I am a computational social scientist specializing in modeling biobehavioral health systems to inform policy initiatives to achieve health equity. My research has mostly focused on the prevention of new HIV infections among sexual and gender minorities (SGM), particularly persons of color. More recently, I have extended my portfolio to incorporate substance use behaviors, incarceration, breast cancer screening, and COVID-19.
Among the challenges in reforming policies or implementing effective biobehavioral interventions, a recurring one is the lack of empirical data that can guide effective planning, especially prior to intervention implementation. This challenge is often expressed in a lack of scientific understanding around how public health challenges are diffused through networked communities. For instance, a number of studies have pointed out the increased levels of HIV, sexually transmitted infections, or tobacco smoking in persons involved with the criminal legal system (PCLS), but relatively few have sought to estimate their magnitude in the social networks of PCLS, limiting our ability to address these concerns.
My modeling work fills these gaps by integrating data from diverse sources to create model-based representations of real-world systems. Using these models, I generate data on components of public health systems about which less is known. I work in teams of behavioral and social scientists, clinicians, epidemiologists, statisticians, biologists, and community stakeholders. Over the past several years, I have led the modeling efforts on such teams for a range of public health initiatives.
