Programmatic Implications of Acute and Early HIV Infection
Bibliographic record
Abstract
Human immunodeficiency virus (HIV) infection includes acute, early, chronic, and late stages. Acute HIV infection lasts approximately 3 weeks and early HIV infection, which includes acute HIV infection, lasts approximately 7 weeks. Many testing and blood screening algorithms detect HIV antibodies about 3 weeks after HIV infection. Incidence estimates are based on results of modeling, cohort studies, surveillance, and/or assays. Viral load is the key modifiable risk factor for HIV transmission and peaks during acute and early HIV infection. Empirical evidence characterizing the impact of acute and early HIV infection on the spread of the HIV epidemic are limited. Time trends of HIV prevalence collected from concentrated and generalized epidemics suggest that acute and early HIV infection may have a limited role in population HIV transmission. Collectively, these data suggest that acute and early HIV infection is relatively short and does not currently require fundamentally different programmatic approaches to manage the HIV/AIDS epidemic in most settings. Research and surveillance will inform which epidemic contexts and phases may require tailored strategies for these stages of HIV infection.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".