This area includes developing and applying scenario models for public health decision support, which is centered on the development and application of scenario models to support public health decision-making, with a particular emphasis on developing durable infrastructure for managing infectious disease outbreaks. Some of this work was instrumental in addressing the challenges posed by the COVID-19 pandemic, providing critical insights that guide public health interventions. This work has been central to our CDC Center for Forecasting and Outbreak Analytics InsightNet center grant, ForeSITE: Forecasting and Simulating Infectious Threats and Epidemics in which we work to build and refine modeling tools to enhance our preparedness and response capabilities for future public health emergencies.

A central part of our modeling for public health decision support is on antibiotic resistance and healthcare associated infections. Our research in antibiotic practices and outcomes focuses on optimizing treatment protocols and addressing the challenges of antibiotic resistance, particularly in inpatient settings and within the Veterans Affairs (VA) healthcare system. By analyzing large-scale data on antibiotic prescribing practices, we aim to identify patterns that contribute to the development of resistant infections and to determine the most effective treatments. This work plays a crucial role in enhancing antibiotic stewardship, providing valuable insights that help improve patient care and combat the spread of antibiotic resistance across diverse healthcare settings, including the VA network.