Dr. Mike Ludkovski and Dr. Jarad Niemi (UCSB Statistics and Applied Probability)

Title: Optimal Dynamic Policies for Influenza Management

Abstract: Management policies for influenza outbreaks balance the expected morbidity and mortality costs versus the cost of intervention policies. We present a methodology for dynamic determination of optimal policies in stochastic compartmental models with parameter uncertainty. Our approach is simulation-based and searches the full set of sequential control strategies. For each time point, it generates a policy map describing the optimal intervention to implement as a function of outbreak state and Bayesian parameter posteriors. As a running example, we study a fully observed stochastic SIR model with isolation and vaccination as two possible interventions. Numerical simulations based on a classic influenza outbreak are used to explore the impact of various cost structures on management policies. We also discuss more complex inference schemes based on incomplete observations.

This talk is geared towards graduate students and will combine both statistical and probabilistic techniques.

Paper URL: http://www.bepress.com/scid/vol2/iss1/art5