Online Program

Spatial Epidemics Prediction by a Random Forest Classifier and Bayesian (309984)

Keywords: Infectious disease, inference, Bayesian

This talk is concerned with the application of two major approaches in statistical inference of infectious disease dynamics. We describe the fitting of a class of epidemic models using Bayesian inference and Machine learning. We apply the two methods to real data from Measles outbreak. Our results suggest that both inference methods are computationally feasible in this context, and show a trade-off between statistical efficiency versus computational speed. The latter appears particularly relevant for real-time applications.