Theme: Epidemiology & Public Health Research Year: 2019
Background: Recent outbreaks of hepatitis C virus (HCV) among people who inject drugs demonstrate
the failure to implement evidence-based prevention and treatment strategies appropriately in
communities where they are needed. Expanded use of Global Hepatitis Outbreak Surveillance
Technology (GHOST), an automated cloud-based system that uses next-generation sequencing data to
conduct molecular surveillance, strain characterization and identify HCV transmission clusters, may
advance prevention efforts by enhancing the ability of health departments to efficiently target
resources.
Methods: Serum specimens from individuals who undergo fee-exempt confirmatory HCV RNA testing at
sites supported by the Wisconsin Department of Health Services (DHS) are routinely analyzed and stored
at the state’s public health laboratory. These instances reflect testing done in public health settings such
as syringe exchange programs and correctional facilities, and not traditional healthcare settings,
resulting in a sample enriched with younger persons with a history of injection drug use. We
retrospectively identified individuals who tested HCV RNA-positive at sites supported by DHS from 2016
to 2017. Frozen residual serum specimens corresponding to these individuals were removed from
storage and shipped to the GHOST center where a novel amplicon-based Illumina MiSeq sequencing
protocol that targets the hypervariable region of the HCV genome was implemented. Sequence data
was uploaded to the GHOST portal where HCV transmission networks were inferred and visualized.
Preliminary Results: Between 2016 and 2017, 459 individuals tested HCV RNA-positive in public health
settings in Wisconsin. Of these, 10% of samples failed PCR amplification and sequencing. Among the first
110 specimens processed, transmission network analysis showed that 22 individuals were linked into 9
clusters for an overall clustering rate of 20%. Genotype 1a (63%) was the most common circulating
strain, followed by 3a (26%), 3b (5%), 1b (3%), 2a (1%) and mixed genotypes (2%).
Conclusion: Capitalizing on scientific innovations in genomic sequencing and an existing laboratory
infrastructure that processes specimens collected in public health settings provides an opportunity to
conduct an epidemiologic investigation of transmission networks involving populations’ key to the
spread of HCV.
Disclosure of Interest Statement: The authors have no conflicts of interest to disclose.