HIV self-testing in Ottawa, Canada used by persons at risk for HIV: The GetaKit study
Bibliographic record
Abstract
BACKGROUND: The Public Health Agency of Canada estimates that about 87% of persons living with human immunodeficiency virus (HIV) in Canada have been diagnosed, which is well below the Joint United Nations Programme on HIV/AIDS target to have 95% of HIV-positive persons diagnosed. Research has shown that HIV self-testing may help increase such diagnoses, especially among the populations who are most affected by HIV. The objective of the study was to determine the uptake and diagnosis outcomes associated with free HIV self-testing. METHODS: We developed the first online mailout free HIV self-testing program in Canada and implemented it in Ottawa. This project ran through the website, www.GetaKit.ca. We intended to recruit 150-400 participants over a 6-12-month period, estimating that this number would yield between 0-1 positive test results (expected positivity rate of 0.08%). RESULTS: Between July 20, 2020 and April 1, 2021, 1,268 people accessed the GetaKit website and verified their eligibility. In total, 600 persons were eligible and 405 ordered an HIV kit. Of those who ordered a kit, 399 completed a baseline survey. Overall, 71% of these participants were members of HIV priority groups. For test results, 228 persons reported test results, with one being positive, for a positivity rate of 0.24% overall and 0.44% of reported results. These rates exceed that normally observed in Ottawa. CONCLUSION: Self-testing of HIV can be effectively delivered through a website. Such an intervention will also be used by persons with undiagnosed infections and appears to do so at a rate higher than that observed by other means of testing. Self-testing of HIV may therefore help Canada achieve the United Nations 95-95-95 targets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".