Projects on Modeling Bacteria Spread

This project will be run by Brittany Stephenson and Cara Sulyok. It investigates the community transmission of Clostridioides difficile (C. difficile) using both systems of ordinary differential equations (ODEs) and agent-based models (ABMs) to determine optimal strategies for mitigating the spread of this bacteria. While C. difficile remains one of the most common causes of healthcare-associated infections in the United States, data from the Emerging Infections Program at the Centers for Disease Control and Prevention has shown a decrease in the overall burden of C. difficile in healthcare settings from 2011 to 2017. During that same time period, no such decrease occurred in community-associated infection, which accounted for nearly 50% of the burden of C. difficile infection (CDI) in 2017. Many mathematical models have been developed to understand C. difficile transmission in healthcare settings, but there has been a noticeable absence of models to understand C. difficile transmission in communities, especially with a focus on what could lead to a CDI outbreak.

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Recommendations from mathematical models regarding disease control are sensitive to underlying assumptions, and there are trade-offs when choosing different modeling techniques. By developing mathematical models using both ODEs and agent-based modeling techniques, the analysis of both models can be compared to determine the most effective strategies for mitigating the spread of C. difficile in communities. In completing these aims, we will help identify the main causes for an outbreak of CDIs in a community and methods to eliminate or reduce the potential spread of this bacteria.