Abstract: A Better Way to Analyze Epidemics?
In this talk, I will discuss the “incidence vs. cumulative-cases” (ICC) curve as a novel perspective on the traditional description of disease data. Through a stochastic representation of the SIR compartmental epidemic model, we will uncover statistical properties that appear only in the ICC phase plane. We will explore how locally fitting SIR ICC curves to synthetic data can be used to quantify changes in a trajectory resulting from both SIR or non-SIR dynamics. Finally, we will apply this methodology to US COVID-19 case data, in order to identify when the epidemic changed across the US and to quantify said changes. This is joint work with Joceline Lega, Faryad Sahneh, and Joe Watkins.