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Record W2241211806 · doi:10.1155/2000/134624

Establishing Priorities for National Communicable Disease Surveillance

2000· article· en· W2241211806 on OpenAlexaffabout

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2000
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsHealth Canada
Fundersnot available
KeywordsCommunicable diseasePublic healthDisease surveillanceEnvironmental healthMedicineGovernment (linguistics)OutbreakNotifiable diseaseInfectious disease (medical specialty)DiseasePopulationVirology

Abstract

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The federal government has collected information on communicable diseases since 1924, under the legislative authority of the Statistics Canada Act and the Health Canada Act (1,2). Aggregate data on communicable diseases was initially collected and collated by The Dominion Bureau of Statistics (later changed to Statistics Canada), but this responsibility, with the exception of tuberculosis, was transferred to the Laboratory Centre for Disease Control (LCDC) in 1988. Responsibility for tuberculosis was subsequently transferred to the LCDC in 1995. Currently, information on communicable diseases under national surveillance is managed by the Division of Disease Surveillance within the Bureau of Infectious Diseases, LCDC. The delivery of health care and public health services is identified in the Canadian Constitution as a provincial power. The federal government has powers over the provision of safe food and the importation of communicable diseases, and has the power to assist in a crisis such as an infectious disease outbreak. Although communicable disease surveillance is carried out under provincial authority, coordination and monitoring occur at the federal level. Provincial and federal health authorities reach agreement on communicable disease surveillance by means of a joint committee called the Advisory Committee on Epidemiology (ACE) and its subcommittee on communicable diseases. The Division of Disease Surveillance is frequently asked why all infectious diseases of general interest are not nationally notifiable. First, disease surveillance requires money, time and energy for health care providers, local health units, provinces, territories or Health Canada to report and collect data on every communicable disease. Second, it requires considerable time and effort to make a disease nationally notifiable because every province and territory needs to go through the legislative or regulatory process of making the disease reportable within their jurisdictions. The process is managed by setting priorities to decide where to put the greatest effort. Criteria for priority setting should be explicit and measurable, and should minimize the influence of such factors as personal interest and political agendas. To the utmost degree possible, the criteria should be based on scientific evidence. Above all, “the challenge is to make the priority-setting process transparent and open to criticism and revision” (3). Before 1987, there was no mechanism in place to evaluate newly emerging diseases and compare them with the diseases that were being reported. Accordingly, in 1987, ACE established a subcommittee on communicable diseases to develop a systematic process to determine which communicable diseases should be monitored at the national level. The subcommittee asked which diseases should be routinely monitored, how should they be monitored and whether they should be monitored at all. These are important questions that have led to a priority setting exercise with the following objectives: to ensure national surveillance of major infectious diseases that threaten the health of Canadians; to support the development and evaluation of programs that are currently in place and those which have been proposed; to ensure the participation of Canada in the global surveillance of specific health threats; and to determine the best use of human and financial resources in the prevention and control of communicable diseases. The priority setting process involves several steps: establishing the criteria; subdividing each criterion into levels; assigning points to each level within each criterion; summing the points and assigning a total score to each disease; ranking the diseases from highest to lowest score; and determining a cut-off point that would allow the inclusion and exclusion of

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)0.134
metaresearch head score (Gemma)0.106
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.708

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1340.106
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0140.007
Science and technology studies0.0080.004
Scholarly communication0.0180.013
Open science0.0090.018
Research integrity0.0070.014
Insufficient payload (model declined to judge)0.0100.004

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 head0.022
GPT teacher head0.370
Teacher spread0.347 · 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 designNot applicable
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

Citations62
Published2000
Admission routes2
Has abstractyes

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