Which community-based HIV initiatives are effective in achieving UNAIDS 90-90-90 targets? A systematic review and meta-analysis of evidence (2007-2018)
Notice bibliographique
Résumé
BACKGROUND: Reaching the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 targets to end the HIV epidemic relies on effective interventions that engage untested HIV+ individuals and retain them in care. Evidence on community-based interventions through the lens of the targets has not yet been synthesized, reflecting a knowledge gap. We conducted a systematic review and meta-analysis to shed light on successful community-based interventions that have been effective in contributing, directly or indirectly, towards the UNAIDS 90-90-90 targets: knowledge of HIV status, linkage to care/on treatment, and viral suppression. Linkage to care was also included in this review due to the limitations of studies. METHODS: We conducted a systematic review and meta-analysis of the period 2007-2018. Eleven databases were searched to identify community-based interventions designed to improve knowledge of HIV status (in particular HIV testing), linkage to care/on treatment, and/or viral suppression. Eligible studies were classified by intervention, population, country income level, outcomes and success. Success was defined as interventions demonstrating statistical significance between intervention and control group or that reached any target by proportion; 90% testing, 81% linked to care/on treatment and 73% viral suppression. RESULTS: Of 82 eligible studies, 51.2% (42/82) reported on HIV testing (first 90), 20.7% (17/82) on linkage to care/ on treatment (second 90), and 45.1% (37/82) on viral suppression (third 90). In all, 67.1% (55/82) of studies reported success; 21 studies on the first 90, 9 towards linkage to care/on treatment, and 25 towards the third. By strategies, 36.6% deployed community workers/peers, 22% used combined test and treat strategies, 12.2% used educational methods, 8.5% used mobile testing, 7.3% used campaigns and 13.4% used technology. For HIV testing/linkage, combined test/treat interventions were often used, for viral suppression, educational interventions and technologies were commonly deployed. Our pooled analysis suggested that deployment of community health care workers/peer workers significantly improved viral suppression (pooled OR: 1.40 95% CI 1.06-1.86). Of the studies published after 2014, 50.0% reported metrics aligned with UNAIDS targets. CONCLUSIONS: Data on linkage to care/on treatment (second target) remained weak, because many studies reported successes on the first and third targets. Stratification by targets and country income levels is informative and guides adaptation of successful interventions in comparable settings. Consistent reporting of clear metrics aligned with UNAIDS targets will aid in synergy of study data with programmatic data that will help reportage. Exploration of innovative interventions, for engagement and linkage and deployment of community/ peer workers is strongly encouraged.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,017 | 0,003 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».