01mar12:00 pm1:00 pmThe Underlying Conditions Seminar: “Why Do Some Uses of Pathogen Genetic Sequence Data Reveal Underlying Infrastructures?: The Cases of HIV and SARS-CoV-2.” with Dr. Stephen Molldrem on March 1st
Dr. Stephen Molldrem is a UC President's Postdoctoral Fellow at the University of California, Irvine in the Department of Anthropology. He received his PhD in American Culture with
Dr. Stephen Molldrem is a UC President’s Postdoctoral Fellow at the University of California, Irvine in the Department of Anthropology. He received his PhD in American Culture with a Graduate Certificate in Science, Technology, and Society (STS) from the University of Michigan in 2019. Stephen is an interdisciplinary researcher situated at the intersection of sexuality studies, critical health studies, data studies, and bioethics. Methodologically, he employs health policy analysis, ethnography, and approaches from STS such as infrastructure studies and actor-network theory. Stephen’s work brings the concerns of critical digital studies to central questions in health policy and digital governance. His book project is titled The Failure and Promise of Digital Healthcare Reform: Health Data Justice, HIV Surveillance, and the Future of Single-Payer. It shows how U.S. federal initiatives to digitize health data infrastructures have been key drivers of changes in how health institutions manage sexual risk, people living with HIV, and sexual and gender minorities. The project critiques “value-based” approaches to U.S. healthcare reform that dominated the 2010s, and argues for ethically maximizing digital tools to deliver services to marginalized groups that have been left behind by revolutions in digital health and market-based approaches to healthcare reform. He has recently published first or sole-authored articles in The American Journal of Bioethics, First Monday, and Health Policy. Stephen has a special interest in understanding how federal policies are implemented in local ecologies of biomedical, public health, and community-based actors. He studies federal policy transformations in digital health, HIV, and LGBTQ health policy from the period of 2009 onward, and also conducted over two years of fieldwork on these topics in metropolitan Atlanta’s HIV/AIDS and LGBTQ health safety nets from 2016-2019. Stephen is an engaged scholar involved in policy work in LGBTQ health, HIV, and health IT with multiple stakeholder groups. He lives in Long Beach, CA, where he organizes with the local chapter of the Democratic Socialists of America (DSA).
This work-in-progress considers recent controversies in the subfield of pathogen genomic epidemiology that have had the effect of revealing the underlying infrastructures that enable research and public health work in this area. By using open source phylogenetic software packages to analyze pathogen genetic sequence data – often in publicly-available or open datasets – genomic epidemiologists can reveal increasingly detailed information about pathogen transmission patterns, antimicrobial resistance, and other disease dynamics. However, these approaches have generated controversy, often over questions of methodological accuracy, informed consent, ethical data re-use, and the potential for increased stigma among affected populations. In the case of HIV, the 2018 rollout of “HIV molecular cluster detection and response” initiatives in the United States has led some advocates (including networks of people living with HIV) to ask the U.S. Centers for Disease Control and Prevention to pause these programs. In the case of SARS-CoV-2, public discussions of “variants,” “strains,” and “types” have raised questions about when researchers should release preliminary results as well as how public health agencies ought to respond to claims about SARS-CoV-2 evolution toward greater transmissibility as part of COVID-19 disease control. In the cases of both HIV and SARS-CoV-2, controversies over the introduction of phylogenetic analysis into disease control have rendered underlying public health and research data infrastructures acutely visible in new ways, revealing aspects of their operation that are otherwise quite opaque. In this work, I explore why uses of pathogen genetic sequence data seem to generate controversies with this specific effect.
(Monday) 12:00 pm - 1:00 pm(GMT-7:00) View in my time