In the United States, clinical HIV data reported to surveillance systems operated by jurisdictional departments of public health are re-used for epidemiology and prevention. In 2018, all jurisdictions began using HIV genetic sequence data from clinical drug resistance tests to identify people living with HIV in "clusters" of others with genetically similar strains. This is called "molecular HIV surveillance" (MHS). In 2019, "cluster detection and response" (CDR) programs that re-use MHS data became the "fourth pillar" of the national HIV strategy. Public health re-uses of HIV data are done without consent and are a source of concern among stakeholders. This article presents three cases that illuminate bioethical challenges associated with re-uses of clinical HIV data for public health. We focus on evidence-base, risk-benefit ratio, determining directionality of HIV transmission, consent, and ethical re-use. The conclusion offers strategies for "HIV data justice." The essay contributes to a "bioethics of the oppressed."
In recent years, applications of big data-driven predictive analytics in public health programs have expanded, offering promises of greater efficiency and improved outcomes. This commentary considers the turn toward predictive modeling in US-based HIV public health initiatives. Through two case studies, we analyze emergent ethical problems and risks. We focus on potential harms related to (1) classifying people living with HIV in public health systems, (2) new ways of combining and sharing individuals' health data that predictive approaches employ, and (3) how new applications of big data in public health challenge the underlying logics and regulatory paradigms that govern data re-uses and rights in public health practice. Drawing on critical technology scholarship, critical bioethics, and advocacy by organized networks of people living with HIV, we argue that stakeholders should enter into a new range of reform-oriented conversations about the regulatory frameworks, ethical norms, and best practices that govern reuses of HIV public health data in the era of predictive public health interventions that target individuals.
Policy Points
Molecular HIV surveillance and cluster detection and response (MHS/CDR) programs have been a core public health activity in the United States since 2018 and are the “fourth pillar” of the Ending the HIV Epidemic initiative launched in 2019.
MHS/CDR has caused controversy, including calls for a moratorium from networks of people living with HIV. In October 2022, the Presidential Advisory Council on HIV/AIDS (PACHA) adopted a resolution calling for major reforms.
We analyze the policy landscape and present four proposals to federal stakeholders pertaining to PACHA's recommendations about incorporating opt‐outs and plain‐language notifications into MHS/CDR programs.
Some early English language news coverage of COVID-19 epidemiology focused on studies that examined how SARS-CoV-2 (the coronavirus that causes COVID-19) was evolving at the genetic level. The use of phylogenetic methods to analyse pathogen genetic sequence data to understand disease dynamics is called 'molecular' or 'genomic' epidemiology. Many research groups in this subfield utilise open science practices, which can involve the circulation of early unreviewed findings on publicly-accessible venues online. From March to May 2020, media outlets covered early SARS-CoV-2 genomic studies that claimed to have discovered types of SARS-CoV-2 that had mutated to be more transmissible. We use methods from Science and Technology Studies (STS) to examine three cumulative cases in which unripe facts about SARS-CoV-2 genomics moved out of scientific publics and into mainstream news. The three cases are: (1) 'A More "Aggressive" Strain of SARS-CoV-2?', (2) 'Eight SARS-CoV-2 Strains?', and (3) 'A "More Contagious," "Mutant" Strain?' In each case, findings were called into question and reporters' framing was overly sensational. We interpret the COVID-19 pandemic as a 'stress-test' for open science practices, and argue that it is important for stakeholders to understand changes in scientific publication and dissemination processes in the wake of the pandemic.
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