Computational power is cheaper and more available than ever, making data modeling increasingly relevant to the field of public health. For Eric Collins, a student in the Department of Chronic Disease Epidemiology, the Public Health Modeling Concentration not only opens up career opportunities, but gives him an opportunity to develop a mathematical skill set that can have a direct impact on public health decision making. “In Transmission Dynamic Modeling of Infectious Diseases, for example, I learned to break down and track an epidemic via a system of differential equations,” says Eric. “That a series of equations can inform a public health decision with minimal resources is exciting and impactful.”
Trained in biology and chemistry, Eric is also working with Associate Professor Andrew DeWan on genome-wide association studies (GWAS). While this research was considered strictly academic for the last generation, it is now coming into its own. The cost of whole-genome sequencing has plummeted in the past decade. An individual can now have their genome sequenced for about $1000. As such, insights gained from GWAS can now be realistically applied to population health and the development of personalized medicine. The Modeling Concentration, says Eric, allows him to swim in the deep waters of mathematics necessary to so many aspects of understanding genetic associations and population health, whether it be in chronic or infectious diseases.