Re‐assessing the late <scp>HIV</scp> diagnosis surveillance definition in the era of increased and frequent testing
Bibliographic record
Abstract
OBJECTIVES: ) is a key public health metric. In an era of more frequent testing, the likelihood of HIV diagnosis occurring during seroconversion, when CD4 counts may dip below 350, is greater. We applied a correction, considering markers of recent infection, and re-assessed 1-year mortality following late diagnosis. METHODS: We used national epidemiological and laboratory surveillance data from all people diagnosed with HIV in England, Wales, and Northern Ireland (EW&NI). Those with a baseline CD4 <350 were reclassified as 'not late' if they had evidence of recent infection (recency test and/or negative test within 24 months). A correction factor (CF) was the number reclassified divided by the number with a CD4 <350. RESULTS: Of the 32 227 people diagnosed with HIV in EW&NI between 2011 and 2019 with a baseline CD4 (81% of total), 46% had a CD4 <350 (uncorrected late diagnosis rate): 34% of gay and bisexual men (GBM), 65% of heterosexual men, and 56% of heterosexual women. Accounting for recency test and/or prior negative tests gave a 'corrected' late diagnosis rate of 39% and corresponding CF of 14%. The CF increased from 10% to 18% during 2011-2015, then plateaued, and was larger among GBM (25%) than heterosexual men and women (6% and 7%, respectively). One-year mortality among people diagnosed late was 329 per 10 000 after reclassification (an increase from 288/10 000). CONCLUSIONS: The case-surveillance definition of late diagnosis increasingly overestimates late presentation, the extent of which differs by key populations. Adjustment of late diagnosis is recommended, particularly for frequent testers such as GBM.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".