top of page
Learn about our team's ongoing projects.
The Prevention Policy Modeling Lab models the health impact, costs, and cost-effectiveness of infectious disease treatment and prevention programs in the United States. We work closely with collaborators in the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) at the Centers for Disease Control and Prevention to inform U.S. health policy and guide public health decision-making at national, state, and local levels. The models we build incorporate evidence-based prevention strategies, emphasize cross-cutting initiatives and produce results that can be operationalized within healthcare and other sectors.
Prevention Policy Modeling Lab
The ARCH ADEPTT trial studies tuberculosis preventative therapy (IPT) in HIV+ adults in Uganda who drink heavily. The study is meant to evaluate the risks and benefits of IPT within this population. A simulation model component will use results from the trial to simulate out effects at a population level.
The HEALing Communties Study (HCS) is a research study that is testing the impact of an integrated set of evidence-based practices across health care, behavioral health, justice, and other community-based settings to prevent and treat opioid misuse and opioid use disorder within highly affected communities. The findings from HCS will provide communities nationwide replicable best practices for prevention and treatment strategies.
The HEP-CE (Hepatitis C Cost Effectiveness) model is a Monte-Carlo health state-transition model which simulates the spread and treatment of HCV in the United States. The model uses values and information derived from a variety of sources, including clinical data and relevant literature. HEP-CE is used to model the efficacy and cost-effectiveness of treatments, policies, and interventions aimed at controlling the HCV epidemic on a population-wide basis.
The RESPOND (Researching Effective Strategies to Prevent Opioid Death) model is a health state-transition model which simulates opioid use disorder in the state of Massachusetts. The RESPOND model is informed by a variety of literature and clinical data sources, both national and Massachusetts specific. RESPOND can be used to model the efficacy and cost-effectiveness of various interventions or policies aimed at reducing the opioid use epidemic.
bottom of page