P1-S4.10 The use of social network analysis to quantify the importance of sex partner meeting venues in an infectious syphilis outbreak in Alberta, Canada
Notice bibliographique
Résumé
Background Places where people meet sex partners may play an important role in the propagation of sexually transmitted infections. Social network analysis (SNA) has the potential to quantify the role that places of social aggregation play in syphilis transmission based on a relational approach. The primary objective of this study was to explore the use of SNA as both an epidemiological and methodological tool to determine the relative importance of sex partner meeting venues to the transmission of syphilis, in a sustained infectious syphilis outbreak. Methods In a network survey study, we identified and enrolled 52 cases and named contacts of infectious syphilis among individuals, aged 18−75 years at a Sexually Transmitted Disease clinic in Alberta Canada, during routine public health measures of infectious disease control between April and August, 2009. In addition to standard contact tracing information, participants were asked to list all venues attended in the last 6 months where sexual partnering may have occurred. We constructed a sexual affiliation network by linking together persons infected with syphilis, and their named sexual contacts, to sex partner meeting venues. By transposing the sexual affiliation matrix and applying matrix multiplication we created two separate networks; a network of persons connected by venues and a dual network of venues connected by persons. Hierarchal clustering was performed to model patterns of individual patronage of venues, and network algebraic measures of centrality and permutation statistical methods were used to determine what type of venue connected the most individuals infected with syphilis. Results 77% of participants reported meeting a sex partner at a social venue in the last 6 months. We identified a densely connected sexual affiliation network of 94 men who have sex with men (MSM), comprised of 18 cases of infectious syphilis and 76 named sexual contacts connected by 21 venues. In the network of sex partner meeting venues, Internet venues had higher degree centrality than non-internet venues (p<0.05). In the network of men connected by venues, hierarchal clustering detected a cluster of 35 men linked together by their patronage of three Internet venues see Abstract P1-S4.10 Figure 1. These three Internet venues had the highest degree centrality in the network of sex partner meeting venues and connected two thirds of all infectious syphilis cases. Abstract P1-S4.10 Figure 1 Number and range of projected HIV prevalence estimates for the PB population (from the model fits to KH and DD data). *Integrated biological and behavioural assessment (IBBA) 2009, collected within the monitoring and evaluation of Avahan, the India initiative. Conclusions To our knowledge, this is the first study to use SNA of a sexual affiliation network to quantify the importance of places in an outbreak of infectious syphilis. Network analysis allowed identification of three key venues that connected individuals who were infected with syphilis. These venues could provide public health officials with an epidemiologic target for primary and secondary prevention strategies to prevent further dissemination of disease.
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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| 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) | 0,000 | 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 ».