Near real-time monitoring of HIV transmission hotspots from routine HIV genotyping: an implementation case study

Background HIV evolves rapidly and therefore infections with similar genetic sequences are likely linked by recent transmission events. Clusters of related infections can represent subpopulations with high rates of transmission. We describe the implementation of an automated near real-time system to monitor and characterise HIV transmission hotspots in British Columbia, Canada. Methods In this implementation case study, we applied a monitoring system to the British Columbia drug treatment database, which holds more than 32 000 anonymised HIV genotypes for nearly 9000 residents of British Columbia living with HIV. On average, five to six new HIV genotypes are deposited in the database every day, which triggers an automated reanalysis of the entire database. We extracted clusters of five or more individuals with short phylogenetic distances between their respective HIV sequences. The system generated monthly reports of the growth and characteristics of clusters that were distributed to public health officers. Findings In June, 2014, the monitoring system detected the expansion of a cluster by 11 new cases during 3 months, including eight cases with transmitted drug resistance. This cluster generally comprised young men who have sex with men. The subsequent report precipitated an enhanced public health follow-up to ensure linkage to care and treatment initiation in the affected subpopulation. Of the nine cases associated with this follow-up, all had already been linked to care and five cases had started treatment. Subsequent to the follow-up, three additional cases started treatment and most cases achieved suppressed viral loads. During the next 12 months, we detected 12 new cases in this cluster with reduction in the onward transmission of drug resistance. Interpretation Our findings show the first application of an automated phylogenetic system monitoring a clinical database to detect a recent HIV outbreak and support the ensuing public health response. By making secondary use of routinely collected HIV genotypes, this approach is cost-effective, attains near real-time monitoring of new cases, and can be implemented in all settings in which HIV genotyping is the standard of care.