P5-S6.28 HIV prevention based on the static modes of transmission synthesis for two Indian districts: insights from dynamical modelling
Notice bibliographique
Résumé
Background The Modes of Transmission (MOT) synthesis uses a static HIV transmission model to predict distribution of incident infections along subgroups over 1 year, and directs HIV prevention along this distribution. Because the MOT does not consider where sustained transmission is most likely to occur, and does not use parameter combinations fitted to observed epidemic characteristics, its relevance for planning interventions may be limited. Methods We fitted a dynamical HIV/STI heterosexual transmission model to districts Mysore and Belgaum, India. The MOT and dynamical models estimated the proportion of new HIV infections over 1 year due to transmission between female sex workers/clients, their non-commercial partnerships, and low-risk partnerships. We compared predictions from the dynamical model to MOT results using prior and posterior (fitted) parameters. Intervention impact was illustrated using the dynamical model. Results Using prior inputs, the MOT predicted that commercial sex accounted for 66.2–70.6% of incident infections among males, whereas 71.7–74.2% of incident infections among females were due to bridging infections from clients. There was less variability in MOT results when fitted inputs were used. The majority of the remaining new infections in males and females were due to transmission within low-risk partnerships. In contrast, the dynamical model predicted a higher contribution of commercial sex among males (90.7–91.2%), a higher contribution of bridging infections among females (70.5–86.9%), and that <1.5% of infections were due to low-risk partnerships. Dynamical modelling predicted that any intervention that reduces transmission by 20% applied among commercial sex partnerships could decrease overall HIV incidence by 12% in the first year and by 21% in 5 years see Abstract P5-S6.28 table 1. Applying this intervention among non-commercial partnerships of clients reduces overall incidence by 9% in years 1 through 5 because clients continue to become infected from their commercial partnerships. Abstract P5-S6.28 Table 1 Distribution of 1-year incident infections by type of partnership, as predicted by the MOT and a fitted dynamical model Partnership type Median % of incident infections attributable to partnership types (2.5 and 97.5 percentiles) MOT (prior inputs) MOT (posterior inputs) Dynamical model Mysore Belgaum Mysore Belgaum Mysore Belgaum Females Commercial 6.5 (2.4, 14.9) 5.1 (1.9, 12.2) 7.0 (3.3, 13.0) 4.5 (2.0, 8.8) 28.4 (18.6, 35.5) 11.7 (5.7, 15.0) Main partnerships of FSWs/Clients 71.7 (50.4, 88.7) 74.2 (48.6, 90.9) 75.6 (61.0, 87.8) 73.0 (55.4, 84.9) 70.5 (63.6, 80.3) 86.9 (83.5, 92.9) Casual partnerships of FSWs/Clients 0.03 (0.01, 0.09) 0.01 (0.003, 0.04) 0.02 (0.01, 0.07) 0.01 (0.004, 0.04) 0.30 (0.25, 0.38) 0.31 (0.23, 0.38) Low-risk 20.0 (4.6, 40.7) 19.4 (4.3, 44.3) 15.8 (7.1, 29.3) 21.8 (10.9, 38.7) 0.76 (0.31, 1.1) 1.0 (0.61, 1.4) Males Commercial 70.6 (21.4, 92.6) 66.2 (14.3, 92.8) 66.0 (40.6, 81.1) 69.1 (41.7, 84.3) 91.2 (90.8, 95.6) 90.7 (88.4, 96.1) Main partnerships of FSWs/Clients 9.8 (3.4, 21.3) 10.8 (3.6, 20.9) 11.3 (6.1, 20.2) 9.6 (4.2, 19.5) 6.3 (3.4, 8.1) 7.3 (2.9, 9.2) Casual partnerships of FSWs/Clients 2.0 (0.5, 4.0) 4.5 (1.2, 9.9) 1.7 (0.66, 3.7) 3.8 (1.3, 8.3) 0.5 (0.3, 0.6) 0.87 (0.51, 1.2) Low-risk 15.6 (2.8, 58.5) 13.0 (1.6, 65.8) 19.7 (10.0, 36.9) 14.9 (6.0, 35.4) 0.6 (0.3, 0.9) 1.0 (0.37, 1.4) FSW, female sex worker; MOT, Modes of Transmission. Conclusion Prior inputs for the MOT will not reflect observed HIV prevalence, and as a result, will produce greater variability in MOT predictions. Allocating resources along a 1-year distribution of incident infections can prioritise prevention to the wrong subgroups because they do not account for the dynamic effects of interventions. Improved methods of epidemic appraisals are urgently needed to guide prevention programming.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».