Model shows incarceration an independent factor in HCV transmission among people who inject drugs
REVIEWED BY: Stacey McKenna, Ph.D.
Hepatitis C is the most common blood-borne infection in the United States, causing either acute or chronic liver disease with a significant proportion of cases culminating in cancer, cirrhosis and death. Nationwide, approximately 3.6 million individuals have antibodies indicating exposure to the hepatitis C virus (HCV). Of these, two-thirds to three-quarters are currently living with an active infection, and estimated prevalence in the U.S. population hovers around 1 percent.
However, certain vulnerable groups are at much higher risk of infection and disease. In particular, HCV rates are extremely and disproportionately high among incarcerated individuals (17.4 to 23.1 percent) and people who inject drugs (PWID) (30 to 70 percent). Furthermore, these two risk categories often overlap. Globally, more than half (58 percent) of PWID have been incarcerated at some point.
Community harm reduction efforts such as syringe exchange and opioid replacement therapy can reduce an individual’s risk for HCV, but such programs are not widespread in the U.S. and are exceedingly rare in the nation’s prisons and jails. In addition, few studies have sought to quantify the role that jail or prison harm reduction efforts play—as well as incarceration itself—in the transmission of HCV among at-risk populations in the United States.
To fill this gap, a team of U.S. and U.K.-based researchers modeled the effects of community and prison-based interventions on HCV transmission among PWID. The study, published in the International Journal of Drug Policy, adapted an existing model that first author Jack Stone and others had used in Scotland to fit the specific context of Perry County, Kentucky, in rural Appalachia.
In the adapted model, Stone et al. stratified PWID according to incarceration state, HCV status, and use of community or jail/prison-based harm reduction (needle/syringe programs and/or opioid substitution therapy), assuming populations mixed freely in the community.
This resulted in the following scenarios:
- Status Quo: Community opioid substitution therapy (OST) coverage low; no needle and syringe programs (NSP).
- Scenario S1*: Community OST 50 percent coverage among PWID; no retention upon incarceration.
- Scenario S1: Community OST and NSP 50 percent among PWID; no retention upon incarceration.
- Scenarios S2/S2*: S1/S1* levels of community harm reduction in place; prison OST has same retention rate as community OST, but no recruitment during incarceration and no retention upon release.
- Scenarios S3/S3*: S2/S2* intact; incarcerated PWID are recruited into OST programs at the same rate as community PWID.
- Scenarios S4/S4*: Scenarios S3/S4* [sic] continue; all PWID are retained on OST for six months following release.
- S5: All features of Scenario S4 hold; drug use is decriminalized following Portugal’s model, which permits possession, trading criminal charges for voluntary treatment referrals.
In each of these scenarios, PWID move through states of incarceration, OST or NSP use and associated susceptibility to HCV. Some become infected and can pass the virus along; others remain susceptible to infection. Stone et al. used this model to predict the effects of each of the above scenarios over a 10-year period from 2020 to 2030 and to compare the respective percentages of new HCV infections that were avoided in each. In addition, they ran a model to examined how HCV incidence would be affected if OST did not affect rates of incarceration and re-incarceration.
The models produced a number of findings that indicate changes to drug (de)criminalization and harm reduction policy could dramatically reduce HCV incidence.
The baseline or Status Quo model suggests that a substantial number of PWID are currently incarcerated and that many are repeatedly re-incarcerated, such that PWID spend nearly half (47.1 percent) of their injecting career actively or recently incarcerated, both of which increase their HCV risk. Subsequent modeling finds that if incarceration and recent release did not alleviate HCV transmission “42.7% (15.0-67.4%) of new HCV infections” could be prevented.
In addition, the model indicates that increasing OST and NSP coverage in communities during incarceration and on release would have substantial benefits, especially if carried out in tandem. In S4, representing what the authors refer to as a “comprehensive harm reduction” scenario where community OST and NSP are 50 percent among PWID, individuals are retained and new individuals recruited in OST during incarceration and OST retention levels hold for six months upon release, nearly half (45.3 percent) of new HCV infections could be prevented.
Perhaps unsurprisingly, the models demonstrate that transmission could be further affected simply by reducing incarceration. In scenario S5, which assumes both comprehensive harm reduction and drug decriminalization beginning in 2020, incarceration rates were halved and 56.8 percent of new infections were prevented. Significantly, the authors note that because community harm reduction coverage in Appalachia remains low, this model indicates that the benefits of preventing incarceration are not solely about maintaining access to harm reduction programs.
Because models are predictive rather than explanatory, they depend on assumptions, such as the notion that PWID have a certain likelihood of acquiring and transmitting HCV or that harm reduction interventions reduce this risk while current and recent incarceration increase it. These assumptions are a potential weakness of the research, but modelers can optimize the accuracy of their output by basing their assumptions on real-life data. Where possible, this is exactly what Stone et al. did. For example, they used findings from the Social Networks Among Appalachian People study to build their assumptions about HCV transmission and incarceration history, as well as to build a Status Quo Scenario low to no community harm reduction. Similarly, they based assumptions about the role OST typically plays in the cycle of incarceration on studies from Australia and Canada. In doing so, the researchers eliminated many possible weaknesses that could have impacted the study.
Interestingly, because they did make the model so situation-specific, generalizability may be weak. Rural Appalachia currently accounts for a disparate percentage of HCV infections and has poor harm reduction programs in place relative to more urban settings. As such, there is a need for additional modeling efforts focused on different contexts.
Nonetheless, these limitations do not diminish the model’s predictions, which are rooted in real data. Overall, this study fills an important gap as the first U.S.-oriented analysis of how both community and incarceration-based prevention interventions affect HCV transmission among PWID. The findings provide initial direction for policy-makers and researchers and highlight the potential for both harm reduction and decriminalization as public health measures.