High Rates of Forward Transmission Events after Acute/Early HIV‐1 Infection
Bibliographic record
Abstract
BACKGROUND: A population-based phylogenetic approach was used to characterize human immunodeficiency virus (HIV)-transmission dynamics in Quebec. METHODS: HIV-1 pol sequences included primary HIV infections (PHIs; <6 months after seroconversion) from the Quebec PHI cohort (1998-2005; n=215) and the provincial genotyping program (2001-2005; n=481). Phylogenetic analysis determined sequence interrelationships among unique PHIs (n=593) and infections from untreated (n=135) and treated (n=660) chronically infected (CI) potential transmitter populations (2001-2005). Clinical features, risk factors, and drug resistance for clustered and nonclustered transmission events were ascertained. RESULTS: Viruses from 49.4% (293/593) of PHIs cosegregated into 75 transmission chains with 2-17 transmissions/cluster. Half of the clusters included 2.7+/-0.8 (mean+/-SD) transmissions, whereas the remainder had 8.8+/-3.5 transmissions. Maximum periods for onward transmission in clusters were 15.2+/-9.5 months. Coclustering of untreated and treated CIs with PHIs were infrequent (6.2% and 4.8%, respectively). The ages, viremia, and risk factors were similar for clustered and nonclustered transmission events. Low prevalence of drug resistance in PHI supported amplified transmissions at early stages. CONCLUSIONS: Early infection accounts for approximately half of onward transmissions in this urban North American study. Therapy at early stages of disease may prevent onward HIV transmission.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".