Title: On the application and theory of ODE compartmental models in epidemiology



Many methodologies in disease modeling have proven invaluable in the evaluation of health interventions. Of these methodologies, one of the most fundamental is compartmental modeling. Compartmental models come in many different forms, with one of the most popular amongst disease modelers being the use of systems of ordinary differential equations.

So, to begin my talk, I will illustrate how such models can inform on public health and evolutionary biology issues, using HIV and Hepatitis G co-infection as proof of concept. Next, I will show how the theoretical extension of ODE compartmental models beyond their traditional formulations can provide even greater insights into disease transmission. Specifically, I will show how generalizing model rates can inform on measles elimination and re-emergence times. Furthermore, I will explain how generalizing the concept of “disease quantity” yields simple gonorrhea models with potentially periodic behavior, reduces model complexity, and more accurately reflect the epidemiology of diseases. Finally, I provide a brief summary and overview of current work and future directions. 

About AI4PAN Artificial Intelligence for Pandemics Seminar Series centred at UQ

Welcome to AI4PAN, the Artificial Intelligence for Pandemics group centered at The University of Queensland (UQ). The group's focus is the application of data science, machine learning, statistical learning, applied mathematics, computation, and other "artificial intelligence" techniques for managing pandemics both at the epidemic and clinical level.