Investigation of a Gonorrhea Outbreak in an Isolated Northern Alberta Community, 2015

Background: In 2014, the rate of Neisseria gonorrhea(NG) in the North-Northwest subzone of Alberta (191/100,000) was four times higher than the provincial rate (46/100,000). Nearly one-third of cases in the subzone were reported from a small isolated community (population estimate: 2000- 2500 people). An investigation of cases was undertaken to determine transmission networks.

Methods: A descriptive summary of all NG cases reported in 2015 from the community was conducted using routinely collected surveillance and partner data. During a two week period in the fall of 2015, cases and contacts were contacted to be re-interviewed to identify local exposure details. NG multiantigen sequence typing was determined and susceptibility to cephalosporins and ciprofloxacin was predicted by RT-PCR using the NAAT specimens. A social network analysis was completed using partner information.

Results: In 2015, there were 84 NG cases reported in the community. All cases were heterosexual, 47.6% (n=40) were female, and 20% (n=8) were pregnant. The median age was 24 years (IQR: 20-30). Twenty-one clients were re-interviewed for local exposure details, representing a participation rate of 19.1% for the 110 gonorrhea cases and contacts. The majority of clients re-interviewed reported limited condom use (90.5%; n=19), being under the influence of alcohol or drugs during sexual encounters (61.1%; n=11), and meeting partners through local house parties (66.7%; n=12). An additional one-third (n=6) of participants met partners on-line. Eight unique STs were identified among 41 cases. 70% (n=29) of the sequence typed cases belong to sequence group ST-7576; one isolate in the province was available from this group and was resistant to erythromycin and tetracycline. SNP assay results were available for 19 specimens among 7 different ST; all were predicted to be susceptible to cephalosporins and ciprofloxacin. There were 21 sexual network components identified, with 33% (n=42) of individuals in network components of three or fewer people. The largest network represents 46.8% (n=59) of cases and contacts.

Conclusion: Using the combination of routine surveillance data, with enhanced exposure details and in depth laboratory data, we were able to ascertain key aspects of the outbreak for local intervention.