Building Robust & Inclusive Democracy
Thomas Stopka

Thomas Stopka

Ph.D., M.H.S.
Thomas Stopka

Research/Areas of Interest

Dr. Thomas Stopka, PhD, MHS, is an Epidemiologist and Professor with the Department of Public Health and Community Medicine at the Tufts University School of Medicine. Dr. Stopka's current mixed methods research focuses on the intersection of substance use disorder, opioid overdose, and infectious diseases (HCV, HIV, STIs). He employs geographic information systems (GIS), spatial epidemiological, qualitative, and biostatistical approaches in multi-site, interdisciplinary studies, and public health interventions to better understand and curb opioid-related morbidity and mortality. He is currently MPI on four clinical trials and observational studies funded by the NIH, CDC, and SAMHSA to test new mobile telemedicine-based HCV treatment and harm reduction models; employ Bayesian spatiotemporal models to predict opioid overdose spikes to inform pre-emptive public health responses; and evaluate the overdose prevention impacts of administration of extended-relief buprenorphine in corrections facilities, and examine xylazine exposure and the risk of skin and soft tissue infections among people who inject drugs. Dr. Stopka is also Co-Chair of the Tufts Research Cluster focused on Equity in Health, Wealth, and Civic Engagement, and Co-Chair of the Public Health and Community Medicine Departmental Research Committee at Tufts. He teaches courses in GIS and spatial epidemiology, research methods for public health, and epidemiology. He enjoys mentoring research assistants, graduate students, postdoctoral fellows, and faculty.

Education

  • Doctor of Philosophy, University of California, Davis, Davis, United States, 2012
  • Master of Health Science, Johns Hopkins University, Baltimore, United States, 1999
  • Bachelor of Science, Fairfield University, Fairfield, United States, 1992

Biography

Dr. Stopka is an Epidemiologist and Professor with the Department of Public Health and Community Medicine at the Tufts University School of Medicine. Through his research, Dr. Stopka explores the interconnectedness of substance use, social and behavioral risk factors, and overdose and infectious disease outcomes among high-risk and often hidden populations through community-engaged, interdisciplinary, multi-methods, applied epidemiological research studies. His major research interests focus on the overlap substance use, infectious disease (HCV, HIV, and STIs), and opioid overdose. He employs qualitative, biostatistical, geographic information systems (GIS), spatial epidemiological, and laboratory approaches in his studies to assess the risk landscape, access to health services, and implement and test public health and clinical interventions to address health disparities. Dr. Stopka is currently a multi-Principal Investigator (MPI) on four National Institute on Drug Abuse (NIDA)-funded studies that aim to: 1) Predict future opioid overdoses in Massachusetts employing Bayesian spatiotemporal models to inform pre-emptive public health responses; 2) determine the best timing for extended-release medications (XR-Buprenorphine) for opioid use disorder among incarcerated people in Massachusetts; and 3) assess the effectiveness of a mobile telemedicine-based hepatitis C treatment intervention among rural people who inject drugs. He is also a Co-Investigator on the National Institute of Health (NIH)-funded HEALing Communities Study to reduce opioid overdose deaths in Massachusetts, in which he is leading GIS and spatial epidemiological analyses. These and other studies that Dr. Stopka is working on employ: 1) ethnographic and qualitative approaches to assess contextual factors tied to salient exposures and outcomes of interest and to generate hypotheses; 2) innovative epidemiological, legal, and policy scans to assess substance use-related morbidity and mortality and health services landscape; 3) spatiotemporal methods to explore the distribution of measures that affect risk, and to determine the geolocation of and access to current services, as well as gaps; 4) Bayesian spatiotemporal dynamic modeling approaches to inform small area forecasting of opioid-related mortality; and 5) examine xylazine exposure and the risk of skin and soft tissue infections among people who inject drugs.