Factors associated with phylogenetic clustering of hepatitis C among people who inject drugs in Baltimore

Phylogenetic Analysis of Hepatitis C Virus Infections in a Large Belgian Cohort Using Next-Generation Sequencing of Full-Length Genomes

The hepatitis C virus (HCV) epidemic in Western countries is primarily perpetuated by the sub-populations of men who have sex with men (MSM) and people who inject drugs (PWID). Understanding the dynamics of transmission in these communities is crucial for removing the remaining hurdles towards HCV elimination. We sequenced 269 annotated HCV plasma samples using probe enrichment and next-generation sequencing, obtaining 224 open reading frames of HCV (OR497849-OR498072). Maximum likelihood phylogenies were generated on the four most prevalent subtypes in this study (HCV1a, 1b, 3a, 4d) with a subsequent transmission cluster analysis. The highest rate of clustering was observed for HCV4d samples (13/17 (76.47%)). The second highest rate of clustering was observed in HCV1a samples (42/78 (53.85%)) with significant association with HIV-positive MSM. HCV1b and HCV3a had very low rates of clustering (2/83 (2.41%) and (0/29)). The spread of the prevalent subtype HCV1b appears to have been largely curtailed, and we demonstrate the onwards transmission of HCV1a and HCV4d in the HIV-positive MSM population across municipal borders. More systematic data collection and sequencing is needed to allow a better understanding of the HCV transmission among the community of PWID and overcome the remaining barriers for HCV elimination in Belgium.

Hepatitis C Virus in people with experience of injection drug use following their displacement to Southern Ukraine before 2020

BACKGROUND

Due to practical challenges associated with genetic sequencing in low-resource environments, the burden of hepatitis C virus (HCV) in forcibly displaced people is understudied. We examined the use of field applicable HCV sequencing methods and phylogenetic analysis to determine HCV transmission dynamics in internally displaced people who inject drugs (IDPWID) in Ukraine.

METHODS

In this cross-sectional study, we used modified respondent-driven sampling to recruit IDPWID who were displaced to Odesa, Ukraine, before 2020. We generated partial and near full length genome (NFLG) HCV sequences using Oxford Nanopore Technology (ONT) MinION in a simulated field environment. Maximum likelihood and Bayesian methods were used to establish phylodynamic relationships.

RESULTS

Between June and September 2020, we collected epidemiological data and whole blood samples from 164 IDPWID (PNAS Nexus.2023;2(3):pgad008). Rapid testing (Wondfo® One Step HCV; Wondfo® One Step HIV1/2) identified an anti-HCV seroprevalence of 67.7%, and 31.1% of participants tested positive for both anti-HCV and HIV. We generated 57 partial or NFLG HCV sequences and identified eight transmission clusters, of which at least two originated within a year and a half post-displacement.

CONCLUSIONS

Locally generated genomic data and phylogenetic analysis in rapidly changing low-resource environments, such as those faced by forcibly displaced people, can help inform effective public health strategies. For example, evidence of HCV transmission clusters originating soon after displacement highlights the importance of implementing urgent preventive interventions in ongoing situations of forced displacement.

The signal-to-cutoff ratios to predict HCV infection among people who inject drugs

People who inject drugs (PWIDs) are primarily the high-risk population for HCV infection. This study aims to determine the optimal cut-off values for predicting HCV infection status based on the Signal-to-Cutoff (S/CO) ratio. In this study, a total of 719 PWIDs’ samples were collected, and performed for screening test by ELISA assay, and followed by RIBA assay and NAT assay to detect HCV antibody and HCV RNA levels, respectively. The findings revealed that the prevalence of HCV infection among PWIDs was 54.66% (393/719), and the false-positive rate of HCV antibody detection by ELISA assay among PWIDs was only 3.85% (16/416). In addition, when the optimal cut-off value for S/CO ratio was 2.0, the sensitivity and specificity of HCV antibody were 100.00% and 93.55%, respectively. And when the optimal cut-off value for S/CO ratio was 21.36, the sensitivity and specificity of HCV RNA positive were 89.90% and 72.73%, respectively. In conclusion, the status of HCV infection can be predicted based on the S/CO ratios of the ELISA assay, which can improve diagnosis and facilitate timely treatment to effectively prevent the spread of HCV infection.

Molecular and spatial epidemiology of HCV among people who inject drugs in Boston, Massachusetts

Integration of genetic, social network, and spatial data has the potential to improve understanding of transmission dynamics in established HCV epidemics. Sequence data were analyzed from 63 viremic people who inject drugs recruited in the Boston area through chain referral or time-location sampling. HCV subtype 1a was most prevalent (57.1%), followed by subtype 3a (33.9%). The phylogenetic distances between sequences were no shorter comparing individuals within versus across networks, nor by location or time of first injection. Social and spatial networks, while interesting, may be too ephemeral to inform transmission dynamics when the date and location of infection are indeterminate.

HCV communication within ego-centric networks of men and women who inject drugs

INTRODUCTION

Leveraging interpersonal communication among social networks of people who inject drugs (PWID) may be an innovative strategy to increase awareness and access to hepatitis C (HCV) care. However, little is known about HCV communication patterns among PWID and if these patterns vary by gender.

METHODS

Egocentric network data collected at baseline from HCV-infected PWID enrolled in a randomized HCV treatment intervention trial in Baltimore, Maryland were analyzed. Logistic generalized estimating models were conducted to identify predictors of HCV communication.

RESULTS

Among 227 PWID, the mean age was 43.8 (SD=10.3), 28.2% (n = 64) were women and 71.8% (n = 163) were men. Female participants reported 516 dyadic relationships and male participants 1139 dyadic relationships. While there were significant gender differences based on socio-demographics, risk behavior and network composition, there were few differences in HCV communication patterns. Both men and women had increased odds of HCV communication with alters who are currently enrolled in drug treatment (AOR 1.7, 95% CI: 1.3-2.4), alters with whom participants share drug preparation equipment (AOR 3.0, 95% CI: 1.9-4.6), alters who are sex partners compared to kin (AOR 3.0; 95% CI: 1.9-4.9) and alters with whom respondents have increased trust (AOR 1.1; 95% CI: 1.11.2) and daily/weekly interactions (AOR 1.7; 95% CI 1.3-2.1).

CONCLUSION

PWID engaged with trusted alters about HCV disclosure and information, highlighting the important role network interventions could play in this vulnerable population.

Utilising an access to care integrated framework to explore the perceptions of hepatitis C treatment of hospital-based interventions among people who use drugs

BACKGROUND

Gaps remain in the hepatitis C virus (HCV) care cascade for people who use drugs (PWUD). Acute medical or surgical illnesses requiring hospitalisation are an opportunity to address addiction, but how inpatient strategies could affect HCV care accessibility for PWUD remains unknown. We explored patient perspectives of hospital-based interventions using an integrated framework of access to HCV care.

METHODS

We conducted a qualitative study of hospitalised adults (n=27) with HCV and addiction admitted to an urban academic medical centre in the United States between June and November 2019. Individual interviews were audio-recorded, transcribed, and dual-coded. We analysed data with coding specific for hospital-based interventions including screening, conducting HCV-related laboratory work-up, starting treatment, connecting with peers, and coordinating outpatient care. We analysed coded data at the semantic level for emergent themes using a framework approach based off an integrated framework of access to HCV care.

RESULTS

The majority of participants primarily used opioids (78%), were white (85%) and men (67%). Participants frequently reported HCV screening during previous hospitalisation with rare inpatient connection to HCV-related services. Participants expressed willingness to discuss HCV treatment candidacy during hospitalisation; however, lack of inpatient conversations led to perception that "nothing could be done" during admission. Participants expressed interest in completing inpatient HCV work-up to "get the ball rollin'" - consolidating care would enhance outpatient service permeability by reducing barriers. Others resisted HCV care coordination, preferring to focus on "immediate" issues including health conditions and addiction treatment. Participants also expressed openness to engaging with peers about HCV, noting shared drug use experience as critical to a peer relationship when discussing HCV.

CONCLUSION

Hospitalised PWUD have varied priorities, necessitating adaptable interventions for addressing HCV. Hospitalisation can be an opportunity to address HCV access to care including identification of treatment eligibility, consolidation of care, and facilitation of HCV-related referrals.

Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action

The opioid crisis in the United States has been defined by waves of drug- and locality-specific Opioid use-Related Epidemics (OREs) of overdose and bloodborne infections, among a range of health harms. The ability to identify localities at risk of such OREs, and better yet, to predict which ones will experience them, holds the potential to mitigate further morbidity and mortality. This narrative review was conducted to identify and describe quantitative approaches aimed at the "risk assessment," "detection" or "prediction" of OREs in the United States. We implemented a PubMed search composed of the: (1) objective (eg, prediction), (2) epidemiologic outcome (eg, outbreak), (3) underlying cause (ie, opioid use), (4) health outcome (eg, overdose, HIV), (5) location (ie, US). In total, 46 studies were included, and the following information extracted: discipline, objective, health outcome, drug/substance type, geographic region/unit of analysis, and data sources. Studies identified relied on clinical, epidemiological, behavioral and drug markets surveillance and applied a range of methods including statistical regression, geospatial analyses, dynamic modeling, phylogenetic analyses and machine learning. Studies for the prediction of overdose mortality at national/state/county and zip code level are rapidly emerging. Geospatial methods are increasingly used to identify hotspots of opioid use and overdose. In the context of infectious disease OREs, routine genetic sequencing of patient samples to identify growing transmission clusters via phylogenetic methods could increase early detection capacity. A coordinated implementation of multiple, complementary approaches would increase our ability to successfully anticipate outbreak risk and respond preemptively. We present a multi-disciplinary framework for the prediction of OREs in the US and reflect on challenges research teams will face in implementing such strategies along with good practices.