Jon A. Wellner Lecture

The 2022 Jon A. Wellner Lecture

Tuesday, March 29, 2022
3:00 p.m. – Lecture in TLC 031 
4:00 p.m. – Refreshments in the IRIC Atrium

Title

Fitting stochastic epidemic models to noisy surveillance data: are we there yet?

Speaker

Vladimir N. Minin, Ph.D.
Professor, Department of Statistics and Associate Director of the Infectious Disease Science Initiative, University of California, Irvine

Abstract

Stochastic epidemic models describe how infectious diseases spread through a population of interest. These models are constructed by first assigning individuals to compartments (e.g., susceptible, infectious, and recovered) and then defining a stochastic process that governs the evolution of sizes of these compartments through time. I will review multiple lines of attack of a challenging and not fully solved problem of fitting these models to noisy infectious disease surveillance data. These solutions involve a range of mathematical techniques: particle filter Markov chain Monte Carlo algorithms, approximations of stochastic differential equations, and Poisson random measure-based Bayesian data augmentation. Importantly, many of these computational strategies open the door for integration of multiple infectious disease surveillance data streams, including less conventional ones (e.g., pathogen wastewater monitoring and genomic surveillance). Such data integration is critical for making key parameters of stochastic epidemic models identifiable. I will illustrate the state-of-the-art statistical inference for stochastic epidemic models using Influenza, Ebola, and SARS-CoV-2 surveillance data and will conclude with open problems and challenges that remain to be addressed.

About the Speaker

Minin’s research interests revolve around developing statistically rigorous solutions to problems that arise in biological sciences. These solutions often involve formulating stochastic models that can describe complex dynamics of biological systems and devising computationally efficient algorithms to fit these models to data. Minin is currently most active in infectious disease epidemiology, working on Bayesian estimation of disease transmission model parameters. His other research interests include phylogenetics, population genetics, computational immunology, and systems biology. Minin received a B.S. in Mathematics from Odesa National University, an M.S. in Mathematics from the University of Idaho, and a Ph.D. in Biomathematics from the University of California, Los Angeles.

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