Hepatitis C Virus Transmission Clusters in Public Health and Correctional Settings, Wisconsin, USA, 2016-20171

Abstract

Ending the hepatitis C virus (HCV) epidemic requires stopping transmission among networks of persons who inject drugs. Identifying transmission networks by using genomic epidemiology may inform community responses that can quickly interrupt transmission. We retrospectively identified HCV RNA-positive specimens corresponding to 459 persons in settings that use the state laboratory, including correctional facilities and syringe services programs, in Wisconsin, USA, during 2016-2017. We conducted next-generation sequencing of HCV and analyzed it for phylogenetic linkage by using the Centers for Disease Control and Prevention Global Hepatitis Outbreak Surveillance Technology platform. Analysis showed that 126 persons were linked across 42 clusters. Phylogenetic clustering was higher in rural communities and associated with female sex and younger age among rural residents. These data highlight that HCV transmission could be reduced by expanding molecular-based surveillance strategies to rural communities affected by the opioid crisis.

Keywords: Hepatitis C virus; United States; Wisconsin; global hepatitis outbreak surveillance technology; hepatitis; injection drug use; molecular epidemiology; phylogenetics; transmission clusters; viruses.

Figure 1

Maximum-likelihood phylogenetic tree of hepatitis C virus hypervariable region 1 consensus sequences from samples from 379 persons in public health and corrections settings, Wisconsin, USA, 2016–2017. The breadth of genetic diversity is shown, and genotypes are labeled. Scale bar indicates nucleotide subsitutions per site.

Figure 2

Hepatitis C virus (HCV) transmission network among persons in public health and corrections settings, Wisconsin, USA, 2016–2017, showing 42 clusters identified by Global Hepatitis Outbreak and Surveillance Technology (GHOST). Each node represents an HCV-infected person for whom HCV sequence data were generated. A transmission link is denoted as a line connecting persons where the minimal Hamming distance between sequences is smaller than the previously validated genetic threshold of 3.77%. Lines connecting clusters are colored according to genotype.

Figure 3

Hepatitis C virus (HCV) transmission network among persons in public health and corrections settings, Wisconsin, USA, 2016–2017, showing intrahost genetic heterogeneity within 1 representative transmission cluster. K-step network contains all possible minimum spanning trees and enables efficient visualization of genetic relatedness among all intrahost hypervariable region 1 (HVR1) variants for persons 338 and 362 (A), persons 338 and 372 (B), and persons 362 and 372 (B). Each node represents an HCV sequence, and the color of the node corresponds to the sample of origin: red, variant found in both samples; green, variant found only in the first sample; blue, variant found only in the second sample. Node size is based on frequency of the HVR1 variant, and edge length is proportional to the modified Hamming distance (does not count positions with insertions or deletions as differences).

Figure 4

Intrahost genetic variation of representative transmission clusters of hepatitis C virus (HCV) among persons in public health and corrections settings, Wisconsin, USA, 2016–2017, highlighting the genetic relatedness of distinct variants. K-step network contains all possible minimum spanning trees and enables efficient visualization of genetic relatedness among all intrahost hypervariable region 1 (HVR1) variants for persons 84 and 86 (A) and persons 281 and 367 (B). Each node represents an HCV sequence. Color of the node corresponds to the sample of origin: green, found only in the first sample; blue, found only in the second sample. The node size is based on frequency of the HVR1 variant, and edge length is proportional to the modified Hamming distance (does not count positions with insertions or deletions as differences).