Neural networks for endemic measles dynamics: comparative analysis and integration with mechanistic models
Wyatt G. Madden,
Wei Jin,
Benjamin Lopman
et al.
Abstract:Measles is an important infectious disease system both for its burden on public health and as an opportunity for studying nonlinear spatio-temporal disease dynamics. Traditional mechanistic models often struggle to fully capture the complex nonlinear spatio-temporal dynamics inherent in measles outbreaks. In this paper, we first develop a high-dimensional feed-forward neural network model with spatial features (SFNN) to forecast endemic measles outbreaks and systematically compare its predictive power with tha… Show more
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