners from participating organizations. MAIN OUTCOME MEASURES: Online survey respondents' awareness and access to the reports, their rated usefulness of reports and subsections, and suggestions for improving usefulness; timeliness of select annual reports from other jurisdictions based on the period from data described to report publication. RESULTS: Among 57 survey respondents, between 74% and 97% rated each report as useful; the most common use was for situational awareness. Respondents ranked timeliness as the most important attribute of surveillance reports, followed by data completeness. Among 6 annual reports reviewed, the median time to publication was 11.5 months compared with 23.2 months for PHO. CONCLUSION: Recommendations based on this evaluation have already been applied to the monthly report (eg, focusing on the most useful sections) and have become key considerations when developing future annual reports and other surveillance reporting tools (eg, need to provide more timely reports). Other public health organizations may also use this evaluation to inform aspects of their surveillance report development and evaluation. The evaluation results have provided PHO with direction on how to improve its provincial infectious disease surveillance reporting moving forward, and formed a basis for future work in surveillance product development and evaluation.

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)0.020
metaresearch head score (Gemma)0.006
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 score0.103
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.103
GPT teacher head0.412
Teacher spread0.308 · 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

Citations2
Published2017
Admission routes2
Has abstractyes

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