Morning Plenary Lecture

The use of mathematical models to understand and control viral pathogens

presented by

Katia Koelle

Assistant Professor
Duke University

Abstract: Scientists studying infectious diseases talk about three epidemiological transitions: the first during the time of animal domestication and human population growth, when infectious diseases were able to establish in human populations, the second during the industrial revolution, when infectious diseases started to be better controlled through improved sanitation measures, and the third just recently as the burden of infectious diseases started to rise again due to the spread of drug resistance and increased urbanization, among other factors. In my talk, I will focus on how mathematical models can be used to better understand the propagation and spread of diseases belonging to the third transition. First, I will focus on dengue dynamics in Thailand, where the burden of the disease has increased and the average age of infected cases has doubled over the last 30 years. I will show how a mathematical model can parsimoniously explain these data and elaborate on the implications of this model for the development of dengue control strategies. Second, I will focus on how mathematical models can be used to understand how viruses, such as influenza and norovirus, evolve over time and how this evolution will affect the possibility of becoming reinfected. Specifically, I will present how using a framework based on a dimensionless number (a concept frequently used in physics) can help us anticipate how quickly viruses will diversify, and what we can do from a public health perspective to reduce viral diversification rates. Together, these two examples illustrate how viruses can rapidly change over time- either in their disease dynamics or in their population structure- and how mathematical models can be used to understand these changes and, equally importantly, to guide us in developing smart, but possibly counterintuitive, control measures.

Biosketch: Dr. Katia Koelle received her Ph.D. from the Department of Ecology and Evolutionary Biology at the University of Michigan in 2005. She was advised by Mercedes Pascual on her dissertation topic, which focused on the role that climate plays in the disease dynamics of cholera. Dr. Koelle then continued her work in disease ecology at the Center for Infectious Disease Dynamics at Penn State. While there, her research started to focus on rapidly evolving RNA viruses such as influenza. In 2007, she joined the Biology faculty at Duke University. Since then, she has continued to work on using mathematical and statistical approaches to better understand viral evolution and disease dynamics. Beyond influenza, she has focused on using models to look at the changing patterns of dengue epidemics and to explore the diversity of evolutionary patterns observed in viruses. Her work also addresses how an improved understanding of these patterns can be used to guide disease control strategies. She teaches a class on mathematical models in biology, as well as classes on disease ecology and evolution.


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