HIV Partner Notification Is Effective and Feasible in Sub-Saharan Africa: Opportunities for HIV Treatment and Prevention
Bibliographic record
Abstract
BACKGROUND: Sexual partners of persons with newly diagnosed HIV infection require HIV counseling, testing and, if necessary, evaluation for therapy. However, many African countries do not have a standardized protocol for partner notification, and the effectiveness of partner notification has not been evaluated in developing countries . METHODS: Individuals with newly diagnosed HIV infection presenting to sexually transmitted infection clinics in Lilongwe, Malawi, were randomized to 1 of 3 methods of partner notification: passive referral, contract referral, or provider referral. The passive referral group was responsible for notifying their partners themselves. The contract referral group was given seven days to notify their partners, after which a health care provider contacted partners who had not reported for counseling and testing. In the provider referral group, a health care provider notified partners directly. RESULTS: Two hundred forty-five index patients named 302 sexual partners and provided locator information for 252. Among locatable partners, 107 returned for HIV counseling and testing; 20 of 82 [24%; 95% confidence interval (CI): 15% to 34%] partners returned in the passive referral arm, 45 of 88 (51%; 95% CI: 41% to 62%) in the contract referral arm, and 42 of 82 (51%; 95% CI: 40% to 62%) in the provider referral arm (P < 0.001). Among returning partners (n = 107), 67 (64%) of were HIV infected with 54 (81%) newly diagnosed. DISCUSSION: This study provides the first evidence of the effectiveness of partner notification in sub-Saharan Africa. Active partner notification was feasible, acceptable, and effective among sexually transmitted infections clinic patients. Partner notification will increase early referral to care and facilitate risk reduction among high-risk uninfected partners.
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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 | 0.004 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".