Improving national surveillance of new HIV diagnoses
Bibliographic record
Abstract
The purpose of national HIV surveillance is to track and summarize trends in newly diagnosed cases as an indicator of HIV transmission within Canada, and supports the development and evaluation of programs and policies for prevention, testing and delivery of care. Accurately capturing and interpreting trends in HIV diagnoses within national surveillance becomes complicated when there is movement of people within a country or when individuals are diagnosed with HIV prior to migrating to a new country. This has been identified as an issue in other countries, including Australia, New Zealand and Switzerland. The Public Health Agency of Canada (PHAC) recently assessed this in Canada after noting a rise in new HIV cases in Canada between 2014 to 2017. An environmental scan was conducted to better understand how new and previously diagnosed cases of HIV were recorded by and reported to PHAC from provincial and territorial (PT) public health authorities. It was discovered there was variation with respect to the reporting of cases who had received a new diagnosis of HIV within the province or territory, but who had previously received an HIV diagnosis from another PT or another country. Five PTs included cases previously diagnosed in another Canadian PT within the HIV surveillance data reported to PHAC and nine PTs included people who were diagnosed with HIV outside of Canada. The provincial and territorial public health authorities then reviewed HIV surveillance data from 2007 to 2017 to identify cases using a common definition of "previous HIV-positive test result". This included any case who gave a history, or had laboratory evidence, of an HIV-positive result from another PT or another country before presenting for care in the province or territory where they now resided. When these cases were subtracted from the total, a revised number of new HIV diagnoses was calculated for Canada. Re-analysis of surveillance data using this common definition for 2007 to 2017 explained more than half of the increase in HIV cases that had been documented in Canada over the last four years. In the future, national surveillance data will be calculated adopting this new common definition of a previous positive test result, in order to more accurately describe the trends in HIV transmission occurring in Canada.
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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 | 0.018 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".