MS08 - ECOP-07 Part 2 of 3

Exploring Heterogeneity in Mathematical Models: Methods, Applications, and Insights (Part 2)

Friday, July 18 from 10:20am - 12:00pm in Salon 4

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Organizers:

Zhisheng Shuai (University of Central Florida), Junping Shi, College of William & Mary; Yixiang Wu, Middle Tennessee State University

Description:

This minisymposium will focus on the mathematical modeling of heterogeneity across various biological systems. Heterogeneity often plays a critical role in shaping the dynamics and outcomes of biological processes. The session aims to: (i) Showcase advances in modeling techniques that capture heterogeneity; (ii) Explore the impact of heterogeneity on predictions and control strategies; (iii) Highlight applications spanning population dynamics, epidemiology, ecology and evolution; (iv) Encourage discussions on the integration of data-driven and theoretical approaches to address heterogeneity. We have confirmed 10 speakers, with 2 more awaiting confirmation (one pending administrative approval at the CDC). Among the confirmed speakers, half are female, and over half are junior researchers, including 1 PhD student and 2 postdocs. Please note that we are going to submit another proposal for the total of 12 speakers.

Room assignment: Salon 4



Yuanwei Qi

University of Central Florida
"Mathematical Analysis of a Cancer Invasion Model"
In this talk I shall present some recent results on Global Existence, Stability of various equilibrium points as well as existence of traveling wave to a well established reaction-diffusion system modeling cancer invasion. This is a joint work with Xinfu Chen of University of Pittsburgh, Xueyan Tao and Shulin Zhou of Peking University.



Chunhua Shan

University of Toledo
"Transmission dynamics and bifurcations of a diffusive epidemic model with a nonlinear recovery rate"
In this talk we study the disease transmission dynamics of a diffusive epidemic model with a nonlinear recovery rate. The Hopf bifurcation and Bogdanov-Taken bifurcation are first considered for the corresponding ODE model. Then we analyze the Turing instability and the Turing-Hopf bifurcation. Numerical simulations and biological interpretation are also provided.



Christopher Heggerud

University of California, Davis
"The many mechanisms behind regime shifts and tools to predict them"
Transient dynamics and regime shifts pose unique challenges when dealing with predictions and management of ecological systems yet little headway has been made on understanding when an ecological system might be in a transient state, or if a regime shift is imminent. In particular, given an ecological timeseries, it is difficult to detect the underlying mechanism causing a regime shift, or if one is occurring at all. Through a series of simplifications, we analyze synthetic data known to exhibit crawl-by type transient dynamics or that undergo some nonlinear excursion through state space that appears as a transient dynamic. Using dynamical systems theory, we create metrics that predict transient dynamics and furthermore to understand useful characteristics of the regime shift. These new metrics are additionally compared to typical early warning signals in ecology and the utility of both are discussed.



Poroshat Yazdanbakhsh

Rollins College
"A Novel Approach to Understanding Disease Spread and Population Persistence in Heterogenous Environments"
How do infectious diseases or species populations evolve in heterogeneous environments? This has been one of the most sought-after questions in the field of mathematical biology. In this talk, we aim to address this question by introducing a new measure called the network heterogeneity index, denoted by H. We offer a fresh perspective to better understand how diseases spread and populations persist in heterogeneous environments. Our analysis shows that how H is influenced by several key factors, including the structure of such networks, regional disease or population dynamics, and the movements between regions. To highlight the importance of H, we conclude our talk by exploring its applications in epidemiology and ecology across various heterogeneous settings.



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