By Camilla Fratta, Ananya Jain, Sydney Mason, Gabby Matejowsky, and Nevaeh Pinkney*.

*Nevaeh helped the group work through the problem set but was unfortunately unable to attend camp during the blog writing.

Mathematical Epidemiology explores the realm of mathematics applied to public health. It relies on modeling to use known information about certain scenarios regarding the spread of diseases and then uses it to predict future outcomes. By the end of the problem set, our group learned about the challenging process that comes with trying to predict population sizes in order to control the spreading of diseases. The equations that are faced in this branch of mathematics are at the heart of mathematical modeling.

**Mathematical Models and Modeling**

A mathematical model is an equation used to predict or model the most likely results to occur in a real-world situation. We used these types of equations to model the spread of a disease in a population, tracking the flow of populations from susceptible to infected to recovered. In real life scenarios, there are too many variables to fully account for, so we only were able to place a few in our equations. This made the models less accurate, but at the same time very useful to us in our problem set. They gave us a good idea of how things worked in an actual epidemic and helped us to understand what mathematical modeling really is.