Can Social Network Analysis Help Address the High Rates of Bacterial Sexually Transmitted Infections in Saskatchewan?

• Published in: Sexually transmitted diseases Vol. 44; no. 6; p. 338
• Main Authors: Trecker, Molly A, Dillon, Jo-Anne R, Lloyd, Kathy, Hennink, Maurice, Jolly, Ann, Waldner, Cheryl
• Format: Journal Article
• Language: English
• Published: United States 01.06.2017
• Subjects: Adolescent; Adult; Age Distribution; Chlamydia Infections - epidemiology; Chlamydia Infections - prevention & control; Chlamydia Infections - transmission; Cluster Analysis; Coinfection - epidemiology; Coinfection - prevention & control; Contact Tracing; Cross-Sectional Studies; Female; Gonorrhea - epidemiology; Gonorrhea - prevention & control; Gonorrhea - transmission; Health Knowledge, Attitudes, Practice; Health Promotion; Humans; Male; Poisson Distribution; Public Health; Recurrence; Risk Factors; Saskatchewan - epidemiology; Sex Work - statistics & numerical data; Sexual Partners; Sexually Transmitted Diseases, Bacterial - epidemiology; Sexually Transmitted Diseases, Bacterial - prevention & control; Sexually Transmitted Diseases, Bacterial - transmission; Social Support; Substance-Related Disorders - epidemiology; Unsafe Sex - statistics & numerical data; Young Adult
• ISSN: 1537-4521
• DOI: 10.1097/OLQ.0000000000000599

Saskatchewan has one of the highest rates of gonorrhea among the Canadian provinces-more than double the national rate. In light of these high rates, and the growing threat of untreatable infections, improved understanding of gonorrhea transmission dynamics in the province and evaluation of the current system and tools for disease control are important. We extracted data from a cross-sectional sample of laboratory-confirmed gonorrhea cases between 2003 and 2012 from the notifiable disease files of the Regina Qu'Appelle Health Region. The database was stratified by calendar year, and social network analysis combined with statistical modeling was used to identify associations between measures of connection within the network and the odds of repeat gonorrhea and risk of coinfection with chlamydia at the time of diagnosis. Networks were highly fragmented. Younger age and component size were positively associated with being coinfected with chlamydia. Being coinfected, reporting sex trade involvement, and component size were all positively associated with repeat infection. This is the first study to apply social network analysis to gonorrhea transmission in Saskatchewan and contributes important information about the relationship of network connections to gonorrhea/chlamydia coinfection and repeat gonorrhea. This study also suggests several areas for change of systems-related factors that could greatly increase understanding of social networks and enhance the potential for bacterial sexually transmitted infection control in Saskatchewan.