Proposed approaches for public health surveillance: A literature review for the Canadian National HIV Surveillance Program
Bibliographic record
Abstract
Background: The National HIV Surveillance Program, managed by the Public Health Agency of Canada, is a passive surveillance system that collects de-identified data on HIV cases in Canada. Regular review of this surveillance system is required to maintain its accuracy, effectiveness and relevance in the face of a changing HIV epidemic. The National HIV Surveillance Program is undergoing a comprehensive review and renewal process with the aim of identifying and implementing potential improvements to meet the information needs of communities, service providers, researchers, provinces and territories and the federal government more effectively. Methods: A non-systematic literature review was conducted in June to July 2023, with 3,521 articles found and 105 included. Objective: This literature review aimed to identify proposed approaches for public health surveillance, with an emphasis on HIV surveillance and identify key findings relating to the following themes: surveillance system infrastructure, data collection, ethical considerations and stakeholder relationships. Results: Key findings from the literature review pertained to standardization and centralization of data collection; collection of demographics, disease staging, social determinants of health and other data elements; and linking surveillance systems to other data sources or other surveillance systems. Additional findings concerned legislative and policy review, privacy strategies, informed consent, ethical surveillance system design, stakeholder consultation at all stages, knowledge translation and ensuring adequate resourcing. Conclusion: In future work, lessons resulting from the literature review will be combined with evidence from other components of the overall review of Canada's HIV surveillance system. Together, this information will be further assessed and prioritized for possible implementation after consultation with data providers and communities.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.056 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.040 | 0.056 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".