Al Scott Prize and Lecture

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.

This event is being held in the regular Modeling seminar spot, and the speaker will present in person.  

Math, 402 and Zoom   https://arizona.zoom.us/j/85889389967    Password:  applied