483
Views
0
CrossRef citations to date
0
Altmetric
Research Papers

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

ORCID Icon, , , , , , , & show all
Pages 803-813 | Received 06 Apr 2023, Accepted 20 Nov 2023, Published online: 01 Dec 2023
 

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.

Acknowledgements

We thank all participants for agreeing to take part in this research, and for generously offering their time and experience. We also thank the project advisory team for their support, peer reviewers, and journal editors for advice on improving earlier versions. The interviews were conducted by Emily Lenton and Dion Kagan, and were checked for accuracy by Andrew Whalley.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1. Medicare is a national insurance scheme in Australia that provides free or subsidised healthcare.

Additional information

Funding

This work was supported by the Australian Research Council under Grant [DP200100941]. The views expressed are the authors’ own.