High Rates of Forward Transmission Events after Acute/Early HIV‐1 Infection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it