Hepatitis C data justice: the implications of data-driven approaches to the elimination of hepatitis C

Abstract

The World Health Organization’s goal of achieving hepatitis C elimination by 2030 is inspiring the use of novel methods to find, diagnose and treat people living with the virus. Globally, rates of hepatitis C treatment uptake have declined. Data-driven public health approaches, including case finding, notification and contact tracing, are being developed and implemented to reach the elimination goal. Drawing on interviews with policymakers, lawyers, peers and others who work with people with hepatitis C, we analyse perceptions of the use of data-driven interventions to achieve elimination, and concerns about risks. While interviewees expressed some enthusiasm for data-driven interventions, they were apprehensive about the possible effects of data collection processes and systems and/or believed that people with hepatitis C were. They noted concerns about the sharing of people’s health data without active consent, and worried that data-driven approaches could perpetuate hepatitis C-related stigma and discrimination. We explore these concerns through the concept of data justice, which helps to account for complexities, risks, and challenges. We argue that data-driven interventions to increase access to treatment will be effective and beneficial only if they also address, or at least do not increase, the barriers to treatment caused by stigma, criminalisation and structural inequities faced by many people with hepatitis C. Such interventions should also be designed to mitigate the limitations of the most usual models of data collection and use.