Trait-based Approaches to Bridging the Gaps Between Mechanistic and Phenomenological Modeling for Ecological Applications

Online seminar by Prof. Leah Johnson from Department of Statistics Computational Modeling and Data Analytics (CMDA), Virginia Tech

31 January 2024
KST 09:30 – 11:00

Join us online: https://pusan.zoom.us/j/88504588732?pwd=rGoUs38pR80P22K35trmPIw3uuefE2.1 Meeting ID: 885 0458 8732 Passcode: 189869

Models for biological and epidemiological processes run the gamut from phenomenological to mechanistic, including differing amounts of biological information and detail. In this talk, I explore models across this spectrum that are used to understand the spread of vector-borne pathogens. I take a trait-based approach, and show how we can use trait data in multiple ways across these models to enable us to make predictions at different scales in space and time. I explore what kinds of trait data can help us answer different kinds of questions in Vector-Borne Disease systems and for multiple goals, from prediction to understanding.