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Record W2892362768 · doi:10.14745/ccdr.v44i05a01

Fifteen years post-SARS: Key milestones in Canada's public health emergency response

2018· article· en· W2892362768 on OpenAlexaffvenueabout
Theresa Tam

Bibliographic record

VenueCanada Communicable Disease Report · 2018
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsPublic healthPandemicPublic relationsAgency (philosophy)Health carePolitical scienceMedicineInfectious disease (medical specialty)DiseaseCoronavirus disease 2019 (COVID-19)NursingSociology

Abstract

fetched live from OpenAlex

This year marks the 15th anniversary of Severe Acute Respiratory Syndrome (SARS) in Canada and the 100th anniversary of the 1918 Spanish influenza pandemic. These, and other recent public health events, provide an opportunity for us to review and reflect on the evolution of Canada's public health emergency response over the past 15 years-from SARS, to the 2009 H1N1 pandemic influenza, to Ebola virus and Zika virus disease. Key lessons have been learned and milestones achieved that have shaped and sharpened our response approach and structures. While SARS was a wake-up-call to strengthen infection prevention and control capacity in health care settings and led to the formation of the Public Health Agency of Canada, it also strengthened our Federal/Provincial/Territorial (FPT) senior-level governance and led to agreements for pan-Canadian mutual aid and infectious disease information sharing. As well, our collective public health laboratory capacity has been strengthened through ongoing response and sharing of advanced diagnostics and research. As we move forward, it will be important to explore the design of scalable or modular emergency response strategies and structures that are socio-culturally appropriate and employ evidence-based strategic risk communications that continue to be critical, especially given the volume and spread of misinformation. With the current global reality, we must recognize that public health threats that go unchecked anywhere in the world have the potential to very rapidly become a public health threat in Canada. We need to build, maintain and share our best public health practices globally, for we neglect these at our peril.

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 score0.090
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.047
GPT teacher head0.333
Teacher spread0.286 · 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

Citations32
Published2018
Admission routes3
Has abstractyes

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